Package evaluation of NuclearToolkit on Julia 1.10.9 (96dc2d8c45*) started at 2025-06-07T03:02:03.720 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 4.65s ################################################################################ # Installation # Installing NuclearToolkit... Resolving package versions... Installed FFMPEG ─ v0.2.4 Updating `~/.julia/environments/v1.10/Project.toml` [89bb3bae] + NuclearToolkit v0.4.5 Updating `~/.julia/environments/v1.10/Manifest.toml` [621f4979] + AbstractFFTs v1.5.0 [1520ce14] + AbstractTrees v0.4.5 [7d9f7c33] + Accessors v0.1.42 [79e6a3ab] + Adapt v4.3.0 [35492f91] + AdaptivePredicates v1.2.0 [66dad0bd] + AliasTables v1.1.3 [27a7e980] + Animations v0.4.2 [dce04be8] + ArgCheck v2.5.0 [7d9fca2a] + Arpack v0.5.4 [2119f1ac] + AssociatedLegendrePolynomials v1.0.1 [67c07d97] + Automa v1.1.0 [13072b0f] + AxisAlgorithms v1.1.0 [39de3d68] + AxisArrays v0.4.7 [198e06fe] + BangBang v0.4.4 [18cc8868] + BaseDirs v1.3.0 [9718e550] + Baselet v0.1.1 [b99e7846] + BinaryProvider v0.5.10 [d1d4a3ce] + BitFlags v0.1.9 [fa961155] + CEnum v0.5.0 [96374032] + CRlibm v1.0.2 [159f3aea] + Cairo v1.1.1 [13f3f980] + CairoMakie v0.13.10 [d360d2e6] + ChainRulesCore v1.25.1 [944b1d66] + CodecZlib v0.7.8 [a2cac450] + ColorBrewer v0.4.1 [35d6a980] + ColorSchemes v3.29.0 [3da002f7] + ColorTypes v0.12.1 [c3611d14] + ColorVectorSpace v0.11.0 [5ae59095] + Colors v0.13.1 [861a8166] + Combinatorics v1.0.3 [34da2185] + Compat v4.16.0 [a33af91c] + CompositionsBase v0.1.2 [f0e56b4a] + ConcurrentUtilities v2.5.0 [187b0558] + ConstructionBase v1.5.8 [6add18c4] + ContextVariablesX v0.1.3 [d38c429a] + Contour v0.6.3 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [244e2a9f] + DefineSingletons v0.1.2 [927a84f5] + DelaunayTriangulation v1.6.4 [8bb1440f] + DelimitedFiles v1.9.1 [31c24e10] + Distributions v0.25.120 [ffbed154] + DocStringExtensions v0.9.4 [4e289a0a] + EnumX v1.0.5 [429591f6] + ExactPredicates v2.2.8 [460bff9d] + ExceptionUnwrapping v0.1.11 [e2ba6199] + ExprTools v0.1.10 [411431e0] + Extents v0.1.6 ⌃ [c87230d0] + FFMPEG v0.2.4 [7a1cc6ca] + FFTW v1.9.0 [cc61a311] + FLoops v0.2.2 [b9860ae5] + FLoopsBase v0.1.1 [5789e2e9] + FileIO v1.17.0 ⌅ [8fc22ac5] + FilePaths v0.8.3 [48062228] + FilePathsBase v0.9.24 [1a297f60] + FillArrays v1.13.0 [53c48c17] + FixedPointNumbers v0.8.5 [1fa38f19] + Format v1.3.7 [b38be410] + FreeType v4.1.1 [663a7486] + FreeTypeAbstraction v0.10.7 [28b8d3ca] + GR v0.73.16 [68eda718] + GeoFormatTypes v0.4.4 [cf35fbd7] + GeoInterface v1.4.1 [5c1252a2] + GeometryBasics v0.5.9 [c27321d9] + Glob v1.3.1 [a2bd30eb] + Graphics v1.1.3 [3955a311] + GridLayoutBase v0.11.1 [42e2da0e] + Grisu v1.0.2 [f67ccb44] + HDF5 v0.17.2 [cd3eb016] + HTTP v1.10.16 [f0d1745a] + HalfIntegers v1.6.0 [34004b35] + HypergeometricFunctions v0.3.28 [2803e5a7] + ImageAxes v0.6.12 [c817782e] + ImageBase v0.1.7 [a09fc81d] + ImageCore v0.10.5 [82e4d734] + ImageIO v0.6.9 [bc367c6b] + ImageMetadata v0.9.10 [9b13fd28] + IndirectArrays v1.0.0 [d25df0c9] + Inflate v0.1.5 [22cec73e] + InitialValues v0.3.1 [18e54dd8] + IntegerMathUtils v0.1.2 ⌅ [a98d9a8b] + Interpolations v0.15.1 [d1acc4aa] + IntervalArithmetic v0.22.35 [8197267c] + IntervalSets v0.7.11 [3587e190] + InverseFunctions v0.1.17 [92d709cd] + IrrationalConstants v0.2.4 [f1662d9f] + Isoband v0.1.1 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [033835bb] + JLD2 v0.5.13 [1019f520] + JLFzf v0.1.11 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [b835a17e] + JpegTurbo v0.1.6 [b14d175d] + JuliaVariables v0.2.4 [5ab0869b] + KernelDensity v0.6.9 [8ac3fa9e] + LRUCache v1.6.2 [b964fa9f] + LaTeXStrings v1.4.0 [23fbe1c1] + Latexify v0.16.8 [a5e1c1ea] + LatinHypercubeSampling v1.9.0 [8cdb02fc] + LazyModules v0.3.1 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.1.0 ⌅ [33e6dc65] + MKL v0.8.0 [d8e11817] + MLStyle v0.4.17 [da04e1cc] + MPI v0.20.22 [3da0fdf6] + MPIPreferences v0.1.11 [1914dd2f] + MacroTools v0.5.16 [ee78f7c6] + Makie v0.22.10 [20f20a25] + MakieCore v0.9.5 [dbb5928d] + MappedArrays v0.4.2 [0a4f8689] + MathTeXEngine v0.6.4 [739be429] + MbedTLS v1.1.9 [442fdcdd] + Measures v0.3.2 [128add7d] + MicroCollections v0.2.0 [e1d29d7a] + Missings v1.2.0 [e94cdb99] + MosaicViews v0.3.4 [77ba4419] + NaNMath v1.1.3 [71a1bf82] + NameResolution v0.1.5 [f09324ee] + Netpbm v1.1.1 [89bb3bae] + NuclearToolkit v0.4.5 [510215fc] + Observables v0.5.5 [6fe1bfb0] + OffsetArrays v1.17.0 [52e1d378] + OpenEXR v0.3.3 [4d8831e6] + OpenSSL v1.5.0 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.35 [f57f5aa1] + PNGFiles v0.4.4 [19eb6ba3] + Packing v0.5.1 [5432bcbf] + PaddedViews v0.5.12 [69de0a69] + Parsers v2.8.3 [eebad327] + PkgVersion v0.3.3 [ccf2f8ad] + PlotThemes v3.3.0 [995b91a9] + PlotUtils v1.4.3 ⌃ [91a5bcdd] + Plots v1.40.1 [647866c9] + PolygonOps v0.1.2 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [8162dcfd] + PrettyPrint v0.2.0 [27ebfcd6] + Primes v0.5.7 [92933f4c] + ProgressMeter v1.10.4 [43287f4e] + PtrArrays v1.3.0 [4b34888f] + QOI v1.0.1 [1fd47b50] + QuadGK v2.11.2 [b3c3ace0] + RangeArrays v0.3.2 [308eb6b3] + RationalRoots v0.2.1 [c84ed2f1] + Ratios v0.4.5 [3cdcf5f2] + RecipesBase v1.3.4 [01d81517] + RecipesPipeline v0.6.12 [189a3867] + Reexport v1.2.2 [05181044] + RelocatableFolders v1.0.1 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.8.0 [5eaf0fd0] + RoundingEmulator v0.2.1 [fdea26ae] + SIMD v3.7.1 [6c6a2e73] + Scratch v1.2.1 [efcf1570] + Setfield v1.1.2 [65257c39] + ShaderAbstractions v0.5.0 [992d4aef] + Showoff v1.0.3 [73760f76] + SignedDistanceFields v0.4.0 [777ac1f9] + SimpleBufferStream v1.2.0 [699a6c99] + SimpleTraits v0.9.4 [45858cf5] + Sixel v0.1.3 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.1 [171d559e] + SplittablesBase v0.1.15 [860ef19b] + StableRNGs v1.0.3 [cae243ae] + StackViews v0.1.2 [90137ffa] + StaticArrays v1.9.13 [1e83bf80] + StaticArraysCore v1.4.3 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.5 [4c63d2b9] + StatsFuns v1.5.0 [09ab397b] + StructArrays v0.7.1 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [62fd8b95] + TensorCore v0.1.1 [731e570b] + TiffImages v0.11.4 [a759f4b9] + TimerOutputs v0.5.29 [3bb67fe8] + TranscodingStreams v0.11.3 [28d57a85] + Transducers v0.4.84 [981d1d27] + TriplotBase v0.1.0 [5c2747f8] + URIs v1.5.2 [1cfade01] + UnicodeFun v0.4.1 [1986cc42] + Unitful v1.22.1 [45397f5d] + UnitfulLatexify v1.7.0 [41fe7b60] + Unzip v0.2.0 [e3aaa7dc] + WebP v0.1.3 [9f57e263] + WignerSymbols v2.0.0 [efce3f68] + WoodburyMatrices v1.0.0 ⌅ [68821587] + Arpack_jll v3.5.1+1 [6e34b625] + Bzip2_jll v1.0.9+0 [4e9b3aee] + CRlibm_jll v1.0.1+0 [83423d85] + Cairo_jll v1.18.5+0 [ee1fde0b] + Dbus_jll v1.16.2+0 [5ae413db] + EarCut_jll v2.2.4+0 [2702e6a9] + EpollShim_jll v0.0.20230411+1 [2e619515] + Expat_jll v2.6.5+0 ⌅ [b22a6f82] + FFMPEG_jll v6.1.2+0 [f5851436] + FFTW_jll v3.3.11+0 [a3f928ae] + Fontconfig_jll v2.16.0+0 [d7e528f0] + FreeType2_jll v2.13.4+0 [559328eb] + FriBidi_jll v1.0.17+0 [0656b61e] + GLFW_jll v3.4.0+2 [d2c73de3] + GR_jll v0.73.16+0 [78b55507] + Gettext_jll v0.21.0+0 [59f7168a] + Giflib_jll v5.2.3+0 [7746bdde] + Glib_jll v2.84.0+0 [3b182d85] + Graphite2_jll v1.3.15+0 [0234f1f7] + HDF5_jll v1.14.6+0 [2e76f6c2] + HarfBuzz_jll v8.5.1+0 [e33a78d0] + Hwloc_jll v2.12.1+0 [905a6f67] + Imath_jll v3.1.11+0 [1d5cc7b8] + IntelOpenMP_jll v2025.0.4+0 [aacddb02] + JpegTurbo_jll v3.1.1+0 [c1c5ebd0] + LAME_jll v3.100.2+0 [88015f11] + LERC_jll v4.0.1+0 [1d63c593] + LLVMOpenMP_jll v18.1.8+0 [dd4b983a] + LZO_jll v2.10.3+0 [e9f186c6] + Libffi_jll v3.4.7+0 [7e76a0d4] + Libglvnd_jll v1.7.1+1 [94ce4f54] + Libiconv_jll v1.18.0+0 [4b2f31a3] + Libmount_jll v2.41.0+0 [89763e89] + Libtiff_jll v4.7.1+0 [38a345b3] + Libuuid_jll v2.41.0+0 [856f044c] + MKL_jll v2025.0.1+1 [7cb0a576] + MPICH_jll v4.3.0+1 [f1f71cc9] + MPItrampoline_jll v5.5.3+0 [9237b28f] + MicrosoftMPI_jll v10.1.4+3 [e7412a2a] + Ogg_jll v1.3.5+1 [6cdc7f73] + OpenBLASConsistentFPCSR_jll v0.3.29+0 [18a262bb] + OpenEXR_jll v3.2.4+0 [fe0851c0] + OpenMPI_jll v5.0.7+2 [458c3c95] + OpenSSL_jll v3.5.0+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [91d4177d] + Opus_jll v1.3.3+0 [36c8627f] + Pango_jll v1.56.3+0 ⌅ [30392449] + Pixman_jll v0.44.2+0 [c0090381] + Qt6Base_jll v6.8.2+1 [629bc702] + Qt6Declarative_jll v6.8.2+1 [ce943373] + Qt6ShaderTools_jll v6.8.2+1 [e99dba38] + Qt6Wayland_jll v6.8.2+0 [f50d1b31] + Rmath_jll v0.5.1+0 [a44049a8] + Vulkan_Loader_jll v1.3.243+0 [a2964d1f] + Wayland_jll v1.23.1+0 [2381bf8a] + Wayland_protocols_jll v1.36.0+0 ⌅ [02c8fc9c] + XML2_jll v2.13.6+1 [ffd25f8a] + XZ_jll v5.8.1+0 [f67eecfb] + Xorg_libICE_jll v1.1.2+0 [c834827a] + Xorg_libSM_jll v1.2.6+0 [4f6342f7] + Xorg_libX11_jll v1.8.12+0 [0c0b7dd1] + Xorg_libXau_jll v1.0.13+0 [935fb764] + Xorg_libXcursor_jll v1.2.4+0 [a3789734] + Xorg_libXdmcp_jll v1.1.6+0 [1082639a] + Xorg_libXext_jll v1.3.7+0 [d091e8ba] + Xorg_libXfixes_jll v6.0.1+0 [a51aa0fd] + Xorg_libXi_jll v1.8.3+0 [d1454406] + Xorg_libXinerama_jll v1.1.6+0 [ec84b674] + Xorg_libXrandr_jll v1.5.5+0 [ea2f1a96] + Xorg_libXrender_jll v0.9.12+0 [c7cfdc94] + Xorg_libxcb_jll v1.17.1+0 [cc61e674] + Xorg_libxkbfile_jll v1.1.3+0 [e920d4aa] + Xorg_xcb_util_cursor_jll v0.1.4+0 [12413925] + Xorg_xcb_util_image_jll v0.4.0+1 [2def613f] + Xorg_xcb_util_jll v0.4.0+1 [975044d2] + Xorg_xcb_util_keysyms_jll v0.4.0+1 [0d47668e] + Xorg_xcb_util_renderutil_jll v0.3.9+1 [c22f9ab0] + Xorg_xcb_util_wm_jll v0.4.1+1 [35661453] + Xorg_xkbcomp_jll v1.4.7+0 [33bec58e] + Xorg_xkeyboard_config_jll v2.44.0+0 [c5fb5394] + Xorg_xtrans_jll v1.6.0+0 [3161d3a3] + Zstd_jll v1.5.7+1 [35ca27e7] + eudev_jll v3.2.9+0 [214eeab7] + fzf_jll v0.61.1+0 [1a1c6b14] + gperf_jll v3.3.0+0 [9a68df92] + isoband_jll v0.2.3+0 [477f73a3] + libaec_jll v1.1.3+0 [a4ae2306] + libaom_jll v3.11.0+0 [0ac62f75] + libass_jll v0.15.2+0 [1183f4f0] + libdecor_jll v0.2.2+0 [2db6ffa8] + libevdev_jll v1.11.0+0 [f638f0a6] + libfdk_aac_jll v2.0.3+0 [36db933b] + libinput_jll v1.18.0+0 [b53b4c65] + libpng_jll v1.6.48+0 [075b6546] + libsixel_jll v1.10.5+0 [f27f6e37] + libvorbis_jll v1.3.7+2 [c5f90fcd] + libwebp_jll v1.5.0+0 [009596ad] + mtdev_jll v1.1.6+0 [1317d2d5] + oneTBB_jll v2022.0.0+0 [1270edf5] + x264_jll v10164.0.1+0 ⌅ [dfaa095f] + x265_jll v3.6.0+0 [d8fb68d0] + xkbcommon_jll v1.8.1+0 [0dad84c5] + ArgTools v1.1.1 [56f22d72] + Artifacts [2a0f44e3] + Base64 [8bf52ea8] + CRC32c [ade2ca70] + Dates [8ba89e20] + Distributed [f43a241f] + Downloads v1.6.0 [7b1f6079] + FileWatching [9fa8497b] + Future [b77e0a4c] + InteractiveUtils [4af54fe1] + LazyArtifacts [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 [8f399da3] + Libdl [37e2e46d] + LinearAlgebra [56ddb016] + Logging [d6f4376e] + Markdown [a63ad114] + Mmap [ca575930] + NetworkOptions v1.2.0 [44cfe95a] + Pkg v1.10.0 [de0858da] + Printf [3fa0cd96] + REPL [9a3f8284] + Random [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization [1a1011a3] + SharedArrays [6462fe0b] + Sockets [2f01184e] + SparseArrays v1.10.0 [10745b16] + Statistics v1.10.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test [cf7118a7] + UUIDs [4ec0a83e] + Unicode [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] + LibCURL_jll v8.4.0+0 [e37daf67] + LibGit2_jll v1.6.4+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.2+1 [14a3606d] + MozillaCACerts_jll v2023.1.10 [4536629a] + OpenBLAS_jll v0.3.23+4 [05823500] + OpenLibm_jll v0.8.5+0 [efcefdf7] + PCRE2_jll v10.42.0+1 [bea87d4a] + SuiteSparse_jll v7.2.1+1 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.52.0+1 [3f19e933] + p7zip_jll v17.4.0+2 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m` Building FFMPEG → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/9143266ba77d3313a4cf61d8333a1970e8c5d8b6/build.log` Installation completed after 47.3s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 641.52s ################################################################################ # Testing # Testing NuclearToolkit Status `/tmp/jl_WaFrHQ/Project.toml` [861a8166] Combinatorics v1.0.3 [c27321d9] Glob v1.3.1 [b964fa9f] LaTeXStrings v1.4.0 [a5e1c1ea] LatinHypercubeSampling v1.9.0 [da04e1cc] MPI v0.20.22 [89bb3bae] NuclearToolkit v0.4.5 [276daf66] SpecialFunctions v2.5.1 [2913bbd2] StatsBase v0.34.5 [a759f4b9] TimerOutputs v0.5.29 [9f57e263] WignerSymbols v2.0.0 [37e2e46d] LinearAlgebra [de0858da] Printf [9a3f8284] Random [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_WaFrHQ/Manifest.toml` [621f4979] AbstractFFTs v1.5.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.42 [79e6a3ab] Adapt v4.3.0 [35492f91] AdaptivePredicates v1.2.0 [66dad0bd] AliasTables v1.1.3 [27a7e980] Animations v0.4.2 [dce04be8] ArgCheck v2.5.0 [7d9fca2a] Arpack v0.5.4 [2119f1ac] AssociatedLegendrePolynomials v1.0.1 [67c07d97] Automa v1.1.0 [13072b0f] 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Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... option in parameters/optional_parameters_srg_emn500n4lo_2n3n.jl will be used. --- chiEFTparameters used --- n_mesh = 50 pmax_fm = 5.0 emax = 2 Nnmax = 20 chi_order = 4 calc_NN = true calc_3N = true coulomb = true calc_EperA = false hw = 20.0 srg = true srg_lambda = 10.0 tbme_fmt = snt.bin fn_tbme = tbme_emn500n4lo_2n3n_srg10.0hw20emax2.snt.bin pottype = emn500n4lo LambdaSFR = 700.0 Lambda_cutoff = 500.0 n_reg = 3 target_nlj = Vector{Int64}[] v_chi_order = 0 n_mesh_P = 10 Pmax_fm = 3.0 kF = 1.35 BetaCM = 1.0 ----------------------------- size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB # of two-body states 78 # of sp states 6 # of channels 2bstate 31 #TBME = 890 E(2H): bare = -2.224576 srg = -2.224576 Diff.2.898e-12 option in parameters/optional_parameters_nnlosat.jl will be used. --- chiEFTparameters used --- n_mesh = 50 pmax_fm = 5.0 emax = 2 Nnmax = 20 chi_order = 2 calc_NN = true calc_3N = false coulomb = true calc_EperA = false hw = 20.0 srg = false srg_lambda = 10.0 tbme_fmt = snt.bin fn_tbme = tbme_nnlosat_barehw20emax2.snt.bin pottype = nnlosat LambdaSFR = 700.0 Lambda_cutoff = 450.0 n_reg = 3 target_nlj = Vector{Int64}[] v_chi_order = 0 n_mesh_P = 10 Pmax_fm = 3.0 kF = 1.35 BetaCM = 0.0 ----------------------------- size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB # of two-body states 78 # of sp states 6 # of channels 2bstate 31 #TBME = 890 E(2H): bare = -2.224574 option in parameters/optional_parameters.jl will be used. --- chiEFTparameters used --- n_mesh = 50 pmax_fm = 5.0 emax = 2 Nnmax = 20 chi_order = 3 calc_NN = true calc_3N = false coulomb = true calc_EperA = false hw = 20.0 srg = false srg_lambda = 10.0 tbme_fmt = snt.bin fn_tbme = tbme_em500n3lo_barehw20emax2.snt.bin pottype = em500n3lo LambdaSFR = 0.0 Lambda_cutoff = 500.0 n_reg = 3 target_nlj = Vector{Int64}[] v_chi_order = 0 n_mesh_P = 10 Pmax_fm = 3.0 kF = 1.35 BetaCM = 0.0 ----------------------------- size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB # of two-body states 78 # of sp states 6 # of channels 2bstate 31 #TBME = 890 E(2H): bare = -2.224578 option in parameters/optional_parameters_snt.jl will be used. --- chiEFTparameters used --- n_mesh = 50 pmax_fm = 5.0 emax = 2 Nnmax = 20 chi_order = 3 calc_NN = true calc_3N = false coulomb = true calc_EperA = false hw = 20.0 srg = false srg_lambda = 10.0 tbme_fmt = snt fn_tbme = tbme_em500n3lo_barehw20emax2.snt pottype = em500n3lo LambdaSFR = 0.0 Lambda_cutoff = 500.0 n_reg = 3 target_nlj = Vector{Int64}[] v_chi_order = 0 n_mesh_P = 10 Pmax_fm = 3.0 kF = 1.35 BetaCM = 0.0 ----------------------------- size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB # of two-body states 78 # of sp states 6 # of channels 2bstate 31 #TBME = 890 E(2H): bare = -2.224578 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.46 KB dictHOB 0.46 KB target: He4 Ref. => Z=2 N=2 E: 1.764636E1b: 38.207627E2b: -36.442992 E3b 0.000000 E: 1.536426E1b: 36.090354E2b: -34.553928 E3b 0.000000 E: 1.500375E1b: 35.309205E2b: -33.808830 E3b 0.000000 E: 1.494386E1b: 35.000751E2b: -33.506366 E3b 0.000000 E: 1.493371E1b: 34.875524E2b: -33.382153 E3b 0.000000 E: 1.493198E1b: 34.824087E2b: -33.330889 E3b 0.000000 E: 1.493169E1b: 34.802858E2b: -33.309689 E3b 0.000000 E: 1.493164E1b: 34.794079E2b: -33.300915 E3b 0.000000 E: 1.493163E1b: 34.790445E2b: -33.297282 E3b 0.000000 E: 1.493163E1b: 34.788941E2b: -33.295778 E3b 0.000000 E: 1.493163E1b: 34.788318E2b: -33.295155 E3b 0.000000 E: 1.493163E1b: 34.788060E2b: -33.294897 E3b 0.000000 E: 1.493163E1b: 34.787953E2b: -33.294790 E3b 0.000000 E: 1.493163E1b: 34.787909E2b: -33.294746 E3b 0.000000 E: 1.493163E1b: 34.787890E2b: -33.294728 E3b 0.000000 E: 1.493163E1b: 34.787883E2b: -33.294720 E3b 0.000000 E: 1.493163E1b: 34.787879E2b: -33.294717 E3b 0.000000 E: 1.493163E1b: 34.787878E2b: -33.294716 E3b 0.000000 E: 1.493163E1b: 34.787878E2b: -33.294715 E3b 0.000000 E: 1.493163 = E1b 34.78788 + E2b -33.29471 ( -5.238 -21.994 -6.063), + E3b 0.00000 EMP2 -5.80479 1b -0.00000 pp -0.00516 pn -5.79209 nn -0.00753 EMP3 0.39510 pp 0.385 hh -0.583 ph 0.593 E_HF 1.49316 E_MBPT(3) = -3.9165 Eexp: -28.296 Eref [1.493, -5.805, 0.395] Es1 [1.4931626671566534, -5.804788515535714, 0.39509684274756846] Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.46 KB dictHOB 0.46 KB target: He4 Ref. => Z=2 N=2 E: 1.493163 = E1b 34.78788 + E2b -33.29471 ( -5.238 -21.994 -6.063), + E3b 0.00000 EMP2 -5.80479 1b -0.00000 pp -0.00516 pn -5.79209 nn -0.00753 EMP3 0.39510 pp 0.385 hh -0.583 ph 0.593 E_HF 1.49316 E_MBPT(3) = -3.9165 Eexp: -28.296 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.46 KB dictHOB 0.46 KB target: He4 Ref. => Z=2 N=2 E: 1.493163 = E1b 34.78788 + E2b -33.29471 ( -5.238 -21.994 -6.063), + E3b 0.00000 EMP2 -5.80479 1b -0.00000 pp -0.00516 pn -5.79209 nn -0.00753 EMP3 0.39510 pp 0.385 hh -0.583 ph 0.593 E_HF 1.49316 E_MBPT(3) = -3.9165 Eexp: -28.296 parameters/optional_parameters.jl is used for IMSRG parameters in parameters/optional_parameters.jl will be used. def-by-run d6j_lj done! 240 step: s E0 ||Omega_1|| ||Omega_2|| ||Eta_1|| ||Eta_2|| Ncomm. nwritten 0 0.000 1.49316267 0.000000e+00 0.000000e+00 5.803186e-17 8.372401e-01 0 0 1 0.500 -2.82961651 2.901593e-17 4.186200e-01 2.013411e-02 3.594196e-01 9 0 2 1.000 -3.72721100 1.006706e-02 1.797098e-01 2.183745e-02 1.792320e-01 17 1 3 1.500 -3.95864402 2.100718e-02 2.689260e-01 1.788977e-02 9.329672e-02 26 1 4 2.000 -4.02314912 8.944886e-03 4.664836e-02 1.290585e-02 5.005505e-02 32 2 5 2.500 -4.04225788 1.539772e-02 7.159439e-02 8.598961e-03 2.771940e-02 39 2 6 3.000 -4.04829228 1.969710e-02 8.526572e-02 5.366889e-03 1.599703e-02 46 2 7 3.500 -4.05035496 2.238048e-02 9.296270e-02 3.112640e-03 9.765797e-03 53 2 8 4.000 -4.05113987 2.393679e-02 9.743574e-02 1.609610e-03 6.409034e-03 60 2 9 4.500 -4.05148532 2.474158e-02 1.001368e-01 6.399675e-04 4.561681e-03 67 2 10 5.000 -4.05166657 2.506129e-02 1.018447e-01 4.908947e-05 3.503471e-03 74 2 11 5.500 -4.05177946 2.507686e-02 1.029838e-01 3.409231e-04 2.857504e-03 81 2 12 6.000 -4.05185969 2.490794e-02 1.037891e-01 5.536528e-04 2.430735e-03 88 2 13 6.500 -4.05192170 2.463225e-02 1.043925e-01 6.672807e-04 2.125465e-03 95 2 14 7.000 -4.05197192 2.429965e-02 1.048693e-01 7.179244e-04 1.891641e-03 102 2 15 7.500 -4.05201362 2.394168e-02 1.052636e-01 7.292480e-04 1.702728e-03 109 2 16 8.000 -4.05204869 2.357802e-02 1.056012e-01 7.165548e-04 1.543996e-03 116 2 17 8.500 -4.05207838 2.322067e-02 1.058978e-01 6.896865e-04 1.406854e-03 123 2 18 9.000 -4.05210360 2.287672e-02 1.061632e-01 6.549435e-04 1.286038e-03 130 2 19 9.500 -4.05212508 2.255010e-02 1.064037e-01 6.163354e-04 1.178161e-03 137 2 20 10.000 -4.05214338 2.224276e-02 1.066234e-01 5.763905e-04 1.080938e-03 144 2 21 10.500 -4.05215898 2.195535e-02 1.068252e-01 5.366795e-04 9.927519e-04 151 2 22 11.000 -4.05217230 2.168776e-02 1.070111e-01 4.981533e-04 9.124066e-04 158 2 23 11.500 -4.05218367 2.143939e-02 1.071828e-01 4.613628e-04 8.389775e-04 165 2 24 12.000 -4.05219338 2.120938e-02 1.073416e-01 4.266006e-04 7.717237e-04 172 2 25 12.500 -4.05220168 2.099672e-02 1.074885e-01 3.939945e-04 7.100320e-04 179 2 26 13.000 -4.05220877 2.080031e-02 1.076244e-01 3.635674e-04 6.533817e-04 186 2 27 13.500 -4.05221484 2.061909e-02 1.077503e-01 3.352776e-04 6.013214e-04 193 2 28 14.000 -4.05222004 2.045198e-02 1.078667e-01 3.090442e-04 5.534533e-04 200 2 29 14.500 -4.05222449 2.029795e-02 1.079744e-01 2.847643e-04 5.094233e-04 207 2 30 15.000 -4.05222831 2.015602e-02 1.080741e-01 2.623238e-04 4.689128e-04 214 2 31 15.500 -4.05223158 2.002529e-02 1.081662e-01 2.416048e-04 4.316334e-04 221 2 32 16.000 -4.05223439 1.990489e-02 1.082513e-01 2.224897e-04 3.973230e-04 228 2 33 16.500 -4.05223681 1.979402e-02 1.083300e-01 2.048644e-04 3.657422e-04 235 2 34 17.000 -4.05223889 1.969193e-02 1.084028e-01 1.886195e-04 3.366723e-04 242 2 35 17.500 -4.05224068 1.959794e-02 1.084699e-01 1.736517e-04 3.099125e-04 249 2 36 18.000 -4.05224222 1.951142e-02 1.085319e-01 1.598638e-04 2.852787e-04 256 2 37 18.500 -4.05224355 1.943176e-02 1.085891e-01 1.471652e-04 2.626017e-04 263 2 38 19.000 -4.05224470 1.935844e-02 1.086420e-01 1.354712e-04 2.417260e-04 270 2 39 19.500 -4.05224570 1.929094e-02 1.086907e-01 1.247036e-04 2.225085e-04 277 2 40 20.000 -4.05224656 1.922881e-02 1.087357e-01 1.147897e-04 2.048176e-04 284 2 41 20.500 -4.05224731 1.917163e-02 1.087771e-01 1.056624e-04 1.885320e-04 291 2 42 21.000 -4.05224796 1.911898e-02 1.088154e-01 9.725969e-05 1.735403e-04 298 2 43 21.500 -4.05224853 1.907053e-02 1.088506e-01 8.952434e-05 1.597398e-04 305 2 44 22.000 -4.05224902 1.902593e-02 1.088831e-01 8.240355e-05 1.470359e-04 312 2 45 22.500 -4.05224945 1.898488e-02 1.089131e-01 7.584863e-05 1.353416e-04 319 2 46 23.000 -4.05224982 1.894710e-02 1.089407e-01 6.981475e-05 1.245768e-04 326 2 47 23.500 -4.05225015 1.891232e-02 1.089662e-01 6.426055e-05 1.146676e-04 333 2 48 24.000 -4.05225044 1.888031e-02 1.089896e-01 5.914799e-05 1.055462e-04 340 2 49 24.500 -4.05225069 1.885084e-02 1.090113e-01 5.444198e-05 9.715003e-05 347 2 50 25.000 -4.05225092 1.882372e-02 1.090312e-01 5.011023e-05 8.942140e-05 354 2 51 25.500 -4.05225111 1.879876e-02 1.090495e-01 4.612302e-05 8.230732e-05 361 2 52 26.000 -4.05225129 1.877578e-02 1.090664e-01 4.245296e-05 7.575896e-05 368 2 53 26.500 -4.05225144 1.875464e-02 1.090820e-01 3.907484e-05 6.973139e-05 375 2 54 27.000 -4.05225157 1.873517e-02 1.090963e-01 3.596546e-05 6.418320e-05 382 2 55 27.500 -4.05225169 1.871726e-02 1.091095e-01 3.310344e-05 5.907631e-05 389 2 56 28.000 -4.05225180 1.870077e-02 1.091217e-01 3.046913e-05 5.437563e-05 396 2 57 28.500 -4.05225190 1.868559e-02 1.091329e-01 2.804441e-05 5.004887e-05 403 2 58 29.000 -4.05225198 1.867162e-02 1.091432e-01 2.581261e-05 4.606631e-05 410 2 59 29.500 -4.05225206 1.865877e-02 1.091527e-01 2.375839e-05 4.240058e-05 417 2 60 30.000 -4.05225213 1.864693e-02 1.091614e-01 2.186762e-05 3.902648e-05 424 2 61 30.500 -4.05225219 1.863604e-02 1.091695e-01 2.012731e-05 3.592082e-05 431 2 62 31.000 -4.05225224 1.862601e-02 1.091769e-01 1.852548e-05 3.306226e-05 438 2 63 31.500 -4.05225229 1.861679e-02 1.091837e-01 1.705112e-05 3.043114e-05 445 2 64 32.000 -4.05225233 1.860829e-02 1.091900e-01 1.569408e-05 2.800938e-05 452 2 65 32.500 -4.05225237 1.860048e-02 1.091958e-01 1.444503e-05 2.578031e-05 459 2 66 33.000 -4.05225241 1.859328e-02 1.092011e-01 1.329538e-05 2.372862e-05 466 2 67 33.500 -4.05225244 1.858666e-02 1.092060e-01 1.223723e-05 2.184018e-05 473 2 68 34.000 -4.05225247 1.858056e-02 1.092105e-01 1.126328e-05 2.010202e-05 480 2 69 34.500 -4.05225250 1.857495e-02 1.092147e-01 1.036684e-05 1.850217e-05 487 2 70 35.000 -4.05225252 1.856979e-02 1.092185e-01 9.541748e-06 1.702964e-05 494 2 71 35.500 -4.05225254 1.856504e-02 1.092220e-01 8.782319e-06 1.567429e-05 501 2 72 36.000 -4.05225256 1.856066e-02 1.092253e-01 8.083329e-06 1.442681e-05 508 2 73 36.500 -4.05225258 1.855664e-02 1.092282e-01 7.439970e-06 1.327860e-05 515 2 74 37.000 -4.05225260 1.855293e-02 1.092310e-01 6.847814e-06 1.222176e-05 522 2 75 37.500 -4.05225261 1.854952e-02 1.092335e-01 6.302786e-06 1.124904e-05 529 2 76 38.000 -4.05225263 1.854638e-02 1.092358e-01 5.801136e-06 1.035373e-05 536 2 77 38.500 -4.05225264 1.854349e-02 1.092380e-01 5.339412e-06 9.529668e-06 543 2 78 39.000 -4.05225265 1.854083e-02 1.092400e-01 4.914436e-06 8.771194e-06 550 2 79 39.500 -4.05225266 1.853839e-02 1.092418e-01 4.523284e-06 8.073085e-06 557 2 80 40.000 -4.05225267 1.853613e-02 1.092434e-01 4.163264e-06 7.430536e-06 564 2 81 40.500 -4.05225268 1.853406e-02 1.092450e-01 3.831898e-06 6.839127e-06 571 2 82 41.000 -4.05225269 1.853215e-02 1.092464e-01 3.526906e-06 6.294788e-06 578 2 83 41.500 -4.05225269 1.853039e-02 1.092477e-01 3.246188e-06 5.793772e-06 585 2 84 42.000 -4.05225270 1.852878e-02 1.092489e-01 2.987813e-06 5.332632e-06 592 2 85 42.500 -4.05225271 1.852729e-02 1.092500e-01 2.750003e-06 4.908194e-06 599 2 86 43.000 -4.05225271 1.852592e-02 1.092510e-01 2.531121e-06 4.517537e-06 606 2 87 43.500 -4.05225272 1.852466e-02 1.092520e-01 2.329660e-06 4.157973e-06 613 2 88 44.000 -4.05225272 1.852350e-02 1.092528e-01 2.144233e-06 3.827027e-06 620 2 89 44.500 -4.05225273 1.852243e-02 1.092536e-01 1.973565e-06 3.522422e-06 627 2 90 45.000 -4.05225273 1.852145e-02 1.092543e-01 1.816482e-06 3.242060e-06 634 2 91 45.500 -4.05225273 1.852054e-02 1.092550e-01 1.671901e-06 2.984013e-06 641 2 92 46.000 -4.05225274 1.851971e-02 1.092556e-01 1.538827e-06 2.746505e-06 648 2 93 46.500 -4.05225274 1.851894e-02 1.092562e-01 1.416346e-06 2.527900e-06 655 2 94 47.000 -4.05225274 1.851824e-02 1.092567e-01 1.303613e-06 2.326695e-06 662 2 95 47.500 -4.05225274 1.851759e-02 1.092572e-01 1.199853e-06 2.141504e-06 669 2 96 48.000 -4.05225275 1.851699e-02 1.092576e-01 1.104351e-06 1.971054e-06 676 2 97 48.500 -4.05225275 1.851644e-02 1.092581e-01 1.016451e-06 1.814169e-06 683 2 98 49.000 -4.05225275 1.851593e-02 1.092584e-01 9.355474e-07 1.669772e-06 690 2 99 49.500 -4.05225275 1.851547e-02 1.092588e-01 8.610830e-07 1.536868e-06 697 2 100 50.000 -4.05225275 1.851504e-02 1.092591e-01 7.925456e-07 1.414542e-06 704 2 101 50.500 -4.05225276 1.851464e-02 1.092594e-01 7.294633e-07 1.301953e-06 711 2 102 51.000 -4.05225276 1.851428e-02 1.092597e-01 6.714021e-07 1.198325e-06 718 2 103 51.500 -4.05225276 1.851395e-02 1.092599e-01 6.179621e-07 1.102945e-06 725 2 104 52.000 -4.05225276 1.851364e-02 1.092601e-01 5.687757e-07 1.015157e-06 732 2 105 52.500 -4.05225276 1.851336e-02 1.092603e-01 5.235042e-07 9.343558e-07 739 2 106 53.000 -4.05225276 1.851310e-02 1.092605e-01 4.818361e-07 8.599862e-07 746 2 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.46 KB dictHOB 0.46 KB target: He4 Ref. => Z=2 N=2 E: 1.493163 = E1b 34.78788 + E2b -33.29471 ( -5.238 -21.994 -6.063), + E3b 0.00000 EMP2 -5.80479 1b -0.00000 pp -0.00516 pn -5.79209 nn -0.00753 EMP3 0.39510 pp 0.385 hh -0.583 ph 0.593 E_HF 1.49316 E_MBPT(3) = -3.9165 Eexp: -28.296 parameters/optional_parameters.jl is used for IMSRG parameters in parameters/optional_parameters.jl will be used. def-by-run d6j_lj done! 240 step: s E0 ||Omega_1|| ||Omega_2|| ||Eta_1|| ||Eta_2|| Ncomm. nwritten 0 0.000 1.49316267 0.000000e+00 0.000000e+00 5.803186e-17 8.372401e-01 0 0 1 0.500 -2.82961651 2.901593e-17 4.186200e-01 2.013411e-02 3.594196e-01 9 0 2 1.000 -3.72721100 1.006706e-02 1.797098e-01 2.183745e-02 1.792320e-01 17 1 3 1.500 -3.95864402 2.100718e-02 2.689260e-01 1.788977e-02 9.329672e-02 26 1 4 2.000 -4.02314912 8.944886e-03 4.664836e-02 1.290585e-02 5.005505e-02 32 2 5 2.500 -4.04225788 1.539772e-02 7.159439e-02 8.598961e-03 2.771940e-02 39 2 6 3.000 -4.04829228 1.969710e-02 8.526572e-02 5.366889e-03 1.599703e-02 46 2 7 3.500 -4.05035496 2.238048e-02 9.296270e-02 3.112640e-03 9.765797e-03 53 2 8 4.000 -4.05113987 2.393679e-02 9.743574e-02 1.609610e-03 6.409034e-03 60 2 9 4.500 -4.05148532 2.474158e-02 1.001368e-01 6.399675e-04 4.561681e-03 67 2 10 5.000 -4.05166657 2.506129e-02 1.018447e-01 4.908947e-05 3.503471e-03 74 2 11 5.500 -4.05177946 2.507686e-02 1.029838e-01 3.409231e-04 2.857504e-03 81 2 12 6.000 -4.05185969 2.490794e-02 1.037891e-01 5.536528e-04 2.430735e-03 88 2 13 6.500 -4.05192170 2.463225e-02 1.043925e-01 6.672807e-04 2.125465e-03 95 2 14 7.000 -4.05197192 2.429965e-02 1.048693e-01 7.179244e-04 1.891641e-03 102 2 15 7.500 -4.05201362 2.394168e-02 1.052636e-01 7.292480e-04 1.702728e-03 109 2 16 8.000 -4.05204869 2.357802e-02 1.056012e-01 7.165548e-04 1.543996e-03 116 2 17 8.500 -4.05207838 2.322067e-02 1.058978e-01 6.896865e-04 1.406854e-03 123 2 18 9.000 -4.05210360 2.287672e-02 1.061632e-01 6.549435e-04 1.286038e-03 130 2 19 9.500 -4.05212508 2.255010e-02 1.064037e-01 6.163354e-04 1.178161e-03 137 2 20 10.000 -4.05214338 2.224276e-02 1.066234e-01 5.763905e-04 1.080938e-03 144 2 21 10.500 -4.05215898 2.195535e-02 1.068252e-01 5.366795e-04 9.927519e-04 151 2 22 11.000 -4.05217230 2.168776e-02 1.070111e-01 4.981533e-04 9.124066e-04 158 2 23 11.500 -4.05218367 2.143939e-02 1.071828e-01 4.613628e-04 8.389775e-04 165 2 24 12.000 -4.05219338 2.120938e-02 1.073416e-01 4.266006e-04 7.717237e-04 172 2 25 12.500 -4.05220168 2.099672e-02 1.074885e-01 3.939945e-04 7.100320e-04 179 2 26 13.000 -4.05220877 2.080031e-02 1.076244e-01 3.635674e-04 6.533817e-04 186 2 27 13.500 -4.05221484 2.061909e-02 1.077503e-01 3.352776e-04 6.013214e-04 193 2 28 14.000 -4.05222004 2.045198e-02 1.078667e-01 3.090442e-04 5.534533e-04 200 2 29 14.500 -4.05222449 2.029795e-02 1.079744e-01 2.847643e-04 5.094233e-04 207 2 30 15.000 -4.05222831 2.015602e-02 1.080741e-01 2.623238e-04 4.689128e-04 214 2 31 15.500 -4.05223158 2.002529e-02 1.081662e-01 2.416048e-04 4.316334e-04 221 2 32 16.000 -4.05223439 1.990489e-02 1.082513e-01 2.224897e-04 3.973230e-04 228 2 33 16.500 -4.05223681 1.979402e-02 1.083300e-01 2.048644e-04 3.657422e-04 235 2 34 17.000 -4.05223889 1.969193e-02 1.084028e-01 1.886195e-04 3.366723e-04 242 2 35 17.500 -4.05224068 1.959794e-02 1.084699e-01 1.736517e-04 3.099125e-04 249 2 36 18.000 -4.05224222 1.951142e-02 1.085319e-01 1.598638e-04 2.852787e-04 256 2 37 18.500 -4.05224355 1.943176e-02 1.085891e-01 1.471652e-04 2.626017e-04 263 2 38 19.000 -4.05224470 1.935844e-02 1.086420e-01 1.354712e-04 2.417260e-04 270 2 39 19.500 -4.05224570 1.929094e-02 1.086907e-01 1.247036e-04 2.225085e-04 277 2 40 20.000 -4.05224656 1.922881e-02 1.087357e-01 1.147897e-04 2.048176e-04 284 2 41 20.500 -4.05224731 1.917163e-02 1.087771e-01 1.056624e-04 1.885320e-04 291 2 42 21.000 -4.05224796 1.911898e-02 1.088154e-01 9.725969e-05 1.735403e-04 298 2 43 21.500 -4.05224853 1.907053e-02 1.088506e-01 8.952434e-05 1.597398e-04 305 2 44 22.000 -4.05224902 1.902593e-02 1.088831e-01 8.240355e-05 1.470359e-04 312 2 45 22.500 -4.05224945 1.898488e-02 1.089131e-01 7.584863e-05 1.353416e-04 319 2 46 23.000 -4.05224982 1.894710e-02 1.089407e-01 6.981475e-05 1.245768e-04 326 2 47 23.500 -4.05225015 1.891232e-02 1.089662e-01 6.426055e-05 1.146676e-04 333 2 48 24.000 -4.05225044 1.888031e-02 1.089896e-01 5.914799e-05 1.055462e-04 340 2 49 24.500 -4.05225069 1.885084e-02 1.090113e-01 5.444198e-05 9.715003e-05 347 2 50 25.000 -4.05225092 1.882372e-02 1.090312e-01 5.011023e-05 8.942140e-05 354 2 51 25.500 -4.05225111 1.879876e-02 1.090495e-01 4.612302e-05 8.230732e-05 361 2 52 26.000 -4.05225129 1.877578e-02 1.090664e-01 4.245296e-05 7.575896e-05 368 2 53 26.500 -4.05225144 1.875464e-02 1.090820e-01 3.907484e-05 6.973139e-05 375 2 54 27.000 -4.05225157 1.873517e-02 1.090963e-01 3.596546e-05 6.418320e-05 382 2 55 27.500 -4.05225169 1.871726e-02 1.091095e-01 3.310344e-05 5.907631e-05 389 2 56 28.000 -4.05225180 1.870077e-02 1.091217e-01 3.046913e-05 5.437563e-05 396 2 57 28.500 -4.05225190 1.868559e-02 1.091329e-01 2.804441e-05 5.004887e-05 403 2 58 29.000 -4.05225198 1.867162e-02 1.091432e-01 2.581261e-05 4.606631e-05 410 2 59 29.500 -4.05225206 1.865877e-02 1.091527e-01 2.375839e-05 4.240058e-05 417 2 60 30.000 -4.05225213 1.864693e-02 1.091614e-01 2.186762e-05 3.902648e-05 424 2 61 30.500 -4.05225219 1.863604e-02 1.091695e-01 2.012731e-05 3.592082e-05 431 2 62 31.000 -4.05225224 1.862601e-02 1.091769e-01 1.852548e-05 3.306226e-05 438 2 63 31.500 -4.05225229 1.861679e-02 1.091837e-01 1.705112e-05 3.043114e-05 445 2 64 32.000 -4.05225233 1.860829e-02 1.091900e-01 1.569408e-05 2.800938e-05 452 2 65 32.500 -4.05225237 1.860048e-02 1.091958e-01 1.444503e-05 2.578031e-05 459 2 66 33.000 -4.05225241 1.859328e-02 1.092011e-01 1.329538e-05 2.372862e-05 466 2 67 33.500 -4.05225244 1.858666e-02 1.092060e-01 1.223723e-05 2.184018e-05 473 2 68 34.000 -4.05225247 1.858056e-02 1.092105e-01 1.126328e-05 2.010202e-05 480 2 69 34.500 -4.05225250 1.857495e-02 1.092147e-01 1.036684e-05 1.850217e-05 487 2 70 35.000 -4.05225252 1.856979e-02 1.092185e-01 9.541748e-06 1.702964e-05 494 2 71 35.500 -4.05225254 1.856504e-02 1.092220e-01 8.782319e-06 1.567429e-05 501 2 72 36.000 -4.05225256 1.856066e-02 1.092253e-01 8.083329e-06 1.442681e-05 508 2 73 36.500 -4.05225258 1.855664e-02 1.092282e-01 7.439970e-06 1.327860e-05 515 2 74 37.000 -4.05225260 1.855293e-02 1.092310e-01 6.847814e-06 1.222176e-05 522 2 75 37.500 -4.05225261 1.854952e-02 1.092335e-01 6.302786e-06 1.124904e-05 529 2 76 38.000 -4.05225263 1.854638e-02 1.092358e-01 5.801136e-06 1.035373e-05 536 2 77 38.500 -4.05225264 1.854349e-02 1.092380e-01 5.339412e-06 9.529668e-06 543 2 78 39.000 -4.05225265 1.854083e-02 1.092400e-01 4.914436e-06 8.771194e-06 550 2 79 39.500 -4.05225266 1.853839e-02 1.092418e-01 4.523284e-06 8.073085e-06 557 2 80 40.000 -4.05225267 1.853613e-02 1.092434e-01 4.163264e-06 7.430536e-06 564 2 81 40.500 -4.05225268 1.853406e-02 1.092450e-01 3.831898e-06 6.839127e-06 571 2 82 41.000 -4.05225269 1.853215e-02 1.092464e-01 3.526906e-06 6.294788e-06 578 2 83 41.500 -4.05225269 1.853039e-02 1.092477e-01 3.246188e-06 5.793772e-06 585 2 84 42.000 -4.05225270 1.852878e-02 1.092489e-01 2.987813e-06 5.332632e-06 592 2 85 42.500 -4.05225271 1.852729e-02 1.092500e-01 2.750003e-06 4.908194e-06 599 2 86 43.000 -4.05225271 1.852592e-02 1.092510e-01 2.531121e-06 4.517537e-06 606 2 87 43.500 -4.05225272 1.852466e-02 1.092520e-01 2.329660e-06 4.157973e-06 613 2 88 44.000 -4.05225272 1.852350e-02 1.092528e-01 2.144233e-06 3.827027e-06 620 2 89 44.500 -4.05225273 1.852243e-02 1.092536e-01 1.973565e-06 3.522422e-06 627 2 90 45.000 -4.05225273 1.852145e-02 1.092543e-01 1.816482e-06 3.242060e-06 634 2 91 45.500 -4.05225273 1.852054e-02 1.092550e-01 1.671901e-06 2.984013e-06 641 2 92 46.000 -4.05225274 1.851971e-02 1.092556e-01 1.538827e-06 2.746505e-06 648 2 93 46.500 -4.05225274 1.851894e-02 1.092562e-01 1.416346e-06 2.527900e-06 655 2 94 47.000 -4.05225274 1.851824e-02 1.092567e-01 1.303613e-06 2.326695e-06 662 2 95 47.500 -4.05225274 1.851759e-02 1.092572e-01 1.199853e-06 2.141504e-06 669 2 96 48.000 -4.05225275 1.851699e-02 1.092576e-01 1.104351e-06 1.971054e-06 676 2 97 48.500 -4.05225275 1.851644e-02 1.092581e-01 1.016451e-06 1.814169e-06 683 2 98 49.000 -4.05225275 1.851593e-02 1.092584e-01 9.355474e-07 1.669772e-06 690 2 99 49.500 -4.05225275 1.851547e-02 1.092588e-01 8.610830e-07 1.536868e-06 697 2 100 50.000 -4.05225275 1.851504e-02 1.092591e-01 7.925456e-07 1.414542e-06 704 2 101 50.500 -4.05225276 1.851464e-02 1.092594e-01 7.294633e-07 1.301953e-06 711 2 102 51.000 -4.05225276 1.851428e-02 1.092597e-01 6.714021e-07 1.198325e-06 718 2 103 51.500 -4.05225276 1.851395e-02 1.092599e-01 6.179621e-07 1.102945e-06 725 2 104 52.000 -4.05225276 1.851364e-02 1.092601e-01 5.687757e-07 1.015157e-06 732 2 105 52.500 -4.05225276 1.851336e-02 1.092603e-01 5.235042e-07 9.343558e-07 739 2 106 53.000 -4.05225276 1.851310e-02 1.092605e-01 4.818361e-07 8.599862e-07 746 2 Starting VS-IMSRG flow step: s E0 ||Omega_1|| ||Omega_2|| ||Eta_1|| ||Eta_2|| Ncomm. nwritten 0 53.000 -4.05225276 0.000000e+00 0.000000e+00 4.818361e-07 7.308335e+00 746 3 1 53.500 -4.05225276 2.409180e-07 3.654168e+00 4.392551e-07 3.570980e+00 758 3 2 54.000 -4.05225276 2.196275e-07 1.785490e+00 4.232126e-07 2.370222e+00 767 4 3 54.500 -4.05225276 2.116063e-07 1.185111e+00 4.068636e-07 1.685689e+00 775 5 4 55.000 -4.05225276 2.034318e-07 8.428447e-01 3.880022e-07 1.243078e+00 783 6 5 55.500 -4.05225276 1.940011e-07 6.215389e-01 3.675953e-07 9.428936e-01 790 7 6 56.000 -4.05225276 1.837976e-07 4.714468e-01 3.466777e-07 7.324383e-01 797 8 7 56.500 -4.05225276 1.733389e-07 3.662192e-01 3.259318e-07 5.800653e-01 804 9 8 57.000 -4.05225276 1.629659e-07 2.900326e-01 3.057463e-07 4.662611e-01 811 10 9 57.500 -4.05225276 1.528731e-07 2.331306e-01 2.863257e-07 3.788951e-01 817 11 10 58.000 -4.05225276 2.960360e-07 4.224996e-01 2.677842e-07 3.103030e-01 824 11 11 58.500 -4.05225276 1.338921e-07 1.551515e-01 2.501328e-07 2.555294e-01 830 12 12 59.000 -4.05225276 2.589585e-07 2.828977e-01 2.334096e-07 2.112329e-01 837 12 13 59.500 -4.05225276 1.167048e-07 1.056164e-01 2.175971e-07 1.750848e-01 843 13 14 60.000 -4.05225276 2.255034e-07 1.931545e-01 2.026878e-07 1.453957e-01 849 13 15 60.500 -4.05225276 3.268473e-07 2.658439e-01 1.886629e-07 1.209004e-01 856 13 16 61.000 -4.05225276 9.433146e-08 6.045020e-02 1.754860e-07 1.006265e-01 862 14 17 61.500 -4.05225276 1.820744e-07 1.107628e-01 1.631294e-07 8.380879e-02 868 14 18 62.000 -4.05225276 2.636391e-07 1.526659e-01 1.515630e-07 6.983578e-02 874 14 19 62.500 -4.05225276 3.394206e-07 1.875820e-01 1.407541e-07 5.821308e-02 880 14 20 63.000 -4.05225276 4.097976e-07 2.166863e-01 1.306680e-07 4.853751e-02 886 14 21 63.500 -4.05225276 4.751316e-07 2.409526e-01 1.212685e-07 4.047815e-02 893 14 22 64.000 -4.05225276 5.357659e-07 2.611891e-01 1.125185e-07 3.376217e-02 900 14 23 64.500 -4.05225276 5.625926e-08 1.688109e-02 1.043683e-07 2.816408e-02 905 15 24 65.000 -4.05225276 1.084434e-07 3.096309e-02 9.677893e-08 2.349669e-02 910 15 25 65.500 -4.05225276 1.568329e-07 4.271136e-02 8.971966e-08 1.960446e-02 915 15 26 66.000 -4.05225276 2.016927e-07 5.251346e-02 8.315911e-08 1.635815e-02 921 15 27 66.500 -4.05225276 2.432722e-07 6.069236e-02 7.706633e-08 1.365022e-02 927 15 28 67.000 -4.05225276 2.818054e-07 6.751725e-02 7.141120e-08 1.139116e-02 933 15 29 67.500 -4.05225276 3.175110e-07 7.321257e-02 6.616472e-08 9.506417e-03 939 15 30 68.000 -4.05225276 3.505934e-07 7.796549e-02 6.129922e-08 7.933845e-03 945 15 31 68.500 -4.05225276 3.812430e-07 8.193210e-02 5.678840e-08 6.621662e-03 951 15 32 69.000 -4.05225276 4.096372e-07 8.524260e-02 5.260744e-08 5.526693e-03 957 15 33 69.500 -4.05225276 4.359409e-07 8.800562e-02 4.873296e-08 4.612936e-03 963 15 34 70.000 -4.05225276 4.603074e-07 9.031175e-02 4.514305e-08 3.850369e-03 969 15 35 70.500 -4.05225276 4.828789e-07 9.223660e-02 4.181719e-08 3.213949e-03 975 15 36 71.000 -4.05225276 5.037875e-07 9.384325e-02 3.873622e-08 2.682790e-03 981 15 37 71.500 -4.05225276 5.231556e-07 9.518432e-02 3.588229e-08 2.239466e-03 987 15 38 72.000 -4.05225276 5.410967e-07 9.630375e-02 3.323880e-08 1.869442e-03 993 15 39 72.500 -4.05225276 5.577161e-07 9.723819e-02 3.079029e-08 1.560588e-03 999 15 40 73.000 -4.05225276 5.731113e-07 9.801821e-02 2.852242e-08 1.302785e-03 1005 15 41 73.500 -4.05225276 5.873725e-07 9.866935e-02 2.642188e-08 1.087589e-03 1011 15 42 74.000 -4.05225276 6.005834e-07 9.921290e-02 2.447632e-08 9.079547e-04 1017 15 43 74.500 -4.05225276 6.128216e-07 9.966666e-02 2.267430e-08 7.580016e-04 1023 15 44 75.000 -4.05225276 6.241587e-07 1.000455e-01 2.100521e-08 6.328228e-04 1029 15 45 75.500 -4.05225276 6.346614e-07 1.003617e-01 1.945922e-08 5.283232e-04 1035 15 46 76.000 -4.05225276 6.443910e-07 1.006257e-01 1.802724e-08 4.410851e-04 1041 15 47 76.500 -4.05225276 6.534046e-07 1.008461e-01 1.670083e-08 3.682559e-04 1047 15 48 77.000 -4.05225276 6.617550e-07 1.010301e-01 1.547218e-08 3.074547e-04 1053 15 49 77.500 -4.05225276 6.694911e-07 1.011837e-01 1.433408e-08 2.566942e-04 1059 15 50 78.000 -4.05225276 6.766581e-07 1.013119e-01 1.327983e-08 2.143158e-04 1065 15 51 78.500 -4.05225276 6.832980e-07 1.014189e-01 1.230323e-08 1.789348e-04 1071 15 52 79.000 -4.05225276 6.894497e-07 1.015083e-01 1.139855e-08 1.493955e-04 1077 15 53 79.500 -4.05225276 6.951489e-07 1.015829e-01 1.056048e-08 1.247330e-04 1083 15 54 80.000 -4.05225276 7.004292e-07 1.016452e-01 9.784106e-09 1.041421e-04 1089 15 55 80.500 -4.05225276 7.053212e-07 1.016972e-01 9.064872e-09 8.695040e-05 1095 15 56 81.000 -4.05225276 7.098537e-07 1.017407e-01 8.398565e-09 7.259660e-05 1101 15 57 81.500 -4.05225276 7.140529e-07 1.017769e-01 7.781281e-09 6.061217e-05 1107 15 58 82.000 -4.05225276 7.179436e-07 1.018072e-01 7.209406e-09 5.060593e-05 1113 15 59 82.500 -4.05225276 7.215483e-07 1.018324e-01 6.679595e-09 4.225131e-05 1119 15 60 83.000 -4.05225276 7.248881e-07 1.018535e-01 6.188748e-09 3.527567e-05 1125 15 61 83.500 -4.05225276 7.279825e-07 1.018711e-01 5.733995e-09 2.945138e-05 1131 15 62 84.000 -4.05225276 7.308495e-07 1.018858e-01 5.312679e-09 2.458840e-05 1137 15 63 84.500 -4.05225276 7.335058e-07 1.018981e-01 4.922337e-09 2.052807e-05 1143 15 64 85.000 -4.05225276 7.359670e-07 1.019083e-01 4.560689e-09 1.713790e-05 1149 15 65 85.500 -4.05225276 7.382473e-07 1.019169e-01 4.225625e-09 1.430729e-05 1155 15 66 86.000 -4.05225276 7.403601e-07 1.019240e-01 3.915188e-09 1.194390e-05 1161 15 67 86.500 -4.05225276 7.423177e-07 1.019300e-01 3.627566e-09 9.970613e-06 1167 15 68 87.000 -4.05225276 7.441315e-07 1.019350e-01 3.361081e-09 8.323057e-06 1173 15 69 87.500 -4.05225276 7.458120e-07 1.019391e-01 3.114179e-09 6.947474e-06 1179 15 70 88.000 -4.05225276 7.473691e-07 1.019426e-01 2.885419e-09 5.798983e-06 1185 15 71 88.500 -4.05225276 7.488118e-07 1.019455e-01 2.673468e-09 4.840107e-06 1191 15 72 89.000 -4.05225276 7.501486e-07 1.019479e-01 2.477089e-09 4.039556e-06 1197 15 73 89.500 -4.05225276 7.513871e-07 1.019499e-01 2.295139e-09 3.371200e-06 1203 15 74 90.000 -4.05225276 7.525347e-07 1.019516e-01 2.126556e-09 2.813223e-06 1209 15 75 90.500 -4.05225276 7.535980e-07 1.019530e-01 1.970358e-09 2.347410e-06 1215 15 76 91.000 -4.05225276 7.545831e-07 1.019541e-01 1.825635e-09 1.958549e-06 1221 15 77 91.500 -4.05225276 7.554960e-07 1.019551e-01 1.691543e-09 1.633939e-06 1227 15 78 92.000 -4.05225276 7.563417e-07 1.019559e-01 1.567302e-09 1.362975e-06 1233 15 79 92.500 -4.05225276 7.571254e-07 1.019566e-01 1.452187e-09 1.136802e-06 1239 15 80 93.000 -4.05225276 7.578515e-07 1.019572e-01 1.345527e-09 9.480253e-07 1245 15 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB target: He4 Ref. => Z=2 N=2 E: -5.872267 = E1b 46.65735 + E2b -52.52961 ( -7.298 -36.942 -8.289), + E3b 0.00000 EMP2 -2.54240 1b -0.00000 pp -0.03408 pn -2.48016 nn -0.02817 EMP3 -0.11250 pp 0.030 hh -0.349 ph 0.207 E_HF -5.87227 E_MBPT(3) = -8.5272 Eexp: -28.296 parameters/optional_parameters.jl is used for IMSRG parameters in parameters/optional_parameters.jl will be used. def-by-run d6j_lj done! 240 step: s E0 ||Omega_1|| ||Omega_2|| ||Eta_1|| ||Eta_2|| Ncomm. nwritten 0 0.000 -5.87226696 0.000000e+00 0.000000e+00 6.477848e-18 5.224524e-01 0 0 1 0.500 -7.94881314 3.238924e-18 2.612262e-01 2.279622e-02 2.381511e-01 8 0 2 1.000 -8.44795260 1.139811e-02 1.190755e-01 2.618768e-02 1.252831e-01 15 1 3 1.500 -8.60330203 2.454127e-02 1.812429e-01 2.365202e-02 6.978627e-02 24 1 4 2.000 -8.65841821 3.644456e-02 2.154872e-01 1.960131e-02 4.045927e-02 33 1 5 2.500 -8.68010266 4.632955e-02 2.349984e-01 1.562641e-02 2.434561e-02 42 1 6 3.000 -8.68945171 5.422267e-02 2.464235e-01 1.224308e-02 1.520325e-02 51 1 7 3.500 -8.69368338 6.121541e-03 7.601625e-03 9.554421e-03 9.798370e-03 56 2 8 4.000 -8.69575196 1.089874e-02 1.246932e-02 7.475101e-03 6.584145e-03 62 2 9 4.500 -8.69682965 1.463626e-02 1.567717e-02 5.899609e-03 4.669665e-03 68 2 10 5.000 -8.69743163 1.758603e-02 1.785347e-02 4.719567e-03 3.561692e-03 74 2 11 5.500 -8.69779659 1.994576e-02 1.937932e-02 3.840689e-03 2.956460e-03 80 2 12 6.000 -8.69803938 2.186604e-02 2.049318e-02 3.186918e-03 2.645172e-03 86 2 13 6.500 -8.69821679 2.345942e-02 2.134759e-02 2.699404e-03 2.487011e-03 92 2 14 7.000 -8.69835743 2.480905e-02 2.204139e-02 2.333747e-03 2.398666e-03 98 2 15 7.500 -8.69847597 2.597585e-02 2.263876e-02 2.056989e-03 2.337442e-03 104 2 16 8.000 -8.69858009 2.700426e-02 2.318108e-02 1.844930e-03 2.283949e-03 110 2 17 8.500 -8.69867389 2.792665e-02 2.369456e-02 1.679930e-03 2.230443e-03 116 2 18 9.000 -8.69875966 2.876654e-02 2.419527e-02 1.549192e-03 2.174502e-03 122 2 19 9.500 -8.69883877 2.954107e-02 2.469258e-02 1.443470e-03 2.115937e-03 129 2 20 10.000 -8.69891207 3.026273e-02 2.519145e-02 1.356090e-03 2.055371e-03 136 2 21 10.500 -8.69898017 3.094071e-02 2.569401e-02 1.282247e-03 1.993618e-03 143 2 22 11.000 -8.69904351 3.158177e-02 2.620064e-02 1.218478e-03 1.931438e-03 150 2 23 11.500 -8.69910249 3.219096e-02 2.671069e-02 1.162290e-03 1.869454e-03 157 2 24 12.000 -8.69915741 3.277205e-02 2.722290e-02 1.111886e-03 1.808146e-03 164 2 25 12.500 -8.69920856 3.332794e-02 2.773578e-02 1.065966e-03 1.747865e-03 171 2 26 13.000 -8.69925620 3.386087e-02 2.824773e-02 1.023591e-03 1.688856e-03 178 2 27 13.500 -8.69930058 3.437262e-02 2.875723e-02 9.840764e-04 1.631288e-03 185 2 28 14.000 -8.69934191 3.486462e-02 2.926284e-02 9.469230e-04 1.575265e-03 192 2 29 14.500 -8.69938040 3.533804e-02 2.976326e-02 9.117632e-04 1.520849e-03 199 2 30 15.000 -8.69941624 3.579389e-02 3.025737e-02 8.783245e-04 1.468069e-03 206 2 31 15.500 -8.69944961 3.623301e-02 3.074419e-02 8.464023e-04 1.416931e-03 213 2 32 16.000 -8.69948069 3.665618e-02 3.122289e-02 8.158409e-04 1.367424e-03 220 2 33 16.500 -8.69950962 3.706407e-02 3.169279e-02 7.865200e-04 1.319525e-03 227 2 34 17.000 -8.69953655 3.745730e-02 3.215334e-02 7.583449e-04 1.273206e-03 234 2 35 17.500 -8.69956162 3.783645e-02 3.260407e-02 7.312392e-04 1.228431e-03 241 2 36 18.000 -8.69958496 3.820204e-02 3.304466e-02 7.051400e-04 1.185160e-03 248 2 37 18.500 -8.69960668 3.855458e-02 3.347484e-02 6.799943e-04 1.143355e-03 255 2 38 19.000 -8.69962690 3.889456e-02 3.389443e-02 6.557565e-04 1.102972e-03 262 2 39 19.500 -8.69964571 3.922241e-02 3.430332e-02 6.323864e-04 1.063969e-03 269 2 40 20.000 -8.69966322 3.953859e-02 3.470146e-02 6.098479e-04 1.026305e-03 276 2 41 20.500 -8.69967951 3.984349e-02 3.508883e-02 5.881081e-04 9.899378e-04 283 2 42 21.000 -8.69969467 4.013752e-02 3.546548e-02 5.671366e-04 9.548260e-04 290 2 43 21.500 -8.69970877 4.042107e-02 3.583148e-02 5.469049e-04 9.209294e-04 297 2 44 22.000 -8.69972190 4.069451e-02 3.618693e-02 5.273862e-04 8.882086e-04 304 2 45 22.500 -8.69973411 4.095819e-02 3.653195e-02 5.085553e-04 8.566251e-04 311 2 46 23.000 -8.69974546 4.121245e-02 3.686670e-02 4.903877e-04 8.261413e-04 318 2 47 23.500 -8.69975603 4.145763e-02 3.719135e-02 4.728604e-04 7.967209e-04 325 2 48 24.000 -8.69976586 4.169404e-02 3.750607e-02 4.559511e-04 7.683283e-04 332 2 49 24.500 -8.69977500 4.192201e-02 3.781106e-02 4.396384e-04 7.409291e-04 339 2 50 25.000 -8.69978351 4.214181e-02 3.810652e-02 4.239015e-04 7.144900e-04 346 2 51 25.500 -8.69979142 4.235375e-02 3.839267e-02 4.087207e-04 6.889785e-04 353 2 52 26.000 -8.69979878 4.255810e-02 3.866970e-02 3.940767e-04 6.643633e-04 360 2 53 26.500 -8.69980562 4.275513e-02 3.893786e-02 3.799509e-04 6.406139e-04 367 2 54 27.000 -8.69981199 4.294509e-02 3.919735e-02 3.663254e-04 6.177008e-04 374 2 55 27.500 -8.69981791 4.312824e-02 3.944840e-02 3.531830e-04 5.955956e-04 381 2 56 28.000 -8.69982341 4.330482e-02 3.969124e-02 3.405068e-04 5.742705e-04 388 2 57 28.500 -8.69982853 4.347507e-02 3.992608e-02 3.282806e-04 5.536988e-04 395 2 58 29.000 -8.69983330 4.363920e-02 4.015314e-02 3.164889e-04 5.338546e-04 402 2 59 29.500 -8.69983772 4.379744e-02 4.037265e-02 3.051165e-04 5.147129e-04 409 2 60 30.000 -8.69984184 4.394999e-02 4.058483e-02 2.941487e-04 4.962494e-04 416 2 61 30.500 -8.69984567 4.409705e-02 4.078989e-02 2.835716e-04 4.784407e-04 423 2 62 31.000 -8.69984923 4.423883e-02 4.098803e-02 2.733713e-04 4.612640e-04 430 2 63 31.500 -8.69985255 4.437551e-02 4.117947e-02 2.635348e-04 4.446975e-04 437 2 64 32.000 -8.69985563 4.450727e-02 4.136441e-02 2.540492e-04 4.287199e-04 444 2 65 32.500 -8.69985849 4.463429e-02 4.154305e-02 2.449024e-04 4.133107e-04 451 2 66 33.000 -8.69986115 4.475673e-02 4.171559e-02 2.360823e-04 3.984501e-04 458 2 67 33.500 -8.69986363 4.487477e-02 4.188221e-02 2.275774e-04 3.841190e-04 465 2 68 34.000 -8.69986594 4.498855e-02 4.204310e-02 2.193768e-04 3.702988e-04 472 2 69 34.500 -8.69986808 4.509823e-02 4.219846e-02 2.114696e-04 3.569716e-04 479 2 70 35.000 -8.69987007 4.520396e-02 4.234844e-02 2.038455e-04 3.441202e-04 486 2 71 35.500 -8.69987192 4.530588e-02 4.249324e-02 1.964945e-04 3.317278e-04 493 2 72 36.000 -8.69987364 4.540412e-02 4.263301e-02 1.894069e-04 3.197783e-04 500 2 73 36.500 -8.69987525 4.549882e-02 4.276792e-02 1.825735e-04 3.082562e-04 507 2 74 37.000 -8.69987674 4.559010e-02 4.289813e-02 1.759852e-04 2.971462e-04 514 2 75 37.500 -8.69987812 4.567809e-02 4.302379e-02 1.696333e-04 2.864340e-04 521 2 76 38.000 -8.69987941 4.576290e-02 4.314507e-02 1.635094e-04 2.761054e-04 528 2 77 38.500 -8.69988061 4.584465e-02 4.326209e-02 1.576055e-04 2.661470e-04 535 2 78 39.000 -8.69988172 4.592345e-02 4.337501e-02 1.519137e-04 2.565455e-04 542 2 79 39.500 -8.69988276 4.599941e-02 4.348397e-02 1.464264e-04 2.472884e-04 549 2 80 40.000 -8.69988372 4.607262e-02 4.358909e-02 1.411365e-04 2.383635e-04 556 2 81 40.500 -8.69988462 4.614318e-02 4.369051e-02 1.360368e-04 2.297589e-04 563 2 82 41.000 -8.69988545 4.621120e-02 4.378835e-02 1.311206e-04 2.214633e-04 570 2 83 41.500 -8.69988623 4.627675e-02 4.388273e-02 1.263813e-04 2.134658e-04 577 2 84 42.000 -8.69988695 4.633994e-02 4.397378e-02 1.218126e-04 2.057556e-04 584 2 85 42.500 -8.69988762 4.640084e-02 4.406161e-02 1.174085e-04 1.983227e-04 591 2 86 43.000 -8.69988824 4.645955e-02 4.414632e-02 1.131630e-04 1.911570e-04 598 2 87 43.500 -8.69988882 4.651612e-02 4.422804e-02 1.090704e-04 1.842491e-04 605 2 88 44.000 -8.69988936 4.657066e-02 4.430685e-02 1.051254e-04 1.775899e-04 612 2 89 44.500 -8.69988987 4.662322e-02 4.438285e-02 1.013226e-04 1.711703e-04 619 2 90 45.000 -8.69989033 4.667388e-02 4.445616e-02 9.765693e-05 1.649819e-04 626 2 91 45.500 -8.69989077 4.672270e-02 4.452686e-02 9.412346e-05 1.590164e-04 633 2 92 46.000 -8.69989117 4.676976e-02 4.459504e-02 9.071747e-05 1.532658e-04 640 2 93 46.500 -8.69989155 4.681512e-02 4.466079e-02 8.743437e-05 1.477225e-04 647 2 94 47.000 -8.69989190 4.685883e-02 4.472419e-02 8.426976e-05 1.423790e-04 654 2 95 47.500 -8.69989223 4.690097e-02 4.478533e-02 8.121939e-05 1.372281e-04 661 2 96 48.000 -8.69989253 4.694157e-02 4.484429e-02 7.827916e-05 1.322630e-04 668 2 97 48.500 -8.69989281 4.698071e-02 4.490113e-02 7.544510e-05 1.274771e-04 675 2 98 49.000 -8.69989307 4.701843e-02 4.495595e-02 7.271341e-05 1.228638e-04 682 2 99 49.500 -8.69989332 4.705479e-02 4.500880e-02 7.008040e-05 1.184170e-04 689 2 100 50.000 -8.69989355 4.708983e-02 4.505976e-02 6.754252e-05 1.141307e-04 696 2 101 50.500 -8.69989376 4.712360e-02 4.510890e-02 6.509635e-05 1.099991e-04 703 2 102 51.000 -8.69989396 4.715614e-02 4.515627e-02 6.273860e-05 1.060168e-04 710 2 103 51.500 -8.69989414 4.718751e-02 4.520195e-02 6.046608e-05 1.021783e-04 717 2 104 52.000 -8.69989431 4.721774e-02 4.524598e-02 5.827571e-05 9.847839e-05 724 2 105 52.500 -8.69989447 4.724688e-02 4.528844e-02 5.616455e-05 9.491220e-05 731 2 106 53.000 -8.69989462 4.727496e-02 4.532937e-02 5.412973e-05 9.147488e-05 738 2 107 53.500 -8.69989476 4.730202e-02 4.536883e-02 5.216851e-05 8.816179e-05 745 2 108 54.000 -8.69989488 4.732811e-02 4.540688e-02 5.027823e-05 8.496846e-05 752 2 109 54.500 -8.69989500 4.735324e-02 4.544355e-02 4.845634e-05 8.189057e-05 759 2 110 55.000 -8.69989512 4.737747e-02 4.547891e-02 4.670036e-05 7.892397e-05 766 2 111 55.500 -8.69989522 4.740082e-02 4.551299e-02 4.500793e-05 7.606464e-05 773 2 112 56.000 -8.69989532 4.742332e-02 4.554585e-02 4.337674e-05 7.330873e-05 780 2 113 56.500 -8.69989541 4.744501e-02 4.557752e-02 4.180459e-05 7.065251e-05 787 2 114 57.000 -8.69989549 4.746591e-02 4.560805e-02 4.028935e-05 6.809237e-05 794 2 115 57.500 -8.69989557 4.748606e-02 4.563749e-02 3.882896e-05 6.562486e-05 801 2 116 58.000 -8.69989564 4.750547e-02 4.566586e-02 3.742144e-05 6.324664e-05 808 2 117 58.500 -8.69989571 4.752418e-02 4.569321e-02 3.606488e-05 6.095448e-05 815 2 118 59.000 -8.69989577 4.754221e-02 4.571958e-02 3.475744e-05 5.874527e-05 822 2 119 59.500 -8.69989583 4.755959e-02 4.574499e-02 3.349735e-05 5.661603e-05 829 2 120 60.000 -8.69989589 4.757634e-02 4.576949e-02 3.228290e-05 5.456387e-05 836 2 121 60.500 -8.69989594 4.759248e-02 4.579310e-02 3.111243e-05 5.258600e-05 843 2 122 61.000 -8.69989599 4.760803e-02 4.581586e-02 2.998436e-05 5.067974e-05 850 2 123 61.500 -8.69989603 4.762302e-02 4.583780e-02 2.889715e-05 4.884250e-05 857 2 124 62.000 -8.69989607 4.763747e-02 4.585895e-02 2.784932e-05 4.707180e-05 864 2 125 62.500 -8.69989611 4.765140e-02 4.587933e-02 2.683946e-05 4.536522e-05 871 2 126 63.000 -8.69989615 4.766482e-02 4.589898e-02 2.586619e-05 4.372045e-05 878 2 127 63.500 -8.69989618 4.767775e-02 4.591792e-02 2.492818e-05 4.213525e-05 885 2 128 64.000 -8.69989622 4.769021e-02 4.593617e-02 2.402416e-05 4.060748e-05 892 2 129 64.500 -8.69989625 4.770222e-02 4.595377e-02 2.315290e-05 3.913505e-05 899 2 130 65.000 -8.69989627 4.771380e-02 4.597072e-02 2.231321e-05 3.771596e-05 906 2 131 65.500 -8.69989630 4.772496e-02 4.598707e-02 2.150396e-05 3.634829e-05 913 2 132 66.000 -8.69989632 4.773571e-02 4.600282e-02 2.072404e-05 3.503017e-05 920 2 133 66.500 -8.69989635 4.774607e-02 4.601801e-02 1.997238e-05 3.375981e-05 927 2 134 67.000 -8.69989637 4.775605e-02 4.603264e-02 1.924797e-05 3.253549e-05 934 2 135 67.500 -8.69989639 4.776568e-02 4.604675e-02 1.854982e-05 3.135554e-05 941 2 136 68.000 -8.69989640 4.777495e-02 4.606035e-02 1.787698e-05 3.021835e-05 948 2 137 68.500 -8.69989642 4.778389e-02 4.607345e-02 1.722853e-05 2.912237e-05 955 2 138 69.000 -8.69989644 4.779250e-02 4.608608e-02 1.660359e-05 2.806612e-05 962 2 139 69.500 -8.69989645 4.780081e-02 4.609825e-02 1.600130e-05 2.704815e-05 969 2 140 70.000 -8.69989647 4.780881e-02 4.610999e-02 1.542085e-05 2.606708e-05 976 2 141 70.500 -8.69989648 4.781652e-02 4.612129e-02 1.486145e-05 2.512158e-05 983 2 142 71.000 -8.69989649 4.782395e-02 4.613219e-02 1.432233e-05 2.421035e-05 990 2 143 71.500 -8.69989650 4.783111e-02 4.614270e-02 1.380276e-05 2.333216e-05 997 2 144 72.000 -8.69989652 4.783801e-02 4.615282e-02 1.330203e-05 2.248580e-05 1004 2 145 72.500 -8.69989653 4.784466e-02 4.616258e-02 1.281946e-05 2.167014e-05 1011 2 146 73.000 -8.69989654 4.785107e-02 4.617198e-02 1.235438e-05 2.088404e-05 1018 2 147 73.500 -8.69989654 4.785725e-02 4.618104e-02 1.190618e-05 2.012645e-05 1025 2 148 74.000 -8.69989655 4.786320e-02 4.618978e-02 1.147422e-05 1.939632e-05 1032 2 149 74.500 -8.69989656 4.786894e-02 4.619820e-02 1.105794e-05 1.869268e-05 1039 2 150 75.000 -8.69989657 4.787446e-02 4.620631e-02 1.065675e-05 1.801454e-05 1046 2 151 75.500 -8.69989657 4.787979e-02 4.621413e-02 1.027011e-05 1.736100e-05 1053 2 152 76.000 -8.69989658 4.788493e-02 4.622167e-02 9.897494e-06 1.673116e-05 1060 2 153 76.500 -8.69989659 4.788988e-02 4.622893e-02 9.538393e-06 1.612416e-05 1067 2 154 77.000 -8.69989659 4.789464e-02 4.623593e-02 9.192317e-06 1.553918e-05 1074 2 155 77.500 -8.69989660 4.789924e-02 4.624268e-02 8.858795e-06 1.497541e-05 1081 2 156 78.000 -8.69989660 4.790367e-02 4.624918e-02 8.537370e-06 1.443209e-05 1088 2 157 78.500 -8.69989661 4.790794e-02 4.625545e-02 8.227604e-06 1.390847e-05 1095 2 158 79.000 -8.69989661 4.791205e-02 4.626149e-02 7.929075e-06 1.340385e-05 1102 2 159 79.500 -8.69989662 4.791602e-02 4.626731e-02 7.641375e-06 1.291752e-05 1109 2 160 80.000 -8.69989662 4.791984e-02 4.627292e-02 7.364111e-06 1.244884e-05 1116 2 161 80.500 -8.69989662 4.792352e-02 4.627832e-02 7.096905e-06 1.199716e-05 1123 2 162 81.000 -8.69989663 4.792707e-02 4.628353e-02 6.839393e-06 1.156186e-05 1130 2 163 81.500 -8.69989663 4.793049e-02 4.628856e-02 6.591223e-06 1.114235e-05 1137 2 164 82.000 -8.69989663 4.793378e-02 4.629340e-02 6.352055e-06 1.073806e-05 1144 2 165 82.500 -8.69989664 4.793696e-02 4.629806e-02 6.121565e-06 1.034844e-05 1151 2 166 83.000 -8.69989664 4.794002e-02 4.630255e-02 5.899436e-06 9.972950e-06 1158 2 167 83.500 -8.69989664 4.794297e-02 4.630689e-02 5.685366e-06 9.611081e-06 1165 2 168 84.000 -8.69989665 4.794581e-02 4.631106e-02 5.479063e-06 9.262339e-06 1172 2 169 84.500 -8.69989665 4.794855e-02 4.631508e-02 5.280244e-06 8.926249e-06 1179 2 170 85.000 -8.69989665 4.795119e-02 4.631896e-02 5.088639e-06 8.602352e-06 1186 2 171 85.500 -8.69989665 4.795373e-02 4.632270e-02 4.903986e-06 8.290206e-06 1193 2 172 86.000 -8.69989665 4.795619e-02 4.632630e-02 4.726032e-06 7.989384e-06 1200 2 173 86.500 -8.69989666 4.795855e-02 4.632977e-02 4.554534e-06 7.699476e-06 1207 2 174 87.000 -8.69989666 4.796083e-02 4.633312e-02 4.389259e-06 7.420086e-06 1214 2 175 87.500 -8.69989666 4.796302e-02 4.633634e-02 4.229981e-06 7.150832e-06 1221 2 176 88.000 -8.69989666 4.796514e-02 4.633945e-02 4.076482e-06 6.891347e-06 1228 2 177 88.500 -8.69989666 4.796717e-02 4.634244e-02 3.928552e-06 6.641277e-06 1235 2 178 89.000 -8.69989666 4.796914e-02 4.634533e-02 3.785990e-06 6.400280e-06 1242 2 179 89.500 -8.69989666 4.797103e-02 4.634811e-02 3.648600e-06 6.168027e-06 1249 2 180 90.000 -8.69989667 4.797285e-02 4.635079e-02 3.516196e-06 5.944201e-06 1256 2 181 90.500 -8.69989667 4.797461e-02 4.635337e-02 3.388596e-06 5.728496e-06 1263 2 182 91.000 -8.69989667 4.797631e-02 4.635586e-02 3.265626e-06 5.520617e-06 1270 2 183 91.500 -8.69989667 4.797794e-02 4.635826e-02 3.147118e-06 5.320281e-06 1277 2 184 92.000 -8.69989667 4.797951e-02 4.636057e-02 3.032911e-06 5.127214e-06 1284 2 185 92.500 -8.69989667 4.798103e-02 4.636280e-02 2.922847e-06 4.941153e-06 1291 2 186 93.000 -8.69989667 4.798249e-02 4.636495e-02 2.816777e-06 4.761843e-06 1298 2 187 93.500 -8.69989667 4.798390e-02 4.636702e-02 2.714557e-06 4.589039e-06 1305 2 188 94.000 -8.69989667 4.798526e-02 4.636901e-02 2.616045e-06 4.422505e-06 1312 2 189 94.500 -8.69989667 4.798656e-02 4.637093e-02 2.521108e-06 4.262014e-06 1319 2 190 95.000 -8.69989668 4.798782e-02 4.637278e-02 2.429616e-06 4.107347e-06 1326 2 191 95.500 -8.69989668 4.798904e-02 4.637457e-02 2.341445e-06 3.958292e-06 1333 2 192 96.000 -8.69989668 4.799021e-02 4.637629e-02 2.256472e-06 3.814646e-06 1340 2 193 96.500 -8.69989668 4.799134e-02 4.637795e-02 2.174584e-06 3.676212e-06 1347 2 194 97.000 -8.69989668 4.799243e-02 4.637954e-02 2.095666e-06 3.542802e-06 1354 2 195 97.500 -8.69989668 4.799347e-02 4.638108e-02 2.019613e-06 3.414233e-06 1361 2 196 98.000 -8.69989668 4.799448e-02 4.638257e-02 1.946319e-06 3.290329e-06 1368 2 197 98.500 -8.69989668 4.799546e-02 4.638400e-02 1.875686e-06 3.170921e-06 1375 2 198 99.000 -8.69989668 4.799639e-02 4.638538e-02 1.807615e-06 3.055846e-06 1382 2 199 99.500 -8.69989668 4.799730e-02 4.638670e-02 1.742015e-06 2.944948e-06 1389 2 200 100.000 -8.69989668 4.799817e-02 4.638798e-02 1.678795e-06 2.838073e-06 1396 2 201 100.500 -8.69989668 4.799901e-02 4.638922e-02 1.617869e-06 2.735077e-06 1403 2 202 101.000 -8.69989668 4.799982e-02 4.639041e-02 1.559155e-06 2.635819e-06 1410 2 203 101.500 -8.69989668 4.800060e-02 4.639155e-02 1.502571e-06 2.540162e-06 1417 2 204 102.000 -8.69989668 4.800135e-02 4.639266e-02 1.448040e-06 2.447977e-06 1424 2 205 102.500 -8.69989668 4.800207e-02 4.639372e-02 1.395489e-06 2.359137e-06 1431 2 206 103.000 -8.69989668 4.800277e-02 4.639475e-02 1.344844e-06 2.273521e-06 1438 2 207 103.500 -8.69989668 4.800344e-02 4.639573e-02 1.296037e-06 2.191012e-06 1445 2 208 104.000 -8.69989668 4.800409e-02 4.639669e-02 1.249002e-06 2.111497e-06 1452 2 209 104.500 -8.69989668 4.800471e-02 4.639760e-02 1.203674e-06 2.034868e-06 1459 2 210 105.000 -8.69989668 4.800532e-02 4.639849e-02 1.159990e-06 1.961019e-06 1466 2 211 105.500 -8.69989668 4.800590e-02 4.639934e-02 1.117892e-06 1.889851e-06 1473 2 212 106.000 -8.69989669 4.800646e-02 4.640016e-02 1.077321e-06 1.821265e-06 1480 2 213 106.500 -8.69989669 4.800699e-02 4.640095e-02 1.038223e-06 1.755168e-06 1487 2 214 107.000 -8.69989669 4.800751e-02 4.640172e-02 1.000544e-06 1.691470e-06 1494 2 215 107.500 -8.69989669 4.800801e-02 4.640245e-02 9.642323e-07 1.630083e-06 1501 2 216 108.000 -8.69989669 4.800850e-02 4.640316e-02 9.292383e-07 1.570925e-06 1508 2 217 108.500 -8.69989669 4.800896e-02 4.640384e-02 8.955143e-07 1.513913e-06 1515 2 218 109.000 -8.69989669 4.800941e-02 4.640450e-02 8.630142e-07 1.458970e-06 1522 2 219 109.500 -8.69989669 4.800984e-02 4.640514e-02 8.316935e-07 1.406021e-06 1529 2 220 110.000 -8.69989669 4.801026e-02 4.640575e-02 8.015095e-07 1.354994e-06 1536 2 221 110.500 -8.69989669 4.801066e-02 4.640634e-02 7.724209e-07 1.305818e-06 1543 2 222 111.000 -8.69989669 4.801104e-02 4.640690e-02 7.443879e-07 1.258427e-06 1550 2 223 111.500 -8.69989669 4.801141e-02 4.640745e-02 7.173724e-07 1.212756e-06 1557 2 224 112.000 -8.69989669 4.801177e-02 4.640798e-02 6.913372e-07 1.168743e-06 1564 2 225 112.500 -8.69989669 4.801212e-02 4.640849e-02 6.662470e-07 1.126327e-06 1571 2 226 113.000 -8.69989669 4.801245e-02 4.640897e-02 6.420672e-07 1.085450e-06 1578 2 227 113.500 -8.69989669 4.801277e-02 4.640945e-02 6.187650e-07 1.046056e-06 1585 2 228 114.000 -8.69989669 4.801308e-02 4.640990e-02 5.963085e-07 1.008092e-06 1592 2 229 114.500 -8.69989669 4.801338e-02 4.641034e-02 5.746670e-07 9.715063e-07 1599 2 230 115.000 -8.69989669 4.801367e-02 4.641076e-02 5.538109e-07 9.362480e-07 1606 2 231 115.500 -8.69989669 4.801394e-02 4.641117e-02 5.337117e-07 9.022693e-07 1613 2 232 116.000 -8.69989669 4.801421e-02 4.641156e-02 5.143419e-07 8.695238e-07 1620 2 233 116.500 -8.69989669 4.801447e-02 4.641194e-02 4.956751e-07 8.379666e-07 1627 2 Operator:Rp2 HF point proton radius 1.502259 charge radius 1.716067 => HF+PT 1.725366 IMSRG point proton radius 1.559825 charge radius 1.766681 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.46 KB dictHOB 0.46 KB target: He4 Ref. => Z=2 N=2 E: -5.872267 = E1b 46.65735 + E2b -52.52961 ( -7.298 -36.942 -8.289), + E3b 0.00000 EMP2 -2.54240 1b -0.00000 pp -0.03408 pn -2.48016 nn -0.02817 EMP3 -0.11250 pp 0.030 hh -0.349 ph 0.207 E_HF -5.87227 E_MBPT(3) = -8.5272 Eexp: -28.296 parameters/optional_parameters_forDMD.jl is used for IMSRG parameters in parameters/optional_parameters_forDMD.jl will be used. def-by-run d6j_lj done! 240 step: s E0 ||Omega_1|| ||Omega_2|| ||Eta_1|| ||Eta_2|| Ncomm. nwritten 0 0.000 -5.87226696 0.000000e+00 0.000000e+00 6.477848e-18 5.224524e-01 0 0 1 0.500 -7.94881314 3.238924e-18 2.612262e-01 2.279622e-02 2.381511e-01 8 0 2 1.000 -8.44866027 1.155713e-02 3.775065e-01 2.617445e-02 1.255542e-01 20 0 3 1.500 -8.60580720 2.487332e-02 4.373845e-01 2.360824e-02 7.028061e-02 32 0 4 2.000 -8.66271302 3.691197e-02 4.701619e-01 1.953050e-02 4.103009e-02 43 0 5 2.500 -8.68581118 4.688881e-02 4.888015e-01 1.553701e-02 2.489865e-02 54 0 6 3.000 -8.69620019 5.483630e-02 4.997259e-01 1.214291e-02 1.568976e-02 65 0 7 3.500 -8.70132166 6.105456e-02 5.063051e-01 9.438175e-03 1.025488e-02 76 0 8 4.000 -8.70406233 6.589275e-02 5.103710e-01 7.356064e-03 6.958220e-03 88 0 9 4.500 -8.70564569 6.966757e-02 5.129470e-01 5.784838e-03 4.935562e-03 100 0 10 5.000 -8.70663195 7.263947e-02 5.146189e-01 4.612676e-03 3.713549e-03 112 0 11 5.500 -8.70729474 7.501623e-02 5.157289e-01 3.740918e-03 3.011040e-03 123 0 12 6.000 -8.70777343 7.694644e-02 5.164843e-01 3.096591e-03 2.631416e-03 134 0 13 6.500 -8.70814298 7.854651e-02 5.170105e-01 2.619707e-03 2.437021e-03 145 0 14 7.000 -8.70844485 7.990216e-02 5.173862e-01 2.265271e-03 2.337252e-03 156 0 15 7.500 -8.70870273 8.107610e-02 5.176616e-01 2.000004e-03 2.280200e-03 167 0 16 8.000 -8.70893063 8.211397e-02 5.178693e-01 1.799518e-03 2.239558e-03 178 0 17 8.500 -8.70913709 8.304893e-02 5.180310e-01 1.646050e-03 2.203290e-03 189 0 18 9.000 -8.70932749 8.390505e-02 5.181610e-01 1.526714e-03 2.166509e-03 200 0 19 9.500 -8.70950535 8.469981e-02 5.182693e-01 1.432185e-03 2.127651e-03 211 0 20 10.000 -8.70967301 8.544589e-02 5.183624e-01 1.355728e-03 2.086582e-03 222 0 21 10.500 -8.70983211 8.615255e-02 5.184451e-01 1.292482e-03 2.043708e-03 233 0 22 11.000 -8.70998382 8.682655e-02 5.185204e-01 1.238939e-03 1.999574e-03 244 0 23 11.500 -8.71012898 8.747285e-02 5.185906e-01 1.192569e-03 1.954698e-03 255 0 24 12.000 -8.71026823 8.809513e-02 5.186572e-01 1.151549e-03 1.909518e-03 266 0 25 12.500 -8.71040207 8.869614e-02 5.187213e-01 1.114559e-03 1.864377e-03 277 0 26 13.000 -8.71053090 8.927793e-02 5.187836e-01 1.080648e-03 1.819536e-03 288 0 27 13.500 -8.71065503 8.984209e-02 5.188445e-01 1.049126e-03 1.775189e-03 299 0 28 14.000 -8.71077474 9.038984e-02 5.189045e-01 1.019494e-03 1.731472e-03 310 0 29 14.500 -8.71089025 9.092216e-02 5.189637e-01 9.913881e-04 1.688481e-03 321 0 30 15.000 -8.71100176 9.143983e-02 5.190222e-01 9.645437e-04 1.646284e-03 332 0 31 15.500 -8.71110946 9.194350e-02 5.190803e-01 9.387669e-04 1.604922e-03 343 0 32 16.000 -8.71121350 9.243373e-02 5.191378e-01 9.139144e-04 1.564422e-03 354 0 33 16.500 -8.71131403 9.291099e-02 5.191949e-01 8.898800e-04 1.524797e-03 365 0 34 17.000 -8.71141119 9.337572e-02 5.192515e-01 8.665841e-04 1.486052e-03 376 0 35 17.500 -8.71150511 9.382828e-02 5.193076e-01 8.439660e-04 1.448185e-03 387 0 36 18.000 -8.71159592 9.426903e-02 5.193632e-01 8.219789e-04 1.411191e-03 398 0 37 18.500 -8.71168371 9.469831e-02 5.194183e-01 8.005863e-04 1.375061e-03 409 0 38 19.000 -8.71176862 9.511642e-02 5.194728e-01 7.797585e-04 1.339783e-03 420 0 39 19.500 -8.71185073 9.552365e-02 5.195268e-01 7.594714e-04 1.305343e-03 431 0 40 20.000 -8.71193015 9.592029e-02 5.195802e-01 7.397047e-04 1.271728e-03 442 0 41 20.500 -8.71200698 9.630661e-02 5.196329e-01 7.204406e-04 1.238922e-03 453 0 42 21.000 -8.71208130 9.668287e-02 5.196851e-01 7.016638e-04 1.206910e-03 464 0 43 21.500 -8.71215321 9.704933e-02 5.197365e-01 6.833603e-04 1.175677e-03 475 0 44 22.000 -8.71222439 9.739089e-02 5.197873e-01 6.763648e-04 1.140663e-03 485 0 45 22.500 -8.71229399 9.772896e-02 5.198365e-01 6.657104e-04 1.108410e-03 495 0 46 23.000 -8.71236182 9.806170e-02 5.198848e-01 6.529124e-04 1.078065e-03 505 0 47 23.500 -8.71242780 9.838805e-02 5.199323e-01 6.389030e-04 1.049146e-03 515 0 48 24.000 -8.71249188 9.870740e-02 5.199793e-01 6.242610e-04 1.021365e-03 525 0 49 24.500 -8.71255407 9.901943e-02 5.200256e-01 6.093484e-04 9.945380e-04 535 0 50 25.000 -8.71261440 9.932401e-02 5.200713e-01 5.943924e-04 9.685466e-04 545 0 51 25.500 -8.71267290 9.962111e-02 5.201163e-01 5.795360e-04 9.433104e-04 555 0 52 26.000 -8.71272963 9.991079e-02 5.201607e-01 5.648690e-04 9.187729e-04 565 0 53 26.500 -8.71278462 1.001931e-01 5.202043e-01 5.504470e-04 8.948929e-04 575 0 54 27.000 -8.71283793 1.004683e-01 5.202473e-01 5.363042e-04 8.716390e-04 585 0 55 27.500 -8.71288961 1.007363e-01 5.202895e-01 5.224605e-04 8.489861e-04 595 0 56 28.000 -8.71293971 1.009975e-01 5.203309e-01 5.089268e-04 8.269132e-04 605 0 57 28.500 -8.71298827 1.012519e-01 5.203716e-01 4.957076e-04 8.054022e-04 615 0 58 29.000 -8.71303536 1.014997e-01 5.204116e-01 4.828040e-04 7.844370e-04 625 0 59 29.500 -8.71308101 1.017410e-01 5.204509e-01 4.702140e-04 7.640028e-04 635 0 60 30.000 -8.71312527 1.019760e-01 5.204893e-01 4.579342e-04 7.440858e-04 645 0 61 30.500 -8.71316819 1.022049e-01 5.205271e-01 4.459597e-04 7.246728e-04 655 0 62 31.000 -8.71320981 1.024278e-01 5.205641e-01 4.342854e-04 7.057513e-04 665 0 63 31.500 -8.71325016 1.026449e-01 5.206004e-01 4.229053e-04 6.873094e-04 675 0 64 32.000 -8.71328930 1.028563e-01 5.206360e-01 4.118133e-04 6.693354e-04 685 0 65 32.500 -8.71332727 1.030622e-01 5.206708e-01 4.010030e-04 6.518179e-04 695 0 66 33.000 -8.71336409 1.032626e-01 5.207050e-01 3.904683e-04 6.347459e-04 705 0 67 33.500 -8.71339980 1.034578e-01 5.207384e-01 3.802027e-04 6.181088e-04 715 0 68 34.000 -8.71343445 1.036478e-01 5.207711e-01 3.702000e-04 6.018959e-04 725 0 69 34.500 -8.71346806 1.038329e-01 5.208032e-01 3.604538e-04 5.860971e-04 735 0 70 35.000 -8.71350067 1.040130e-01 5.208345e-01 3.509582e-04 5.707023e-04 745 0 71 35.500 -8.71353232 1.041885e-01 5.208652e-01 3.417069e-04 5.557018e-04 755 0 72 36.000 -8.71356302 1.043593e-01 5.208953e-01 3.326941e-04 5.410859e-04 765 0 73 36.500 -8.71359281 1.045256e-01 5.209246e-01 3.239139e-04 5.268453e-04 775 0 74 37.000 -8.71362172 1.046875e-01 5.209534e-01 3.153606e-04 5.129708e-04 785 0 75 37.500 -8.71364977 1.048451e-01 5.209815e-01 3.070287e-04 4.994535e-04 795 0 76 38.000 -8.71367700 1.049986e-01 5.210089e-01 2.989126e-04 4.862846e-04 805 0 77 38.500 -8.71370343 1.051480e-01 5.210358e-01 2.910070e-04 4.734555e-04 815 0 78 39.000 -8.71372909 1.052935e-01 5.210621e-01 2.833067e-04 4.609579e-04 825 0 79 39.500 -8.71375399 1.054351e-01 5.210877e-01 2.758065e-04 4.487834e-04 835 0 80 40.000 -8.71377816 1.055730e-01 5.211128e-01 2.685014e-04 4.369243e-04 845 0 81 40.500 -8.71380163 1.057072e-01 5.211373e-01 2.613866e-04 4.253725e-04 855 0 82 41.000 -8.71382441 1.058378e-01 5.211613e-01 2.544572e-04 4.141205e-04 865 0 83 41.500 -8.71384653 1.059650e-01 5.211847e-01 2.477086e-04 4.031607e-04 875 0 84 42.000 -8.71386801 1.060888e-01 5.212075e-01 2.411362e-04 3.924859e-04 885 0 85 42.500 -8.71388886 1.062094e-01 5.212298e-01 2.347355e-04 3.820889e-04 895 0 86 43.000 -8.71390911 1.063267e-01 5.212516e-01 2.285023e-04 3.719627e-04 905 0 87 43.500 -8.71392878 1.064409e-01 5.212729e-01 2.224323e-04 3.621006e-04 915 0 88 44.000 -8.71394788 1.065521e-01 5.212937e-01 2.165212e-04 3.524959e-04 925 0 89 44.500 -8.71396642 1.066603e-01 5.213140e-01 2.107652e-04 3.431420e-04 935 0 90 45.000 -8.71398444 1.067657e-01 5.213338e-01 2.051601e-04 3.340326e-04 945 0 91 45.500 -8.71400193 1.068682e-01 5.213531e-01 1.997023e-04 3.251616e-04 955 0 92 46.000 -8.71401893 1.069681e-01 5.213720e-01 1.943878e-04 3.165229e-04 965 0 93 46.500 -8.71403544 1.070652e-01 5.213904e-01 1.892131e-04 3.081105e-04 975 0 94 47.000 -8.71405147 1.071598e-01 5.214084e-01 1.841745e-04 2.999187e-04 985 0 95 47.500 -8.71406705 1.072519e-01 5.214259e-01 1.792685e-04 2.919419e-04 995 0 96 48.000 -8.71408218 1.073415e-01 5.214430e-01 1.744918e-04 2.841746e-04 1005 0 97 48.500 -8.71409688 1.074287e-01 5.214597e-01 1.698410e-04 2.766114e-04 1015 0 98 49.000 -8.71411116 1.075136e-01 5.214760e-01 1.653128e-04 2.692471e-04 1025 0 99 49.500 -8.71412504 1.075962e-01 5.214918e-01 1.609042e-04 2.620766e-04 1035 0 100 50.000 -8.71413852 1.076767e-01 5.215073e-01 1.566119e-04 2.550949e-04 1045 0 101 50.500 -8.71415163 1.077550e-01 5.215224e-01 1.524331e-04 2.482971e-04 1055 0 102 51.000 -8.71416436 1.078312e-01 5.215372e-01 1.483647e-04 2.416786e-04 1065 0 103 51.500 -8.71417672 1.079053e-01 5.215515e-01 1.444039e-04 2.352346e-04 1075 0 104 52.000 -8.71418875 1.079775e-01 5.215655e-01 1.405479e-04 2.289608e-04 1085 0 105 52.500 -8.71420043 1.080478e-01 5.215792e-01 1.367940e-04 2.228526e-04 1095 0 106 53.000 -8.71421178 1.081161e-01 5.215925e-01 1.331395e-04 2.169058e-04 1105 0 107 53.500 -8.71422281 1.081827e-01 5.216055e-01 1.295818e-04 2.111162e-04 1115 0 108 54.000 -8.71423353 1.082475e-01 5.216182e-01 1.261184e-04 2.054798e-04 1125 0 109 54.500 -8.71424395 1.083105e-01 5.216305e-01 1.227469e-04 1.999925e-04 1135 0 110 55.000 -8.71425408 1.083719e-01 5.216425e-01 1.194649e-04 1.946505e-04 1145 0 111 55.500 -8.71426393 1.084316e-01 5.216543e-01 1.162699e-04 1.894500e-04 1155 0 112 56.000 -8.71427350 1.084897e-01 5.216657e-01 1.131598e-04 1.843873e-04 1165 0 113 56.500 -8.71428280 1.085463e-01 5.216768e-01 1.101324e-04 1.794589e-04 1175 0 114 57.000 -8.71429184 1.086013e-01 5.216877e-01 1.071853e-04 1.746612e-04 1185 0 115 57.500 -8.71430063 1.086549e-01 5.216983e-01 1.043166e-04 1.699907e-04 1195 0 116 58.000 -8.71430917 1.087070e-01 5.217086e-01 1.015242e-04 1.654443e-04 1205 0 117 58.500 -8.71431747 1.087578e-01 5.217186e-01 9.880610e-05 1.610186e-04 1215 0 118 59.000 -8.71432555 1.088072e-01 5.217284e-01 9.616032e-05 1.567104e-04 1225 0 119 59.500 -8.71433340 1.088552e-01 5.217380e-01 9.358496e-05 1.525168e-04 1235 0 120 60.000 -8.71434103 1.089020e-01 5.217473e-01 9.107819e-05 1.484347e-04 1245 0 121 60.500 -8.71434845 1.089476e-01 5.217563e-01 8.863818e-05 1.444611e-04 1255 0 122 61.000 -8.71435566 1.089919e-01 5.217651e-01 8.626320e-05 1.405932e-04 1265 0 123 61.500 -8.71436267 1.090350e-01 5.217737e-01 8.395151e-05 1.368283e-04 1275 0 124 62.000 -8.71436949 1.090769e-01 5.217821e-01 8.170145e-05 1.331636e-04 1285 0 125 62.500 -8.71437612 1.091178e-01 5.217903e-01 7.951140e-05 1.295965e-04 1295 0 126 63.000 -8.71438256 1.091575e-01 5.217982e-01 7.737977e-05 1.261245e-04 1305 0 127 63.500 -8.71438883 1.091962e-01 5.218060e-01 7.530502e-05 1.227449e-04 1315 0 128 64.000 -8.71439492 1.092339e-01 5.218135e-01 7.328565e-05 1.194555e-04 1325 0 129 64.500 -8.71440085 1.092705e-01 5.218209e-01 7.132018e-05 1.162537e-04 1335 0 130 65.000 -8.71440661 1.093061e-01 5.218280e-01 6.940720e-05 1.131374e-04 1345 0 131 65.500 -8.71441221 1.093408e-01 5.218350e-01 6.754531e-05 1.101041e-04 1355 0 132 66.000 -8.71441766 1.093746e-01 5.218418e-01 6.573316e-05 1.071519e-04 1365 0 133 66.500 -8.71442296 1.094075e-01 5.218484e-01 6.396943e-05 1.042784e-04 1375 0 134 67.000 -8.71442811 1.094394e-01 5.218548e-01 6.225285e-05 1.014816e-04 1385 0 135 67.500 -8.71443312 1.094706e-01 5.218611e-01 6.058215e-05 9.875955e-05 1395 0 136 68.000 -8.71443799 1.095008e-01 5.218672e-01 5.895612e-05 9.611018e-05 1405 0 137 68.500 -8.71444273 1.095303e-01 5.218732e-01 5.737359e-05 9.353159e-05 1415 0 138 69.000 -8.71444734 1.095590e-01 5.218790e-01 5.583338e-05 9.102192e-05 1425 0 139 69.500 -8.71445182 1.095869e-01 5.218846e-01 5.433438e-05 8.857932e-05 1435 0 140 70.000 -8.71445618 1.096141e-01 5.218901e-01 5.287549e-05 8.620202e-05 1445 0 141 70.500 -8.71446042 1.096405e-01 5.218955e-01 5.145565e-05 8.388830e-05 1455 0 142 71.000 -8.71446454 1.096662e-01 5.219007e-01 5.007381e-05 8.163645e-05 1465 0 143 71.500 -8.71446855 1.096912e-01 5.219058e-01 4.872897e-05 7.944485e-05 1475 0 144 72.000 -8.71447245 1.097156e-01 5.219107e-01 4.742015e-05 7.731188e-05 1485 0 145 72.500 -8.71447624 1.097393e-01 5.219155e-01 4.614637e-05 7.523599e-05 1495 0 146 73.000 -8.71447993 1.097624e-01 5.219202e-01 4.490672e-05 7.321566e-05 1505 0 147 73.500 -8.71448352 1.097848e-01 5.219248e-01 4.370027e-05 7.124942e-05 1515 0 148 74.000 -8.71448701 1.098067e-01 5.219292e-01 4.252615e-05 6.933582e-05 1525 0 149 74.500 -8.71449040 1.098279e-01 5.219335e-01 4.138350e-05 6.747346e-05 1535 0 150 75.000 -8.71449370 1.098486e-01 5.219377e-01 4.027147e-05 6.566099e-05 1545 0 151 75.500 -8.71449691 1.098687e-01 5.219418e-01 3.918925e-05 6.389706e-05 1555 0 152 76.000 -8.71450004 1.098883e-01 5.219458e-01 3.813605e-05 6.218040e-05 1565 0 153 76.500 -8.71450308 1.099074e-01 5.219497e-01 3.711108e-05 6.050973e-05 1575 0 154 77.000 -8.71450603 1.099259e-01 5.219535e-01 3.611360e-05 5.888384e-05 1585 0 155 77.500 -8.71450891 1.099440e-01 5.219572e-01 3.514287e-05 5.730152e-05 1595 0 156 78.000 -8.71451170 1.099616e-01 5.219608e-01 3.419818e-05 5.576163e-05 1605 0 157 78.500 -8.71451442 1.099786e-01 5.219642e-01 3.327883e-05 5.426301e-05 1615 0 158 79.000 -8.71451707 1.099953e-01 5.219676e-01 3.238414e-05 5.280458e-05 1625 0 159 79.500 -8.71451964 1.100115e-01 5.219710e-01 3.151346e-05 5.138526e-05 1635 0 160 80.000 -8.71452214 1.100272e-01 5.219742e-01 3.066615e-05 5.000401e-05 1645 0 161 80.500 -8.71452458 1.100426e-01 5.219773e-01 2.984157e-05 4.865981e-05 1655 0 162 81.000 -8.71452695 1.100575e-01 5.219804e-01 2.903913e-05 4.735167e-05 1665 0 163 81.500 -8.71452925 1.100720e-01 5.219833e-01 2.825823e-05 4.607862e-05 1675 0 164 82.000 -8.71453150 1.100861e-01 5.219862e-01 2.749829e-05 4.483974e-05 1685 0 165 82.500 -8.71453368 1.100999e-01 5.219890e-01 2.675875e-05 4.363410e-05 1695 0 166 83.000 -8.71453580 1.101132e-01 5.219918e-01 2.603907e-05 4.246081e-05 1705 0 167 83.500 -8.71453786 1.101263e-01 5.219944e-01 2.533872e-05 4.131902e-05 1715 0 168 84.000 -8.71453987 1.101389e-01 5.219970e-01 2.465717e-05 4.020788e-05 1725 0 169 84.500 -8.71454182 1.101512e-01 5.219996e-01 2.399393e-05 3.912657e-05 1735 0 170 85.000 -8.71454372 1.101632e-01 5.220020e-01 2.334850e-05 3.807429e-05 1745 0 171 85.500 -8.71454557 1.101749e-01 5.220044e-01 2.272041e-05 3.705027e-05 1755 0 172 86.000 -8.71454737 1.101863e-01 5.220068e-01 2.210919e-05 3.605374e-05 1765 0 173 86.500 -8.71454912 1.101973e-01 5.220090e-01 2.151440e-05 3.508398e-05 1775 0 174 87.000 -8.71455082 1.102081e-01 5.220112e-01 2.093558e-05 3.414026e-05 1785 0 175 87.500 -8.71455248 1.102185e-01 5.220134e-01 2.037232e-05 3.322189e-05 1795 0 176 88.000 -8.71455409 1.102287e-01 5.220155e-01 1.982419e-05 3.232819e-05 1805 0 177 88.500 -8.71455566 1.102386e-01 5.220175e-01 1.929079e-05 3.145850e-05 1815 0 178 89.000 -8.71455718 1.102483e-01 5.220195e-01 1.877173e-05 3.061217e-05 1825 0 179 89.500 -8.71455866 1.102577e-01 5.220214e-01 1.826662e-05 2.978858e-05 1835 0 180 90.000 -8.71456011 1.102668e-01 5.220233e-01 1.777508e-05 2.898713e-05 1845 0 181 90.500 -8.71456151 1.102757e-01 5.220251e-01 1.729676e-05 2.820721e-05 1855 0 182 91.000 -8.71456288 1.102843e-01 5.220269e-01 1.683130e-05 2.744824e-05 1865 0 183 91.500 -8.71456420 1.102927e-01 5.220286e-01 1.637834e-05 2.670968e-05 1875 0 184 92.000 -8.71456550 1.103009e-01 5.220303e-01 1.593757e-05 2.599097e-05 1885 0 185 92.500 -8.71456676 1.103089e-01 5.220320e-01 1.550865e-05 2.529157e-05 1895 0 186 93.000 -8.71456798 1.103166e-01 5.220336e-01 1.509126e-05 2.461098e-05 1905 0 187 93.500 -8.71456917 1.103242e-01 5.220351e-01 1.468509e-05 2.394868e-05 1915 0 188 94.000 -8.71457033 1.103315e-01 5.220366e-01 1.428984e-05 2.330418e-05 1925 0 189 94.500 -8.71457145 1.103387e-01 5.220381e-01 1.390523e-05 2.267702e-05 1935 0 190 95.000 -8.71457255 1.103456e-01 5.220395e-01 1.353095e-05 2.206671e-05 1945 0 191 95.500 -8.71457362 1.103524e-01 5.220409e-01 1.316674e-05 2.147282e-05 1955 0 192 96.000 -8.71457466 1.103590e-01 5.220423e-01 1.281233e-05 2.089489e-05 1965 0 193 96.500 -8.71457567 1.103654e-01 5.220436e-01 1.246745e-05 2.033251e-05 1975 0 194 97.000 -8.71457665 1.103716e-01 5.220449e-01 1.213185e-05 1.978525e-05 1985 0 195 97.500 -8.71457760 1.103777e-01 5.220461e-01 1.180527e-05 1.925270e-05 1995 0 196 98.000 -8.71457853 1.103836e-01 5.220473e-01 1.148748e-05 1.873448e-05 2005 0 197 98.500 -8.71457944 1.103893e-01 5.220485e-01 1.117824e-05 1.823020e-05 2015 0 198 99.000 -8.71458032 1.103949e-01 5.220497e-01 1.087732e-05 1.773948e-05 2025 0 199 99.500 -8.71458118 1.104003e-01 5.220508e-01 1.058449e-05 1.726196e-05 2035 0 200 100.000 -8.71458201 1.104056e-01 5.220519e-01 1.029954e-05 1.679728e-05 2045 0 201 100.500 -8.71458282 1.104108e-01 5.220530e-01 1.002226e-05 1.634511e-05 2055 0 202 101.000 -8.71458361 1.104158e-01 5.220540e-01 9.752433e-06 1.590509e-05 2065 0 203 101.500 -8.71458438 1.104207e-01 5.220550e-01 9.489870e-06 1.547692e-05 2075 0 204 102.000 -8.71458512 1.104254e-01 5.220560e-01 9.234372e-06 1.506026e-05 2085 0 205 102.500 -8.71458585 1.104300e-01 5.220569e-01 8.985750e-06 1.465482e-05 2095 0 206 103.000 -8.71458656 1.104345e-01 5.220579e-01 8.743817e-06 1.426028e-05 2105 0 207 103.500 -8.71458725 1.104389e-01 5.220588e-01 8.508395e-06 1.387636e-05 2115 0 208 104.000 -8.71458791 1.104431e-01 5.220596e-01 8.279308e-06 1.350277e-05 2125 0 209 104.500 -8.71458857 1.104473e-01 5.220605e-01 8.056386e-06 1.313923e-05 2135 0 210 105.000 -8.71458920 1.104513e-01 5.220613e-01 7.839463e-06 1.278547e-05 2145 0 211 105.500 -8.71458982 1.104552e-01 5.220621e-01 7.628379e-06 1.244123e-05 2155 0 212 106.000 -8.71459042 1.104590e-01 5.220629e-01 7.422975e-06 1.210626e-05 2165 0 213 106.500 -8.71459100 1.104627e-01 5.220637e-01 7.223100e-06 1.178030e-05 2175 0 214 107.000 -8.71459157 1.104663e-01 5.220644e-01 7.028604e-06 1.146311e-05 2185 0 215 107.500 -8.71459212 1.104699e-01 5.220652e-01 6.839344e-06 1.115446e-05 2195 0 216 108.000 -8.71459266 1.104733e-01 5.220659e-01 6.655177e-06 1.085412e-05 2205 0 217 108.500 -8.71459318 1.104766e-01 5.220666e-01 6.475968e-06 1.056185e-05 2215 0 218 109.000 -8.71459369 1.104798e-01 5.220672e-01 6.301582e-06 1.027746e-05 2225 0 219 109.500 -8.71459419 1.104830e-01 5.220679e-01 6.131891e-06 1.000072e-05 2235 0 220 110.000 -8.71459467 1.104861e-01 5.220685e-01 5.966767e-06 9.731425e-06 2245 0 221 110.500 -8.71459514 1.104890e-01 5.220691e-01 5.806088e-06 9.469381e-06 2255 0 222 111.000 -8.71459559 1.104919e-01 5.220697e-01 5.649735e-06 9.214391e-06 2265 0 223 111.500 -8.71459604 1.104948e-01 5.220703e-01 5.497591e-06 8.966264e-06 2275 0 224 112.000 -8.71459647 1.104975e-01 5.220709e-01 5.349542e-06 8.724816e-06 2285 0 225 112.500 -8.71459689 1.105002e-01 5.220714e-01 5.205479e-06 8.489868e-06 2295 0 226 113.000 -8.71459730 1.105028e-01 5.220720e-01 5.065295e-06 8.261244e-06 2305 0 227 113.500 -8.71459770 1.105053e-01 5.220725e-01 4.928885e-06 8.038775e-06 2315 0 228 114.000 -8.71459808 1.105078e-01 5.220730e-01 4.796147e-06 7.822294e-06 2325 0 229 114.500 -8.71459846 1.105102e-01 5.220735e-01 4.666982e-06 7.611642e-06 2335 0 230 115.000 -8.71459883 1.105125e-01 5.220740e-01 4.541296e-06 7.406660e-06 2345 0 231 115.500 -8.71459918 1.105148e-01 5.220745e-01 4.418993e-06 7.207197e-06 2355 0 232 116.000 -8.71459953 1.105170e-01 5.220749e-01 4.299983e-06 7.013104e-06 2365 0 233 116.500 -8.71459987 1.105191e-01 5.220754e-01 4.184177e-06 6.824236e-06 2375 0 234 117.000 -8.71460020 1.105212e-01 5.220758e-01 4.071490e-06 6.640453e-06 2385 0 235 117.500 -8.71460052 1.105233e-01 5.220762e-01 3.961836e-06 6.461619e-06 2395 0 236 118.000 -8.71460083 1.105253e-01 5.220766e-01 3.855135e-06 6.287599e-06 2405 0 237 118.500 -8.71460113 1.105272e-01 5.220770e-01 3.751307e-06 6.118264e-06 2415 0 238 119.000 -8.71460142 1.105291e-01 5.220774e-01 3.650275e-06 5.953489e-06 2425 0 239 119.500 -8.71460171 1.105309e-01 5.220778e-01 3.551963e-06 5.793150e-06 2435 0 240 120.000 -8.71460199 1.105327e-01 5.220782e-01 3.456299e-06 5.637129e-06 2445 0 241 120.500 -8.71460226 1.105344e-01 5.220785e-01 3.363210e-06 5.485308e-06 2455 0 242 121.000 -8.71460252 1.105361e-01 5.220789e-01 3.272628e-06 5.337576e-06 2465 0 243 121.500 -8.71460278 1.105377e-01 5.220792e-01 3.184486e-06 5.193821e-06 2475 0 244 122.000 -8.71460303 1.105393e-01 5.220795e-01 3.098716e-06 5.053937e-06 2485 0 245 122.500 -8.71460327 1.105408e-01 5.220798e-01 3.015257e-06 4.917820e-06 2495 0 246 123.000 -8.71460351 1.105424e-01 5.220802e-01 2.934045e-06 4.785368e-06 2505 0 247 123.500 -8.71460374 1.105438e-01 5.220805e-01 2.855020e-06 4.656483e-06 2515 0 248 124.000 -8.71460397 1.105452e-01 5.220808e-01 2.778122e-06 4.531068e-06 2525 0 249 124.500 -8.71460418 1.105466e-01 5.220810e-01 2.703296e-06 4.409031e-06 2535 0 250 125.000 -8.71460440 1.105480e-01 5.220813e-01 2.630485e-06 4.290279e-06 2545 0 251 125.500 -8.71460460 1.105493e-01 5.220816e-01 2.559634e-06 4.174726e-06 2555 0 252 126.000 -8.71460480 1.105506e-01 5.220819e-01 2.490692e-06 4.062284e-06 2565 0 253 126.500 -8.71460500 1.105518e-01 5.220821e-01 2.423606e-06 3.952871e-06 2575 0 254 127.000 -8.71460519 1.105530e-01 5.220824e-01 2.358327e-06 3.846403e-06 2585 0 255 127.500 -8.71460537 1.105542e-01 5.220826e-01 2.294806e-06 3.742803e-06 2595 0 256 128.000 -8.71460555 1.105554e-01 5.220829e-01 2.232996e-06 3.641993e-06 2605 0 257 128.500 -8.71460573 1.105565e-01 5.220831e-01 2.172850e-06 3.543898e-06 2615 0 258 129.000 -8.71460590 1.105576e-01 5.220833e-01 2.114324e-06 3.448444e-06 2625 0 259 129.500 -8.71460606 1.105586e-01 5.220835e-01 2.057374e-06 3.355561e-06 2635 0 260 130.000 -8.71460623 1.105596e-01 5.220837e-01 2.001958e-06 3.265180e-06 2645 0 261 130.500 -8.71460638 1.105607e-01 5.220840e-01 1.948035e-06 3.177233e-06 2655 0 262 131.000 -8.71460654 1.105616e-01 5.220842e-01 1.895564e-06 3.091654e-06 2665 0 263 131.500 -8.71460668 1.105626e-01 5.220843e-01 1.844506e-06 3.008380e-06 2675 0 264 132.000 -8.71460683 1.105635e-01 5.220845e-01 1.794823e-06 2.927348e-06 2685 0 265 132.500 -8.71460697 1.105644e-01 5.220847e-01 1.746478e-06 2.848499e-06 2695 0 266 133.000 -8.71460711 1.105653e-01 5.220849e-01 1.699435e-06 2.771774e-06 2705 0 267 133.500 -8.71460724 1.105661e-01 5.220851e-01 1.653659e-06 2.697115e-06 2715 0 268 134.000 -8.71460737 1.105669e-01 5.220853e-01 1.609116e-06 2.624466e-06 2725 0 269 134.500 -8.71460750 1.105677e-01 5.220854e-01 1.565773e-06 2.553774e-06 2735 0 270 135.000 -8.71460762 1.105685e-01 5.220856e-01 1.523597e-06 2.484987e-06 2745 0 271 135.500 -8.71460774 1.105693e-01 5.220857e-01 1.482557e-06 2.418052e-06 2755 0 272 136.000 -8.71460785 1.105700e-01 5.220859e-01 1.442623e-06 2.352919e-06 2765 0 273 136.500 -8.71460797 1.105708e-01 5.220860e-01 1.403764e-06 2.289541e-06 2775 0 274 137.000 -8.71460808 1.105715e-01 5.220862e-01 1.365952e-06 2.227870e-06 2785 0 275 137.500 -8.71460819 1.105721e-01 5.220863e-01 1.329158e-06 2.167860e-06 2795 0 276 138.000 -8.71460829 1.105728e-01 5.220865e-01 1.293355e-06 2.109466e-06 2805 0 277 138.500 -8.71460839 1.105734e-01 5.220866e-01 1.258517e-06 2.052645e-06 2815 0 278 139.000 -8.71460849 1.105741e-01 5.220867e-01 1.224616e-06 1.997354e-06 2825 0 279 139.500 -8.71460859 1.105747e-01 5.220869e-01 1.191629e-06 1.943553e-06 2835 0 280 140.000 -8.71460868 1.105753e-01 5.220870e-01 1.159531e-06 1.891200e-06 2845 0 281 140.500 -8.71460877 1.105759e-01 5.220871e-01 1.128297e-06 1.840258e-06 2855 0 282 141.000 -8.71460886 1.105764e-01 5.220872e-01 1.097904e-06 1.790688e-06 2865 0 283 141.500 -8.71460894 1.105770e-01 5.220873e-01 1.068330e-06 1.742453e-06 2875 0 284 142.000 -8.71460903 1.105775e-01 5.220874e-01 1.039553e-06 1.695517e-06 2885 0 285 142.500 -8.71460911 1.105780e-01 5.220876e-01 1.011550e-06 1.649845e-06 2895 0 286 143.000 -8.71460919 1.105785e-01 5.220877e-01 9.843021e-07 1.605404e-06 2905 0 287 143.500 -8.71460927 1.105790e-01 5.220878e-01 9.577879e-07 1.562159e-06 2915 0 288 144.000 -8.71460934 1.105795e-01 5.220879e-01 9.319879e-07 1.520080e-06 2925 0 289 144.500 -8.71460941 1.105800e-01 5.220880e-01 9.068828e-07 1.479133e-06 2935 0 290 145.000 -8.71460949 1.105804e-01 5.220880e-01 8.824540e-07 1.439290e-06 2945 0 291 145.500 -8.71460955 1.105809e-01 5.220881e-01 8.586831e-07 1.400520e-06 2955 0 292 146.000 -8.71460962 1.105813e-01 5.220882e-01 8.355526e-07 1.362794e-06 2965 0 293 146.500 -8.71460969 1.105817e-01 5.220883e-01 8.130451e-07 1.326084e-06 2975 0 294 147.000 -8.71460975 1.105821e-01 5.220884e-01 7.911438e-07 1.290363e-06 2985 0 295 147.500 -8.71460981 1.105825e-01 5.220885e-01 7.698325e-07 1.255605e-06 2995 0 296 148.000 -8.71460987 1.105829e-01 5.220886e-01 7.490952e-07 1.221782e-06 3005 0 297 148.500 -8.71460993 1.105833e-01 5.220886e-01 7.289165e-07 1.188871e-06 3015 0 298 149.000 -8.71460999 1.105836e-01 5.220887e-01 7.092814e-07 1.156846e-06 3025 0 299 149.500 -8.71461005 1.105840e-01 5.220888e-01 6.901751e-07 1.125683e-06 3035 0 300 150.000 -8.71461010 1.105843e-01 5.220889e-01 6.715835e-07 1.095360e-06 3045 0 301 150.500 -8.71461015 1.105847e-01 5.220889e-01 6.534927e-07 1.065854e-06 3055 0 302 151.000 -8.71461020 1.105850e-01 5.220890e-01 6.358892e-07 1.037143e-06 3065 0 303 151.500 -8.71461025 1.105853e-01 5.220891e-01 6.187599e-07 1.009205e-06 3075 0 304 152.000 -8.71461030 1.105856e-01 5.220891e-01 6.020919e-07 9.820195e-07 3085 0 305 152.500 -8.71461035 1.105859e-01 5.220892e-01 5.858730e-07 9.555663e-07 3095 0 306 153.000 -8.71461039 1.105862e-01 5.220892e-01 5.700909e-07 9.298257e-07 3105 0 307 153.500 -8.71461044 1.105865e-01 5.220893e-01 5.547340e-07 9.047784e-07 3115 0 308 154.000 -8.71461048 1.105868e-01 5.220894e-01 5.397907e-07 8.804059e-07 3125 0 309 154.500 -8.71461053 1.105871e-01 5.220894e-01 5.252500e-07 8.566898e-07 3135 0 310 155.000 -8.71461057 1.105873e-01 5.220895e-01 5.111009e-07 8.336126e-07 3145 0 Trying to perform DMD.... Snapshot from smin 15.0 s_end 20.0 ds 0.5 fullrank 8 checking full Sigma[1:6]... 4.4e-01 3.1e-03 1.6e-06 2.8e-08 1.5e-10 1.7e-12 singular values 4.4e-01 3.1e-03 1.6e-06 2.8e-08 1.5e-10 1.7e-12 eigenvalues of Atilde [0.561222422676189, 0.6165709849013116, 0.7201012836800604, 0.9506015365456886, 0.972575200595801, 1.0000000075241215] stationary? may be... true ────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 23.0s / 0.0% 208MiB / 0.3% Section ncalls time %tot avg alloc %tot avg ────────────────────────────────────────────────────────────────────── full SVD 1 416μs 53.0% 416μs 273KiB 51.3% 273KiB SVD(full) 1 370μs 47.0% 370μs 259KiB 48.7% 259KiB ────────────────────────────────────────────────────────────────────── s = 30.00 ||x'-x|| 2.3108e-04 5.5391e-05 s = 50.00 ||x'-x|| 3.8893e-04 1.0155e-04 s = 30.0 DMD: Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.46 KB dictHOB 0.46 KB target: He4 Ref. => Z=2 N=2 E: -5.872267 = E1b 46.65735 + E2b -52.52961 ( -7.298 -36.942 -8.289), + E3b 0.00000 EMP2 -2.54240 1b -0.00000 pp -0.03408 pn -2.48016 nn -0.02817 EMP3 -0.11250 pp 0.030 hh -0.349 ph 0.207 E_HF -5.87227 E_MBPT(3) = -8.5272 Eexp: -28.296 parameters/optional_parameters_forDMD.jl is used for IMSRG parameters in parameters/optional_parameters_forDMD.jl will be used. def-by-run d6j_lj done! 240 step: s E0 ||Omega_1|| ||Omega_2|| ||Eta_1|| ||Eta_2|| Ncomm. nwritten 0 0.000 -5.87226696 0.000000e+00 0.000000e+00 6.477848e-18 5.224524e-01 0 0 1 0.500 -7.94881314 3.238924e-18 2.612262e-01 2.279622e-02 2.381511e-01 8 0 IMSRG from file flowOmega/omega_dmd_vec_473He4_s30.00.h5 En(s=30.00;DMD) = -8.713035538493438 s = 50.0 DMD: Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.46 KB dictHOB 0.46 KB target: He4 Ref. => Z=2 N=2 E: -5.872267 = E1b 46.65735 + E2b -52.52961 ( -7.298 -36.942 -8.289), + E3b 0.00000 EMP2 -2.54240 1b -0.00000 pp -0.03408 pn -2.48016 nn -0.02817 EMP3 -0.11250 pp 0.030 hh -0.349 ph 0.207 E_HF -5.87227 E_MBPT(3) = -8.5272 Eexp: -28.296 parameters/optional_parameters_forDMD.jl is used for IMSRG parameters in parameters/optional_parameters_forDMD.jl will be used. def-by-run d6j_lj done! 240 step: s E0 ||Omega_1|| ||Omega_2|| ||Eta_1|| ||Eta_2|| Ncomm. nwritten 0 0.000 -5.87226696 0.000000e+00 0.000000e+00 6.477848e-18 5.224524e-01 0 0 1 0.500 -7.94881314 3.238924e-18 2.612262e-01 2.279622e-02 2.381511e-01 8 0 IMSRG from file flowOmega/omega_dmd_vec_473He4_s50.00.h5 En(s=50.00;DMD) = -8.714005571195361 Be8 Z,N=(4,4) c(2,2) v(2,2) mdim: 51 ( 1.71 ) pnrank 1: [1, 2, 1, 2, 1, 11] -1.740908 [1, 2, 1, 2, 2, 29] -2.891015 [2, 2, 1, 2, 2, 30] 1.61493 [1, 2, 2, 2, 2, 30] 1.61493 [2, 2, 2, 2, 2, 31] -2.530268 [1, 1, 1, 1, 0, 32] -0.923452 [2, 2, 1, 1, 0, 33] -3.604288 [1, 1, 2, 2, 0, 33] -3.604288 [2, 2, 2, 2, 0, 34] -3.911419 pnrank 2: [3, 3, 3, 3, 0, 12] -1.485811 [4, 4, 3, 3, 0, 13] -3.767531 [3, 3, 4, 4, 0, 13] -3.767531 [4, 4, 4, 4, 0, 14] -4.588577 [3, 4, 3, 4, 2, 15] -3.435722 [4, 4, 3, 4, 2, 16] 1.682983 [3, 4, 4, 4, 2, 16] 1.682983 [4, 4, 4, 4, 2, 17] -3.04968 [3, 4, 3, 4, 1, 18] -2.180926 pnrank 3: [1, 3, 1, 3, 0, 1] -1.770043 [2, 4, 1, 3, 0, 2] -3.895014 [1, 3, 2, 4, 0, 2] -3.895014 [2, 4, 2, 4, 0, 3] -4.834416 [1, 4, 1, 4, 2, 4] -4.728354 [2, 3, 1, 4, 2, 5] -1.180262 [1, 4, 2, 3, 2, 5] -1.180262 [2, 4, 1, 4, 2, 6] 1.225047 [1, 4, 2, 4, 2, 6] 1.225047 [2, 3, 2, 3, 2, 7] -4.733337 [2, 4, 2, 3, 2, 8] -1.228383 [2, 3, 2, 4, 2, 8] -1.228383 [2, 4, 2, 4, 2, 9] -3.112495 [2, 4, 2, 4, 3, 10] -5.160327 [1, 3, 1, 3, 1, 19] -2.560999 [1, 4, 1, 3, 1, 20] -2.034375 [1, 3, 1, 4, 1, 20] -2.034375 [2, 3, 1, 3, 1, 21] 2.039864 [1, 3, 2, 3, 1, 21] 2.039864 [2, 4, 1, 3, 1, 22] 0.766191 [1, 3, 2, 4, 1, 22] 0.766191 [1, 4, 1, 4, 1, 23] -4.127823 [2, 3, 1, 4, 1, 24] 2.044854 [1, 4, 2, 3, 1, 24] 2.044854 [2, 4, 1, 4, 1, 25] -2.619293 [1, 4, 2, 4, 1, 25] -2.619293 [2, 3, 2, 3, 1, 26] -4.148153 [2, 4, 2, 3, 1, 27] 2.618685 [2, 3, 2, 4, 1, 27] 2.618685 [2, 4, 2, 4, 1, 28] -2.197045 labels[i] [1, 3, 1, 3, 0, 1] ME -1.770043 labels[i] [2, 4, 1, 3, 0, 2] ME -3.895014 labels[i] [1, 3, 2, 4, 0, 2] ME -3.895014 labels[i] [2, 4, 2, 4, 0, 3] ME -4.834416 labels[i] [1, 4, 1, 4, 2, 4] ME -4.728354 labels[i] [2, 3, 1, 4, 2, 5] ME -1.180262 labels[i] [1, 4, 2, 3, 2, 5] ME -1.180262 labels[i] [2, 4, 1, 4, 2, 6] ME 1.225047 labels[i] [1, 4, 2, 4, 2, 6] ME 1.225047 labels[i] [2, 3, 2, 3, 2, 7] ME -4.733337 labels[i] [2, 4, 2, 3, 2, 8] ME -1.228383 labels[i] [2, 3, 2, 4, 2, 8] ME -1.228383 labels[i] [2, 4, 2, 4, 2, 9] ME -3.112495 labels[i] [2, 4, 2, 4, 3, 10] ME -5.160327 labels[i] [1, 3, 1, 3, 1, 19] ME -2.560999 labels[i] [1, 4, 1, 3, 1, 20] ME -2.034375 labels[i] [1, 3, 1, 4, 1, 20] ME -2.034375 labels[i] [2, 3, 1, 3, 1, 21] ME 2.039864 labels[i] [1, 3, 2, 3, 1, 21] ME 2.039864 labels[i] [2, 4, 1, 3, 1, 22] ME 0.766191 labels[i] [1, 3, 2, 4, 1, 22] ME 0.766191 labels[i] [1, 4, 1, 4, 1, 23] ME -4.127823 labels[i] [2, 3, 1, 4, 1, 24] ME 2.044854 labels[i] [1, 4, 2, 3, 1, 24] ME 2.044854 labels[i] [2, 4, 1, 4, 1, 25] ME -2.619293 labels[i] [1, 4, 2, 4, 1, 25] ME -2.619293 labels[i] [2, 3, 2, 3, 1, 26] ME -4.148153 labels[i] [2, 4, 2, 3, 1, 27] ME 2.618685 labels[i] [2, 3, 2, 4, 1, 27] ME 2.618685 labels[i] [2, 4, 2, 4, 1, 28] ME -2.197045 J [0.0, 2.0] En. -10.7202 -8.4098 Ex. 0.0000 2.3104 Be8 Z,N=(4,4) c(2,2) v(2,2) mdim: 51 ( 1.71 ) pnrank 1: [1, 1, 1, 1, 0, 1] 0.244 [2, 2, 1, 1, 0, 2] -5.0526 [1, 1, 2, 2, 0, 2] -5.0526 [1, 2, 1, 2, 1, 3] 0.7344 [1, 2, 1, 2, 2, 4] -1.1443 [2, 2, 1, 2, 2, 5] 1.7423 [1, 2, 2, 2, 2, 5] 1.7423 [2, 2, 2, 2, 0, 6] -3.3287 [2, 2, 2, 2, 2, 7] 0.0878 pnrank 2: [3, 3, 3, 3, 0, 8] 0.244 [4, 4, 3, 3, 0, 9] -5.0526 [3, 3, 4, 4, 0, 9] -5.0526 [3, 4, 3, 4, 1, 10] 0.7344 [3, 4, 3, 4, 2, 11] -1.1443 [4, 4, 3, 4, 2, 12] 1.7423 [3, 4, 4, 4, 2, 12] 1.7423 [4, 4, 4, 4, 0, 13] -3.3287 [4, 4, 4, 4, 2, 14] 0.0878 pnrank 3: [1, 3, 1, 3, 0, 15] 0.244 [1, 3, 1, 3, 1, 16] -4.29215 [1, 4, 1, 3, 1, 17] -0.85185 [1, 3, 1, 4, 1, 17] -0.85185 [2, 3, 1, 3, 1, 18] 0.85185 [1, 3, 2, 3, 1, 18] 0.85185 [2, 4, 1, 3, 0, 19] -5.0526 [1, 3, 2, 4, 0, 19] -5.0526 [2, 4, 1, 3, 1, 20] 1.7698 [1, 3, 2, 4, 1, 20] 1.7698 [1, 4, 1, 4, 1, 21] -2.91415 [1, 4, 2, 3, 1, 22] 3.64855 [2, 3, 1, 4, 1, 22] 3.64855 [2, 3, 2, 3, 1, 23] -2.91415 [1, 4, 1, 4, 2, 24] -2.6011 [1, 4, 2, 3, 2, 25] -1.4568 [2, 3, 1, 4, 2, 25] -1.4568 [2, 3, 2, 3, 2, 26] -2.6011 [2, 4, 1, 4, 1, 27] -2.2667 [1, 4, 2, 4, 1, 27] -2.2667 [2, 4, 2, 3, 1, 28] 2.2667 [2, 3, 2, 4, 1, 28] 2.2667 [2, 4, 1, 4, 2, 29] 1.23199 [1, 4, 2, 4, 2, 29] 1.23199 [2, 4, 2, 3, 2, 30] -1.23199 [2, 3, 2, 4, 2, 30] -1.23199 [2, 4, 2, 4, 0, 31] -3.3287 [2, 4, 2, 4, 1, 32] -3.4362 [2, 4, 2, 4, 2, 33] 0.0878 [2, 4, 2, 4, 3, 34] -7.2668 labels[i] [1, 3, 1, 3, 0, 15] ME 0.244 labels[i] [1, 3, 1, 3, 1, 16] ME -4.29215 labels[i] [1, 4, 1, 3, 1, 17] ME -0.85185 labels[i] [1, 3, 1, 4, 1, 17] ME -0.85185 labels[i] [2, 3, 1, 3, 1, 18] ME 0.85185 labels[i] [1, 3, 2, 3, 1, 18] ME 0.85185 labels[i] [2, 4, 1, 3, 0, 19] ME -5.0526 labels[i] [1, 3, 2, 4, 0, 19] ME -5.0526 labels[i] [2, 4, 1, 3, 1, 20] ME 1.7698 labels[i] [1, 3, 2, 4, 1, 20] ME 1.7698 labels[i] [1, 4, 1, 4, 1, 21] ME -2.91415 labels[i] [1, 4, 2, 3, 1, 22] ME 3.64855 labels[i] [2, 3, 1, 4, 1, 22] ME 3.64855 labels[i] [2, 3, 2, 3, 1, 23] ME -2.91415 labels[i] [1, 4, 1, 4, 2, 24] ME -2.6011 labels[i] [1, 4, 2, 3, 2, 25] ME -1.4568 labels[i] [2, 3, 1, 4, 2, 25] ME -1.4568 labels[i] [2, 3, 2, 3, 2, 26] ME -2.6011 labels[i] [2, 4, 1, 4, 1, 27] ME -2.2667 labels[i] [1, 4, 2, 4, 1, 27] ME -2.2667 labels[i] [2, 4, 2, 3, 1, 28] ME 2.2667 labels[i] [2, 3, 2, 4, 1, 28] ME 2.2667 labels[i] [2, 4, 1, 4, 2, 29] ME 1.23199 labels[i] [1, 4, 2, 4, 2, 29] ME 1.23199 labels[i] [2, 4, 2, 3, 2, 30] ME -1.23199 labels[i] [2, 3, 2, 4, 2, 30] ME -1.23199 labels[i] [2, 4, 2, 4, 0, 31] ME -3.3287 labels[i] [2, 4, 2, 4, 1, 32] ME -3.4362 labels[i] [2, 4, 2, 4, 2, 33] ME 0.0878 labels[i] [2, 4, 2, 4, 3, 34] ME -7.2668 J [0.0, 2.0, 4.0, 2.0, 1.0, 2.0, 3.0, 1.0, 0.0, 4.0] En. -31.1194 -27.2997 -19.1618 -18.2487 -16.7222 -14.9253 -14.5169 -14.0171 -13.9510 -13.4781 Ex. 0.0000 3.8197 11.9576 12.8707 14.3972 16.1941 16.6025 17.1023 17.1684 17.6413 O18 Z,N=(8,10) c(8,8) v(0,2) mdim: 10 ( 1.00 ) pnrank 1: [1, 1, 1, 1, 0, 1] -1.6913 [2, 2, 1, 1, 0, 2] -1.015 [1, 1, 2, 2, 0, 2] -1.015 [3, 3, 1, 1, 0, 3] -1.5602 [1, 1, 3, 3, 0, 3] -1.5602 [1, 2, 1, 2, 1, 4] 0.5158 [1, 2, 1, 2, 2, 5] -0.3034 [1, 3, 1, 2, 2, 6] -1.6131 [1, 2, 1, 3, 2, 6] -1.6131 [2, 2, 1, 2, 2, 7] -0.3494 [1, 2, 2, 2, 2, 7] -0.3494 [2, 3, 1, 2, 1, 8] -0.0456 [1, 2, 2, 3, 1, 8] -0.0456 [2, 3, 1, 2, 2, 9] 0.3713 [1, 2, 2, 3, 2, 9] 0.3713 [3, 3, 1, 2, 2, 10] -0.8866 [1, 2, 3, 3, 2, 10] -0.8866 [1, 3, 1, 3, 2, 11] -0.9405 [1, 3, 1, 3, 3, 12] 0.6841 [2, 2, 1, 3, 2, 13] -0.3173 [1, 3, 2, 2, 2, 13] -0.3173 [2, 3, 1, 3, 2, 14] 0.3147 [1, 3, 2, 3, 2, 14] 0.3147 [2, 3, 1, 3, 3, 15] 0.5525 [1, 3, 2, 3, 3, 15] 0.5525 [3, 3, 1, 3, 2, 16] -0.9317 [1, 3, 3, 3, 2, 16] -0.9317 [2, 2, 2, 2, 0, 17] -1.8992 [2, 2, 2, 2, 2, 18] -0.0974 [2, 3, 2, 2, 2, 19] 0.5032 [2, 2, 2, 3, 2, 19] 0.5032 [3, 3, 2, 2, 0, 20] -3.1025 [2, 2, 3, 3, 0, 20] -3.1025 [3, 3, 2, 2, 2, 21] -1.2187 [2, 2, 3, 3, 2, 21] -1.2187 [2, 3, 2, 3, 1, 22] 0.6556 [2, 3, 2, 3, 2, 23] -0.1545 [2, 3, 2, 3, 3, 24] 0.7673 [2, 3, 2, 3, 4, 25] -1.4447 [3, 3, 2, 3, 2, 26] 0.2137 [2, 3, 3, 3, 2, 26] 0.2137 [3, 3, 2, 3, 4, 27] 1.3349 [2, 3, 3, 3, 4, 27] 1.3349 [3, 3, 3, 3, 0, 28] -2.5598 [3, 3, 3, 3, 2, 29] -1.0007 [3, 3, 3, 3, 4, 30] -0.2069 pnrank 2: [4, 4, 4, 4, 0, 129] -1.6913 [5, 5, 4, 4, 0, 130] -1.015 [4, 4, 5, 5, 0, 130] -1.015 [6, 6, 4, 4, 0, 131] -1.5602 [4, 4, 6, 6, 0, 131] -1.5602 [4, 5, 4, 5, 1, 132] 0.5158 [4, 5, 4, 5, 2, 133] -0.3034 [4, 6, 4, 5, 2, 134] -1.6131 [4, 5, 4, 6, 2, 134] -1.6131 [5, 5, 4, 5, 2, 135] -0.3494 [4, 5, 5, 5, 2, 135] -0.3494 [5, 6, 4, 5, 1, 136] -0.0456 [4, 5, 5, 6, 1, 136] -0.0456 [5, 6, 4, 5, 2, 137] 0.3713 [4, 5, 5, 6, 2, 137] 0.3713 [6, 6, 4, 5, 2, 138] -0.8866 [4, 5, 6, 6, 2, 138] -0.8866 [4, 6, 4, 6, 2, 139] -0.9405 [4, 6, 4, 6, 3, 140] 0.6841 [5, 5, 4, 6, 2, 141] -0.3173 [4, 6, 5, 5, 2, 141] -0.3173 [5, 6, 4, 6, 2, 142] 0.3147 [4, 6, 5, 6, 2, 142] 0.3147 [5, 6, 4, 6, 3, 143] 0.5525 [4, 6, 5, 6, 3, 143] 0.5525 [6, 6, 4, 6, 2, 144] -0.9317 [4, 6, 6, 6, 2, 144] -0.9317 [5, 5, 5, 5, 0, 145] -1.8992 [5, 5, 5, 5, 2, 146] -0.0974 [5, 6, 5, 5, 2, 147] 0.5032 [5, 5, 5, 6, 2, 147] 0.5032 [6, 6, 5, 5, 0, 148] -3.1025 [5, 5, 6, 6, 0, 148] -3.1025 [6, 6, 5, 5, 2, 149] -1.2187 [5, 5, 6, 6, 2, 149] -1.2187 [5, 6, 5, 6, 1, 150] 0.6556 [5, 6, 5, 6, 2, 151] -0.1545 [5, 6, 5, 6, 3, 152] 0.7673 [5, 6, 5, 6, 4, 153] -1.4447 [6, 6, 5, 6, 2, 154] 0.2137 [5, 6, 6, 6, 2, 154] 0.2137 [6, 6, 5, 6, 4, 155] 1.3349 [5, 6, 6, 6, 4, 155] 1.3349 [6, 6, 6, 6, 0, 156] -2.5598 [6, 6, 6, 6, 2, 157] -1.0007 [6, 6, 6, 6, 4, 158] -0.2069 pnrank 3: [1, 4, 1, 4, 0, 31] -1.6913 [1, 4, 1, 4, 1, 32] -3.7093 [1, 5, 1, 4, 1, 33] 0.6506089 [1, 4, 1, 5, 1, 33] 0.6506089 [2, 4, 1, 4, 1, 34] -0.6506089 [1, 4, 2, 4, 1, 34] -0.6506089 [2, 5, 1, 4, 0, 35] -1.015 [1, 4, 2, 5, 0, 35] -1.015 [2, 5, 1, 4, 1, 36] 0.1574 [1, 4, 2, 5, 1, 36] 0.1574 [2, 6, 1, 4, 1, 37] -1.4301942 [1, 4, 2, 6, 1, 37] -1.4301942 [3, 5, 1, 4, 1, 38] 1.4301942 [1, 4, 3, 5, 1, 38] 1.4301942 [3, 6, 1, 4, 0, 39] -1.5602 [1, 4, 3, 6, 0, 39] -1.5602 [3, 6, 1, 4, 1, 40] -0.5344 [1, 4, 3, 6, 1, 40] -0.5344 [1, 5, 1, 5, 1, 41] -1.7651 [1, 5, 1, 5, 2, 42] -1.0769 [1, 6, 1, 5, 2, 43] 0.44895 [1, 5, 1, 6, 2, 43] 0.44895 [2, 4, 1, 5, 1, 44] 2.2809 [1, 5, 2, 4, 1, 44] 2.2809 [2, 4, 1, 5, 2, 45] -0.7735 [1, 5, 2, 4, 2, 45] -0.7735 [2, 5, 1, 5, 1, 46] 0.6005458 [1, 5, 2, 5, 1, 46] 0.6005458 [2, 5, 1, 5, 2, 47] -0.2470631 [1, 5, 2, 5, 2, 47] -0.2470631 [2, 6, 1, 5, 1, 48] 0.78875 [1, 5, 2, 6, 1, 48] 0.78875 [2, 6, 1, 5, 2, 49] -0.0358 [1, 5, 2, 6, 2, 49] -0.0358 [3, 4, 1, 5, 2, 50] -2.06205 [1, 5, 3, 4, 2, 50] -2.06205 [3, 5, 1, 5, 1, 51] -0.83435 [1, 5, 3, 5, 1, 51] -0.83435 [3, 5, 1, 5, 2, 52] -0.4071 [1, 5, 3, 5, 2, 52] -0.4071 [3, 6, 1, 5, 1, 53] -0.0192333 [1, 5, 3, 6, 1, 53] -0.0192333 [3, 6, 1, 5, 2, 54] -0.6269209 [1, 5, 3, 6, 2, 54] -0.6269209 [1, 6, 1, 6, 2, 55] -0.62795 [1, 6, 1, 6, 3, 56] -1.7491 [2, 4, 1, 6, 2, 57] 2.06205 [1, 6, 2, 4, 2, 57] 2.06205 [2, 5, 1, 6, 2, 58] -0.224365 [1, 6, 2, 5, 2, 58] -0.224365 [2, 5, 1, 6, 3, 59] 0.0684479 [1, 6, 2, 5, 3, 59] 0.0684479 [2, 6, 1, 6, 2, 60] 0.48055 [1, 6, 2, 6, 2, 60] 0.48055 [2, 6, 1, 6, 3, 61] -0.35005 [1, 6, 2, 6, 3, 61] -0.35005 [3, 4, 1, 6, 2, 62] -0.31255 [1, 6, 3, 4, 2, 62] -0.31255 [3, 4, 1, 6, 3, 63] -2.4332 [1, 6, 3, 4, 3, 63] -2.4332 [3, 5, 1, 6, 2, 64] 0.16585 [1, 6, 3, 5, 2, 64] 0.16585 [3, 5, 1, 6, 3, 65] 0.90255 [1, 6, 3, 5, 3, 65] 0.90255 [3, 6, 1, 6, 2, 66] -0.6588114 [1, 6, 3, 6, 2, 66] -0.6588114 [3, 6, 1, 6, 3, 67] -0.8603368 [1, 6, 3, 6, 3, 67] -0.8603368 [2, 4, 2, 4, 1, 68] -1.7651 [2, 4, 2, 4, 2, 69] -1.0769 [2, 5, 2, 4, 1, 70] -0.6005458 [2, 4, 2, 5, 1, 70] -0.6005458 [2, 5, 2, 4, 2, 71] 0.2470631 [2, 4, 2, 5, 2, 71] 0.2470631 [2, 6, 2, 4, 1, 72] -0.83435 [2, 4, 2, 6, 1, 72] -0.83435 [2, 6, 2, 4, 2, 73] -0.4071 [2, 4, 2, 6, 2, 73] -0.4071 [3, 4, 2, 4, 2, 74] -0.44895 [2, 4, 3, 4, 2, 74] -0.44895 [3, 5, 2, 4, 1, 75] 0.78875 [2, 4, 3, 5, 1, 75] 0.78875 [3, 5, 2, 4, 2, 76] -0.0358 [2, 4, 3, 5, 2, 76] -0.0358 [3, 6, 2, 4, 1, 77] 0.0192333 [2, 4, 3, 6, 1, 77] 0.0192333 [3, 6, 2, 4, 2, 78] 0.6269209 [2, 4, 3, 6, 2, 78] 0.6269209 [2, 5, 2, 5, 0, 79] -1.8992 [2, 5, 2, 5, 1, 80] -1.6582 [2, 5, 2, 5, 2, 81] -0.0974 [2, 5, 2, 5, 3, 82] -2.966 [2, 6, 2, 5, 1, 83] -0.1359059 [2, 5, 2, 6, 1, 83] -0.1359059 [2, 6, 2, 5, 2, 84] 0.3558161 [2, 5, 2, 6, 2, 84] 0.3558161 [2, 6, 2, 5, 3, 85] -1.0111627 [2, 5, 2, 6, 3, 85] -1.0111627 [3, 4, 2, 5, 2, 86] -0.224365 [2, 5, 3, 4, 2, 86] -0.224365 [3, 4, 2, 5, 3, 87] 0.0684479 [2, 5, 3, 4, 3, 87] 0.0684479 [3, 5, 2, 5, 1, 88] 0.1359059 [2, 5, 3, 5, 1, 88] 0.1359059 [3, 5, 2, 5, 2, 89] -0.3558161 [2, 5, 3, 5, 2, 89] -0.3558161 [3, 5, 2, 5, 3, 90] 1.0111627 [2, 5, 3, 5, 3, 90] 1.0111627 [3, 6, 2, 5, 0, 91] -3.1025 [2, 5, 3, 6, 0, 91] -3.1025 [3, 6, 2, 5, 1, 92] 1.6647 [2, 5, 3, 6, 1, 92] 1.6647 [3, 6, 2, 5, 2, 93] -1.2187 [2, 5, 3, 6, 2, 93] -1.2187 [3, 6, 2, 5, 3, 94] 1.1792 [2, 5, 3, 6, 3, 94] 1.1792 [2, 6, 2, 6, 1, 95] -2.67715 [2, 6, 2, 6, 2, 96] -2.1831 [2, 6, 2, 6, 3, 97] -0.22255 [2, 6, 2, 6, 4, 98] -3.0318 [3, 4, 2, 6, 2, 99] -0.16585 [2, 6, 3, 4, 2, 99] -0.16585 [3, 4, 2, 6, 3, 100] -0.90255 [2, 6, 3, 4, 3, 100] -0.90255 [3, 5, 2, 6, 1, 101] 3.33275 [2, 6, 3, 5, 1, 101] 3.33275 [3, 5, 2, 6, 2, 102] -2.0286 [2, 6, 3, 5, 2, 102] -2.0286 [3, 5, 2, 6, 3, 103] 0.98985 [2, 6, 3, 5, 3, 103] 0.98985 [3, 5, 2, 6, 4, 104] -1.5871 [2, 6, 3, 5, 4, 104] -1.5871 [3, 6, 2, 6, 1, 105] -2.4739545 [2, 6, 3, 6, 1, 105] -2.4739545 [3, 6, 2, 6, 2, 106] 0.1511087 [2, 6, 3, 6, 2, 106] 0.1511087 [3, 6, 2, 6, 3, 107] -1.6335581 [2, 6, 3, 6, 3, 107] -1.6335581 [3, 6, 2, 6, 4, 108] 0.9439168 [2, 6, 3, 6, 4, 108] 0.9439168 [3, 4, 3, 4, 2, 109] -0.62795 [3, 4, 3, 4, 3, 110] -1.7491 [3, 5, 3, 4, 2, 111] -0.48055 [3, 4, 3, 5, 2, 111] -0.48055 [3, 5, 3, 4, 3, 112] 0.35005 [3, 4, 3, 5, 3, 112] 0.35005 [3, 6, 3, 4, 2, 113] -0.6588114 [3, 4, 3, 6, 2, 113] -0.6588114 [3, 6, 3, 4, 3, 114] -0.8603368 [3, 4, 3, 6, 3, 114] -0.8603368 [3, 5, 3, 5, 1, 115] -2.67715 [3, 5, 3, 5, 2, 116] -2.1831 [3, 5, 3, 5, 3, 117] -0.22255 [3, 5, 3, 5, 4, 118] -3.0318 [3, 6, 3, 5, 1, 119] 2.4739545 [3, 5, 3, 6, 1, 119] 2.4739545 [3, 6, 3, 5, 2, 120] -0.1511087 [3, 5, 3, 6, 2, 120] -0.1511087 [3, 6, 3, 5, 3, 121] 1.6335581 [3, 5, 3, 6, 3, 121] 1.6335581 [3, 6, 3, 5, 4, 122] -0.9439168 [3, 5, 3, 6, 4, 122] -0.9439168 [3, 6, 3, 6, 0, 123] -2.5598 [3, 6, 3, 6, 1, 124] -1.3796 [3, 6, 3, 6, 2, 125] -1.0007 [3, 6, 3, 6, 3, 126] -1.6651 [3, 6, 3, 6, 4, 127] -0.2069 [3, 6, 3, 6, 5, 128] -4.3205 labels[i] [1, 4, 1, 4, 0, 31] ME -1.6913 labels[i] [1, 4, 1, 4, 1, 32] ME -3.7093 labels[i] [1, 5, 1, 4, 1, 33] ME 0.6506089 labels[i] [1, 4, 1, 5, 1, 33] ME 0.6506089 labels[i] [2, 4, 1, 4, 1, 34] ME -0.6506089 labels[i] [1, 4, 2, 4, 1, 34] ME -0.6506089 labels[i] [2, 5, 1, 4, 0, 35] ME -1.015 labels[i] [1, 4, 2, 5, 0, 35] ME -1.015 labels[i] [2, 5, 1, 4, 1, 36] ME 0.1574 labels[i] [1, 4, 2, 5, 1, 36] ME 0.1574 labels[i] [2, 6, 1, 4, 1, 37] ME -1.4301942 labels[i] [1, 4, 2, 6, 1, 37] ME -1.4301942 labels[i] [3, 5, 1, 4, 1, 38] ME 1.4301942 labels[i] [1, 4, 3, 5, 1, 38] ME 1.4301942 labels[i] [3, 6, 1, 4, 0, 39] ME -1.5602 labels[i] [1, 4, 3, 6, 0, 39] ME -1.5602 labels[i] [3, 6, 1, 4, 1, 40] ME -0.5344 labels[i] [1, 4, 3, 6, 1, 40] ME -0.5344 labels[i] [1, 5, 1, 5, 1, 41] ME -1.7651 labels[i] [1, 5, 1, 5, 2, 42] ME -1.0769 labels[i] [1, 6, 1, 5, 2, 43] ME 0.44895 labels[i] [1, 5, 1, 6, 2, 43] ME 0.44895 labels[i] [2, 4, 1, 5, 1, 44] ME 2.2809 labels[i] [1, 5, 2, 4, 1, 44] ME 2.2809 labels[i] [2, 4, 1, 5, 2, 45] ME -0.7735 labels[i] [1, 5, 2, 4, 2, 45] ME -0.7735 labels[i] [2, 5, 1, 5, 1, 46] ME 0.6005458 labels[i] [1, 5, 2, 5, 1, 46] ME 0.6005458 labels[i] [2, 5, 1, 5, 2, 47] ME -0.2470631 labels[i] [1, 5, 2, 5, 2, 47] ME -0.2470631 labels[i] [2, 6, 1, 5, 1, 48] ME 0.78875 labels[i] [1, 5, 2, 6, 1, 48] ME 0.78875 labels[i] [2, 6, 1, 5, 2, 49] ME -0.0358 labels[i] [1, 5, 2, 6, 2, 49] ME -0.0358 labels[i] [3, 4, 1, 5, 2, 50] ME -2.06205 labels[i] [1, 5, 3, 4, 2, 50] ME -2.06205 labels[i] [3, 5, 1, 5, 1, 51] ME -0.83435 labels[i] [1, 5, 3, 5, 1, 51] ME -0.83435 labels[i] [3, 5, 1, 5, 2, 52] ME -0.4071 labels[i] [1, 5, 3, 5, 2, 52] ME -0.4071 labels[i] [3, 6, 1, 5, 1, 53] ME -0.0192333 labels[i] [1, 5, 3, 6, 1, 53] ME -0.0192333 labels[i] [3, 6, 1, 5, 2, 54] ME -0.6269209 labels[i] [1, 5, 3, 6, 2, 54] ME -0.6269209 labels[i] [1, 6, 1, 6, 2, 55] ME -0.62795 labels[i] [1, 6, 1, 6, 3, 56] ME -1.7491 labels[i] [2, 4, 1, 6, 2, 57] ME 2.06205 labels[i] [1, 6, 2, 4, 2, 57] ME 2.06205 labels[i] [2, 5, 1, 6, 2, 58] ME -0.224365 labels[i] [1, 6, 2, 5, 2, 58] ME -0.224365 labels[i] [2, 5, 1, 6, 3, 59] ME 0.0684479 labels[i] [1, 6, 2, 5, 3, 59] ME 0.0684479 labels[i] [2, 6, 1, 6, 2, 60] ME 0.48055 labels[i] [1, 6, 2, 6, 2, 60] ME 0.48055 labels[i] [2, 6, 1, 6, 3, 61] ME -0.35005 labels[i] [1, 6, 2, 6, 3, 61] ME -0.35005 labels[i] [3, 4, 1, 6, 2, 62] ME -0.31255 labels[i] [1, 6, 3, 4, 2, 62] ME -0.31255 labels[i] [3, 4, 1, 6, 3, 63] ME -2.4332 labels[i] [1, 6, 3, 4, 3, 63] ME -2.4332 labels[i] [3, 5, 1, 6, 2, 64] ME 0.16585 labels[i] [1, 6, 3, 5, 2, 64] ME 0.16585 labels[i] [3, 5, 1, 6, 3, 65] ME 0.90255 labels[i] [1, 6, 3, 5, 3, 65] ME 0.90255 labels[i] [3, 6, 1, 6, 2, 66] ME -0.6588114 labels[i] [1, 6, 3, 6, 2, 66] ME -0.6588114 labels[i] [3, 6, 1, 6, 3, 67] ME -0.8603368 labels[i] [1, 6, 3, 6, 3, 67] ME -0.8603368 labels[i] [2, 4, 2, 4, 1, 68] ME -1.7651 labels[i] [2, 4, 2, 4, 2, 69] ME -1.0769 labels[i] [2, 5, 2, 4, 1, 70] ME -0.6005458 labels[i] [2, 4, 2, 5, 1, 70] ME -0.6005458 labels[i] [2, 5, 2, 4, 2, 71] ME 0.2470631 labels[i] [2, 4, 2, 5, 2, 71] ME 0.2470631 labels[i] [2, 6, 2, 4, 1, 72] ME -0.83435 labels[i] [2, 4, 2, 6, 1, 72] ME -0.83435 labels[i] [2, 6, 2, 4, 2, 73] ME -0.4071 labels[i] [2, 4, 2, 6, 2, 73] ME -0.4071 labels[i] [3, 4, 2, 4, 2, 74] ME -0.44895 labels[i] [2, 4, 3, 4, 2, 74] ME -0.44895 labels[i] [3, 5, 2, 4, 1, 75] ME 0.78875 labels[i] [2, 4, 3, 5, 1, 75] ME 0.78875 labels[i] [3, 5, 2, 4, 2, 76] ME -0.0358 labels[i] [2, 4, 3, 5, 2, 76] ME -0.0358 labels[i] [3, 6, 2, 4, 1, 77] ME 0.0192333 labels[i] [2, 4, 3, 6, 1, 77] ME 0.0192333 labels[i] [3, 6, 2, 4, 2, 78] ME 0.6269209 labels[i] [2, 4, 3, 6, 2, 78] ME 0.6269209 labels[i] [2, 5, 2, 5, 0, 79] ME -1.8992 labels[i] [2, 5, 2, 5, 1, 80] ME -1.6582 labels[i] [2, 5, 2, 5, 2, 81] ME -0.0974 labels[i] [2, 5, 2, 5, 3, 82] ME -2.966 labels[i] [2, 6, 2, 5, 1, 83] ME -0.1359059 labels[i] [2, 5, 2, 6, 1, 83] ME -0.1359059 labels[i] [2, 6, 2, 5, 2, 84] ME 0.3558161 labels[i] [2, 5, 2, 6, 2, 84] ME 0.3558161 labels[i] [2, 6, 2, 5, 3, 85] ME -1.0111627 labels[i] [2, 5, 2, 6, 3, 85] ME -1.0111627 labels[i] [3, 4, 2, 5, 2, 86] ME -0.224365 labels[i] [2, 5, 3, 4, 2, 86] ME -0.224365 labels[i] [3, 4, 2, 5, 3, 87] ME 0.0684479 labels[i] [2, 5, 3, 4, 3, 87] ME 0.0684479 labels[i] [3, 5, 2, 5, 1, 88] ME 0.1359059 labels[i] [2, 5, 3, 5, 1, 88] ME 0.1359059 labels[i] [3, 5, 2, 5, 2, 89] ME -0.3558161 labels[i] [2, 5, 3, 5, 2, 89] ME -0.3558161 labels[i] [3, 5, 2, 5, 3, 90] ME 1.0111627 labels[i] [2, 5, 3, 5, 3, 90] ME 1.0111627 labels[i] [3, 6, 2, 5, 0, 91] ME -3.1025 labels[i] [2, 5, 3, 6, 0, 91] ME -3.1025 labels[i] [3, 6, 2, 5, 1, 92] ME 1.6647 labels[i] [2, 5, 3, 6, 1, 92] ME 1.6647 labels[i] [3, 6, 2, 5, 2, 93] ME -1.2187 labels[i] [2, 5, 3, 6, 2, 93] ME -1.2187 labels[i] [3, 6, 2, 5, 3, 94] ME 1.1792 labels[i] [2, 5, 3, 6, 3, 94] ME 1.1792 labels[i] [2, 6, 2, 6, 1, 95] ME -2.67715 labels[i] [2, 6, 2, 6, 2, 96] ME -2.1831 labels[i] [2, 6, 2, 6, 3, 97] ME -0.22255 labels[i] [2, 6, 2, 6, 4, 98] ME -3.0318 labels[i] [3, 4, 2, 6, 2, 99] ME -0.16585 labels[i] [2, 6, 3, 4, 2, 99] ME -0.16585 labels[i] [3, 4, 2, 6, 3, 100] ME -0.90255 labels[i] [2, 6, 3, 4, 3, 100] ME -0.90255 labels[i] [3, 5, 2, 6, 1, 101] ME 3.33275 labels[i] [2, 6, 3, 5, 1, 101] ME 3.33275 labels[i] [3, 5, 2, 6, 2, 102] ME -2.0286 labels[i] [2, 6, 3, 5, 2, 102] ME -2.0286 labels[i] [3, 5, 2, 6, 3, 103] ME 0.98985 labels[i] [2, 6, 3, 5, 3, 103] ME 0.98985 labels[i] [3, 5, 2, 6, 4, 104] ME -1.5871 labels[i] [2, 6, 3, 5, 4, 104] ME -1.5871 labels[i] [3, 6, 2, 6, 1, 105] ME -2.4739545 labels[i] [2, 6, 3, 6, 1, 105] ME -2.4739545 labels[i] [3, 6, 2, 6, 2, 106] ME 0.1511087 labels[i] [2, 6, 3, 6, 2, 106] ME 0.1511087 labels[i] [3, 6, 2, 6, 3, 107] ME -1.6335581 labels[i] [2, 6, 3, 6, 3, 107] ME -1.6335581 labels[i] [3, 6, 2, 6, 4, 108] ME 0.9439168 labels[i] [2, 6, 3, 6, 4, 108] ME 0.9439168 labels[i] [3, 4, 3, 4, 2, 109] ME -0.62795 labels[i] [3, 4, 3, 4, 3, 110] ME -1.7491 labels[i] [3, 5, 3, 4, 2, 111] ME -0.48055 labels[i] [3, 4, 3, 5, 2, 111] ME -0.48055 labels[i] [3, 5, 3, 4, 3, 112] ME 0.35005 labels[i] [3, 4, 3, 5, 3, 112] ME 0.35005 labels[i] [3, 6, 3, 4, 2, 113] ME -0.6588114 labels[i] [3, 4, 3, 6, 2, 113] ME -0.6588114 labels[i] [3, 6, 3, 4, 3, 114] ME -0.8603368 labels[i] [3, 4, 3, 6, 3, 114] ME -0.8603368 labels[i] [3, 5, 3, 5, 1, 115] ME -2.67715 labels[i] [3, 5, 3, 5, 2, 116] ME -2.1831 labels[i] [3, 5, 3, 5, 3, 117] ME -0.22255 labels[i] [3, 5, 3, 5, 4, 118] ME -3.0318 labels[i] [3, 6, 3, 5, 1, 119] ME 2.4739545 labels[i] [3, 5, 3, 6, 1, 119] ME 2.4739545 labels[i] [3, 6, 3, 5, 2, 120] ME -0.1511087 labels[i] [3, 5, 3, 6, 2, 120] ME -0.1511087 labels[i] [3, 6, 3, 5, 3, 121] ME 1.6335581 labels[i] [3, 5, 3, 6, 3, 121] ME 1.6335581 labels[i] [3, 6, 3, 5, 4, 122] ME -0.9439168 labels[i] [3, 5, 3, 6, 4, 122] ME -0.9439168 labels[i] [3, 6, 3, 6, 0, 123] ME -2.5598 labels[i] [3, 6, 3, 6, 1, 124] ME -1.3796 labels[i] [3, 6, 3, 6, 2, 125] ME -1.0007 labels[i] [3, 6, 3, 6, 3, 126] ME -1.6651 labels[i] [3, 6, 3, 6, 4, 127] ME -0.2069 labels[i] [3, 6, 3, 6, 5, 128] ME -4.3205 2J= 0 En. 2.32420 Be8 Z,N=(4,4) c(2,2) v(2,2) mdim: 51 ( 1.71 ) pnrank 1: [1, 1, 1, 1, 0, 1] 0.244 [2, 2, 1, 1, 0, 2] -5.0526 [1, 1, 2, 2, 0, 2] -5.0526 [1, 2, 1, 2, 1, 3] 0.7344 [1, 2, 1, 2, 2, 4] -1.1443 [2, 2, 1, 2, 2, 5] 1.7423 [1, 2, 2, 2, 2, 5] 1.7423 [2, 2, 2, 2, 0, 6] -3.3287 [2, 2, 2, 2, 2, 7] 0.0878 pnrank 2: [3, 3, 3, 3, 0, 8] 0.244 [4, 4, 3, 3, 0, 9] -5.0526 [3, 3, 4, 4, 0, 9] -5.0526 [3, 4, 3, 4, 1, 10] 0.7344 [3, 4, 3, 4, 2, 11] -1.1443 [4, 4, 3, 4, 2, 12] 1.7423 [3, 4, 4, 4, 2, 12] 1.7423 [4, 4, 4, 4, 0, 13] -3.3287 [4, 4, 4, 4, 2, 14] 0.0878 pnrank 3: [1, 3, 1, 3, 0, 15] 0.244 [1, 3, 1, 3, 1, 16] -4.29215 [1, 4, 1, 3, 1, 17] -0.85185 [1, 3, 1, 4, 1, 17] -0.85185 [2, 3, 1, 3, 1, 18] 0.85185 [1, 3, 2, 3, 1, 18] 0.85185 [2, 4, 1, 3, 0, 19] -5.0526 [1, 3, 2, 4, 0, 19] -5.0526 [2, 4, 1, 3, 1, 20] 1.7698 [1, 3, 2, 4, 1, 20] 1.7698 [1, 4, 1, 4, 1, 21] -2.91415 [1, 4, 2, 3, 1, 22] 3.64855 [2, 3, 1, 4, 1, 22] 3.64855 [2, 3, 2, 3, 1, 23] -2.91415 [1, 4, 1, 4, 2, 24] -2.6011 [1, 4, 2, 3, 2, 25] -1.4568 [2, 3, 1, 4, 2, 25] -1.4568 [2, 3, 2, 3, 2, 26] -2.6011 [2, 4, 1, 4, 1, 27] -2.2667 [1, 4, 2, 4, 1, 27] -2.2667 [2, 4, 2, 3, 1, 28] 2.2667 [2, 3, 2, 4, 1, 28] 2.2667 [2, 4, 1, 4, 2, 29] 1.23199 [1, 4, 2, 4, 2, 29] 1.23199 [2, 4, 2, 3, 2, 30] -1.23199 [2, 3, 2, 4, 2, 30] -1.23199 [2, 4, 2, 4, 0, 31] -3.3287 [2, 4, 2, 4, 1, 32] -3.4362 [2, 4, 2, 4, 2, 33] 0.0878 [2, 4, 2, 4, 3, 34] -7.2668 labels[i] [1, 3, 1, 3, 0, 15] ME 0.244 labels[i] [1, 3, 1, 3, 1, 16] ME -4.29215 labels[i] [1, 4, 1, 3, 1, 17] ME -0.85185 labels[i] [1, 3, 1, 4, 1, 17] ME -0.85185 labels[i] [2, 3, 1, 3, 1, 18] ME 0.85185 labels[i] [1, 3, 2, 3, 1, 18] ME 0.85185 labels[i] [2, 4, 1, 3, 0, 19] ME -5.0526 labels[i] [1, 3, 2, 4, 0, 19] ME -5.0526 labels[i] [2, 4, 1, 3, 1, 20] ME 1.7698 labels[i] [1, 3, 2, 4, 1, 20] ME 1.7698 labels[i] [1, 4, 1, 4, 1, 21] ME -2.91415 labels[i] [1, 4, 2, 3, 1, 22] ME 3.64855 labels[i] [2, 3, 1, 4, 1, 22] ME 3.64855 labels[i] [2, 3, 2, 3, 1, 23] ME -2.91415 labels[i] [1, 4, 1, 4, 2, 24] ME -2.6011 labels[i] [1, 4, 2, 3, 2, 25] ME -1.4568 labels[i] [2, 3, 1, 4, 2, 25] ME -1.4568 labels[i] [2, 3, 2, 3, 2, 26] ME -2.6011 labels[i] [2, 4, 1, 4, 1, 27] ME -2.2667 labels[i] [1, 4, 2, 4, 1, 27] ME -2.2667 labels[i] [2, 4, 2, 3, 1, 28] ME 2.2667 labels[i] [2, 3, 2, 4, 1, 28] ME 2.2667 labels[i] [2, 4, 1, 4, 2, 29] ME 1.23199 labels[i] [1, 4, 2, 4, 2, 29] ME 1.23199 labels[i] [2, 4, 2, 3, 2, 30] ME -1.23199 labels[i] [2, 3, 2, 4, 2, 30] ME -1.23199 labels[i] [2, 4, 2, 4, 0, 31] ME -3.3287 labels[i] [2, 4, 2, 4, 1, 32] ME -3.4362 labels[i] [2, 4, 2, 4, 2, 33] ME 0.0878 labels[i] [2, 4, 2, 4, 3, 34] ME -7.2668 2J= 0 En. -31.11941 eigvals(Hflat) -31.1194 _0 = -31.11940948105114 _0 = 0.0 pn-pair truncated dim. => 15 En. = -20.698502739983773 config: 1 π: 40 ν:17 weight -0.16336915338529687 proton neutron 　　●◯　 　　◯●　 　●◯◯◯ 　◯◯◯● config: 2 π: 12 ν:3 weight -0.1720912047326677 proton neutron 　　◯◯　 　　◯◯　 　●●◯◯ 　◯◯●● config: 3 π: 36 ν:18 weight 0.0897653865954266 proton neutron 　　●◯　 　　◯●　 　◯●◯◯ 　◯◯●◯ config: 4 π: 24 ν:33 weight 0.04255369237039856 proton neutron 　　◯●　 　　●◯　 　●◯◯◯ 　◯◯◯● config: 5 π: 10 ν:5 weight 0.03844976927767668 proton neutron 　　◯◯　 　　◯◯　 　●◯●◯ 　◯●◯● config: 6 π: 48 ν:48 weight -0.0851717244204334 proton neutron 　　●●　 　　●●　 　◯◯◯◯ 　◯◯◯◯ config: 7 π: 34 ν:20 weight -0.08071065890181586 proton neutron 　　●◯　 　　◯●　 　◯◯●◯ 　◯●◯◯ config: 8 π: 20 ν:34 weight -0.0807106589018162 proton neutron 　　◯●　 　　●◯　 　◯●◯◯ 　◯◯●◯ config: 9 π: 9 ν:9 weight -0.7257875914760176 proton neutron 　　◯◯　 　　◯◯　 　●◯◯● 　●◯◯● config: 10 π: 6 ν:6 weight -0.5636008784633381 proton neutron 　　◯◯　 　　◯◯　 　◯●●◯ 　◯●●◯ config: 11 π: 33 ν:24 weight 0.04255369237039883 proton neutron 　　●◯　 　　◯●　 　◯◯◯● 　●◯◯◯ config: 12 π: 18 ν:36 weight 0.089765386595426 proton neutron 　　◯●　 　　●◯　 　◯◯●◯ 　◯●◯◯ config: 13 π: 5 ν:10 weight 0.03844976927767785 proton neutron 　　◯◯　 　　◯◯　 　◯●◯● 　●◯●◯ config: 14 π: 17 ν:40 weight -0.163369153385297 proton neutron 　　◯●　 　　●◯　 　◯◯◯● 　●◯◯◯ config: 15 π: 3 ν:12 weight -0.1720912047326674 proton neutron 　　◯◯　 　　◯◯　 　◯◯●● 　●●◯◯ Li6 Z,N=(3,3) c(2,2) v(1,1) mdim: 10 ( 1.00 ) config: 1 --oo-- π0s1/2 -xooo- π0s3/2 --oo-- ν0s1/2 -ooox- ν0s3/2 config: 2 --xo-- π0s1/2 -oooo- π0s3/2 --ox-- ν0s1/2 -oooo- ν0s3/2 config: 3 --xo-- π0s1/2 -oooo- π0s3/2 --oo-- ν0s1/2 -ooxo- ν0s3/2 config: 4 --oo-- π0s1/2 -oxoo- π0s3/2 --ox-- ν0s1/2 -oooo- ν0s3/2 config: 5 --oo-- π0s1/2 -oxoo- π0s3/2 --oo-- ν0s1/2 -ooxo- ν0s3/2 config: 6 --ox-- π0s1/2 -oooo- π0s3/2 --xo-- ν0s1/2 -oooo- ν0s3/2 config: 7 --ox-- π0s1/2 -oooo- π0s3/2 --oo-- ν0s1/2 -oxoo- ν0s3/2 config: 8 --oo-- π0s1/2 -ooxo- π0s3/2 --xo-- ν0s1/2 -oooo- ν0s3/2 config: 9 --oo-- π0s1/2 -ooxo- π0s3/2 --oo-- ν0s1/2 -oxoo- ν0s3/2 config: 10 --oo-- π0s1/2 -ooox- π0s3/2 --oo-- ν0s1/2 -xooo- ν0s3/2 pnrank 1: [1, 1, 1, 1, 0, 1] 0.244 [2, 2, 1, 1, 0, 2] -5.0526 [1, 1, 2, 2, 0, 2] -5.0526 [1, 2, 1, 2, 1, 3] 0.7344 [1, 2, 1, 2, 2, 4] -1.1443 [2, 2, 1, 2, 2, 5] 1.7423 [1, 2, 2, 2, 2, 5] 1.7423 [2, 2, 2, 2, 0, 6] -3.3287 [2, 2, 2, 2, 2, 7] 0.0878 pnrank 2: [3, 3, 3, 3, 0, 8] 0.244 [4, 4, 3, 3, 0, 9] -5.0526 [3, 3, 4, 4, 0, 9] -5.0526 [3, 4, 3, 4, 1, 10] 0.7344 [3, 4, 3, 4, 2, 11] -1.1443 [4, 4, 3, 4, 2, 12] 1.7423 [3, 4, 4, 4, 2, 12] 1.7423 [4, 4, 4, 4, 0, 13] -3.3287 [4, 4, 4, 4, 2, 14] 0.0878 pnrank 3: [1, 3, 1, 3, 0, 15] 0.244 [1, 3, 1, 3, 1, 16] -4.29215 [1, 4, 1, 3, 1, 17] -0.85185 [1, 3, 1, 4, 1, 17] -0.85185 [2, 3, 1, 3, 1, 18] 0.85185 [1, 3, 2, 3, 1, 18] 0.85185 [2, 4, 1, 3, 0, 19] -5.0526 [1, 3, 2, 4, 0, 19] -5.0526 [2, 4, 1, 3, 1, 20] 1.7698 [1, 3, 2, 4, 1, 20] 1.7698 [1, 4, 1, 4, 1, 21] -2.91415 [1, 4, 2, 3, 1, 22] 3.64855 [2, 3, 1, 4, 1, 22] 3.64855 [2, 3, 2, 3, 1, 23] -2.91415 [1, 4, 1, 4, 2, 24] -2.6011 [1, 4, 2, 3, 2, 25] -1.4568 [2, 3, 1, 4, 2, 25] -1.4568 [2, 3, 2, 3, 2, 26] -2.6011 [2, 4, 1, 4, 1, 27] -2.2667 [1, 4, 2, 4, 1, 27] -2.2667 [2, 4, 2, 3, 1, 28] 2.2667 [2, 3, 2, 4, 1, 28] 2.2667 [2, 4, 1, 4, 2, 29] 1.23199 [1, 4, 2, 4, 2, 29] 1.23199 [2, 4, 2, 3, 2, 30] -1.23199 [2, 3, 2, 4, 2, 30] -1.23199 [2, 4, 2, 4, 0, 31] -3.3287 [2, 4, 2, 4, 1, 32] -3.4362 [2, 4, 2, 4, 2, 33] 0.0878 [2, 4, 2, 4, 3, 34] -7.2668 labels[i] [1, 3, 1, 3, 0, 15] ME 0.244 labels[i] [1, 3, 1, 3, 1, 16] ME -4.29215 labels[i] [1, 4, 1, 3, 1, 17] ME -0.85185 labels[i] [1, 3, 1, 4, 1, 17] ME -0.85185 labels[i] [2, 3, 1, 3, 1, 18] ME 0.85185 labels[i] [1, 3, 2, 3, 1, 18] ME 0.85185 labels[i] [2, 4, 1, 3, 0, 19] ME -5.0526 labels[i] [1, 3, 2, 4, 0, 19] ME -5.0526 labels[i] [2, 4, 1, 3, 1, 20] ME 1.7698 labels[i] [1, 3, 2, 4, 1, 20] ME 1.7698 labels[i] [1, 4, 1, 4, 1, 21] ME -2.91415 labels[i] [1, 4, 2, 3, 1, 22] ME 3.64855 labels[i] [2, 3, 1, 4, 1, 22] ME 3.64855 labels[i] [2, 3, 2, 3, 1, 23] ME -2.91415 labels[i] [1, 4, 1, 4, 2, 24] ME -2.6011 labels[i] [1, 4, 2, 3, 2, 25] ME -1.4568 labels[i] [2, 3, 1, 4, 2, 25] ME -1.4568 labels[i] [2, 3, 2, 3, 2, 26] ME -2.6011 labels[i] [2, 4, 1, 4, 1, 27] ME -2.2667 labels[i] [1, 4, 2, 4, 1, 27] ME -2.2667 labels[i] [2, 4, 2, 3, 1, 28] ME 2.2667 labels[i] [2, 3, 2, 4, 1, 28] ME 2.2667 labels[i] [2, 4, 1, 4, 2, 29] ME 1.23199 labels[i] [1, 4, 2, 4, 2, 29] ME 1.23199 labels[i] [2, 4, 2, 3, 2, 30] ME -1.23199 labels[i] [2, 3, 2, 4, 2, 30] ME -1.23199 labels[i] [2, 4, 2, 4, 0, 31] ME -3.3287 labels[i] [2, 4, 2, 4, 1, 32] ME -3.4362 labels[i] [2, 4, 2, 4, 2, 33] ME 0.0878 labels[i] [2, 4, 2, 4, 3, 34] ME -7.2668 2J= 0 En. -3.90981 n= 1 entropy 1.7710069416492182 0.1900 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1200 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1900 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1200 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1900 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1900 U 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 -0.0000 0.0000 -1.0000 0.0000 0.0000 0.0000 1.0000 0.0000 -0.0000 0.0000 0.0000 -0.0000 0.0000 0.0000 0.0000 -1.0000 0.0000 1.0000 0.0000 0.0000 0.0000 -0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 Sig 0.1900 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1900 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1900 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1900 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1200 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.1200 V 0.0000 0.0000 0.0000 1.0000 -0.0000 -0.0000 0.0000 0.0000 0.0000 0.0000 -1.0000 -0.0000 0.0000 0.0000 1.0000 0.0000 -0.0000 -0.0000 0.0000 0.0000 0.0000 0.0000 -0.0000 -1.0000 0.0000 1.0000 0.0000 0.0000 -0.0000 -0.0000 1.0000 0.0000 0.0000 0.0000 -0.0000 -0.0000 He6 Z,N=(2,4) c(2,2) v(0,2) mdim: 5 ( 0.70 ) pnrank 1: [1, 1, 1, 1, 0, 1] 0.244 [2, 2, 1, 1, 0, 2] -5.0526 [1, 1, 2, 2, 0, 2] -5.0526 [1, 2, 1, 2, 1, 3] 0.7344 [1, 2, 1, 2, 2, 4] -1.1443 [2, 2, 1, 2, 2, 5] 1.7423 [1, 2, 2, 2, 2, 5] 1.7423 [2, 2, 2, 2, 0, 6] -3.3287 [2, 2, 2, 2, 2, 7] 0.0878 pnrank 2: [3, 3, 3, 3, 0, 8] 0.244 [4, 4, 3, 3, 0, 9] -5.0526 [3, 3, 4, 4, 0, 9] -5.0526 [3, 4, 3, 4, 1, 10] 0.7344 [3, 4, 3, 4, 2, 11] -1.1443 [4, 4, 3, 4, 2, 12] 1.7423 [3, 4, 4, 4, 2, 12] 1.7423 [4, 4, 4, 4, 0, 13] -3.3287 [4, 4, 4, 4, 2, 14] 0.0878 pnrank 3: [1, 3, 1, 3, 0, 15] 0.244 [1, 3, 1, 3, 1, 16] -4.29215 [1, 4, 1, 3, 1, 17] -0.85185 [1, 3, 1, 4, 1, 17] -0.85185 [2, 3, 1, 3, 1, 18] 0.85185 [1, 3, 2, 3, 1, 18] 0.85185 [2, 4, 1, 3, 0, 19] -5.0526 [1, 3, 2, 4, 0, 19] -5.0526 [2, 4, 1, 3, 1, 20] 1.7698 [1, 3, 2, 4, 1, 20] 1.7698 [1, 4, 1, 4, 1, 21] -2.91415 [1, 4, 2, 3, 1, 22] 3.64855 [2, 3, 1, 4, 1, 22] 3.64855 [2, 3, 2, 3, 1, 23] -2.91415 [1, 4, 1, 4, 2, 24] -2.6011 [1, 4, 2, 3, 2, 25] -1.4568 [2, 3, 1, 4, 2, 25] -1.4568 [2, 3, 2, 3, 2, 26] -2.6011 [2, 4, 1, 4, 1, 27] -2.2667 [1, 4, 2, 4, 1, 27] -2.2667 [2, 4, 2, 3, 1, 28] 2.2667 [2, 3, 2, 4, 1, 28] 2.2667 [2, 4, 1, 4, 2, 29] 1.23199 [1, 4, 2, 4, 2, 29] 1.23199 [2, 4, 2, 3, 2, 30] -1.23199 [2, 3, 2, 4, 2, 30] -1.23199 [2, 4, 2, 4, 0, 31] -3.3287 [2, 4, 2, 4, 1, 32] -3.4362 [2, 4, 2, 4, 2, 33] 0.0878 [2, 4, 2, 4, 3, 34] -7.2668 labels[i] [1, 3, 1, 3, 0, 15] ME 0.244 labels[i] [1, 3, 1, 3, 1, 16] ME -4.29215 labels[i] [1, 4, 1, 3, 1, 17] ME -0.85185 labels[i] [1, 3, 1, 4, 1, 17] ME -0.85185 labels[i] [2, 3, 1, 3, 1, 18] ME 0.85185 labels[i] [1, 3, 2, 3, 1, 18] ME 0.85185 labels[i] [2, 4, 1, 3, 0, 19] ME -5.0526 labels[i] [1, 3, 2, 4, 0, 19] ME -5.0526 labels[i] [2, 4, 1, 3, 1, 20] ME 1.7698 labels[i] [1, 3, 2, 4, 1, 20] ME 1.7698 labels[i] [1, 4, 1, 4, 1, 21] ME -2.91415 labels[i] [1, 4, 2, 3, 1, 22] ME 3.64855 labels[i] [2, 3, 1, 4, 1, 22] ME 3.64855 labels[i] [2, 3, 2, 3, 1, 23] ME -2.91415 labels[i] [1, 4, 1, 4, 2, 24] ME -2.6011 labels[i] [1, 4, 2, 3, 2, 25] ME -1.4568 labels[i] [2, 3, 1, 4, 2, 25] ME -1.4568 labels[i] [2, 3, 2, 3, 2, 26] ME -2.6011 labels[i] [2, 4, 1, 4, 1, 27] ME -2.2667 labels[i] [1, 4, 2, 4, 1, 27] ME -2.2667 labels[i] [2, 4, 2, 3, 1, 28] ME 2.2667 labels[i] [2, 3, 2, 4, 1, 28] ME 2.2667 labels[i] [2, 4, 1, 4, 2, 29] ME 1.23199 labels[i] [1, 4, 2, 4, 2, 29] ME 1.23199 labels[i] [2, 4, 2, 3, 2, 30] ME -1.23199 labels[i] [2, 3, 2, 4, 2, 30] ME -1.23199 labels[i] [2, 4, 2, 4, 0, 31] ME -3.3287 labels[i] [2, 4, 2, 4, 1, 32] ME -3.4362 labels[i] [2, 4, 2, 4, 2, 33] ME 0.0878 labels[i] [2, 4, 2, 4, 3, 34] ME -7.2668 2J= 0 En. -3.90981 He6 Z,N=(2,4) c(2,2) v(0,2) mdim: 2 ( 0.30 ) pnrank 1: [1, 1, 1, 1, 0, 1] 0.244 [2, 2, 1, 1, 0, 2] -5.0526 [1, 1, 2, 2, 0, 2] -5.0526 [1, 2, 1, 2, 1, 3] 0.7344 [1, 2, 1, 2, 2, 4] -1.1443 [2, 2, 1, 2, 2, 5] 1.7423 [1, 2, 2, 2, 2, 5] 1.7423 [2, 2, 2, 2, 0, 6] -3.3287 [2, 2, 2, 2, 2, 7] 0.0878 pnrank 2: [3, 3, 3, 3, 0, 8] 0.244 [4, 4, 3, 3, 0, 9] -5.0526 [3, 3, 4, 4, 0, 9] -5.0526 [3, 4, 3, 4, 1, 10] 0.7344 [3, 4, 3, 4, 2, 11] -1.1443 [4, 4, 3, 4, 2, 12] 1.7423 [3, 4, 4, 4, 2, 12] 1.7423 [4, 4, 4, 4, 0, 13] -3.3287 [4, 4, 4, 4, 2, 14] 0.0878 pnrank 3: [1, 3, 1, 3, 0, 15] 0.244 [1, 3, 1, 3, 1, 16] -4.29215 [1, 4, 1, 3, 1, 17] -0.85185 [1, 3, 1, 4, 1, 17] -0.85185 [2, 3, 1, 3, 1, 18] 0.85185 [1, 3, 2, 3, 1, 18] 0.85185 [2, 4, 1, 3, 0, 19] -5.0526 [1, 3, 2, 4, 0, 19] -5.0526 [2, 4, 1, 3, 1, 20] 1.7698 [1, 3, 2, 4, 1, 20] 1.7698 [1, 4, 1, 4, 1, 21] -2.91415 [1, 4, 2, 3, 1, 22] 3.64855 [2, 3, 1, 4, 1, 22] 3.64855 [2, 3, 2, 3, 1, 23] -2.91415 [1, 4, 1, 4, 2, 24] -2.6011 [1, 4, 2, 3, 2, 25] -1.4568 [2, 3, 1, 4, 2, 25] -1.4568 [2, 3, 2, 3, 2, 26] -2.6011 [2, 4, 1, 4, 1, 27] -2.2667 [1, 4, 2, 4, 1, 27] -2.2667 [2, 4, 2, 3, 1, 28] 2.2667 [2, 3, 2, 4, 1, 28] 2.2667 [2, 4, 1, 4, 2, 29] 1.23199 [1, 4, 2, 4, 2, 29] 1.23199 [2, 4, 2, 3, 2, 30] -1.23199 [2, 3, 2, 4, 2, 30] -1.23199 [2, 4, 2, 4, 0, 31] -3.3287 [2, 4, 2, 4, 1, 32] -3.4362 [2, 4, 2, 4, 2, 33] 0.0878 [2, 4, 2, 4, 3, 34] -7.2668 labels[i] [1, 3, 1, 3, 0, 15] ME 0.244 labels[i] [1, 3, 1, 3, 1, 16] ME -4.29215 labels[i] [1, 4, 1, 3, 1, 17] ME -0.85185 labels[i] [1, 3, 1, 4, 1, 17] ME -0.85185 labels[i] [2, 3, 1, 3, 1, 18] ME 0.85185 labels[i] [1, 3, 2, 3, 1, 18] ME 0.85185 labels[i] [2, 4, 1, 3, 0, 19] ME -5.0526 labels[i] [1, 3, 2, 4, 0, 19] ME -5.0526 labels[i] [2, 4, 1, 3, 1, 20] ME 1.7698 labels[i] [1, 3, 2, 4, 1, 20] ME 1.7698 labels[i] [1, 4, 1, 4, 1, 21] ME -2.91415 labels[i] [1, 4, 2, 3, 1, 22] ME 3.64855 labels[i] [2, 3, 1, 4, 1, 22] ME 3.64855 labels[i] [2, 3, 2, 3, 1, 23] ME -2.91415 labels[i] [1, 4, 1, 4, 2, 24] ME -2.6011 labels[i] [1, 4, 2, 3, 2, 25] ME -1.4568 labels[i] [2, 3, 1, 4, 2, 25] ME -1.4568 labels[i] [2, 3, 2, 3, 2, 26] ME -2.6011 labels[i] [2, 4, 1, 4, 1, 27] ME -2.2667 labels[i] [1, 4, 2, 4, 1, 27] ME -2.2667 labels[i] [2, 4, 2, 3, 1, 28] ME 2.2667 labels[i] [2, 3, 2, 4, 1, 28] ME 2.2667 labels[i] [2, 4, 1, 4, 2, 29] ME 1.23199 labels[i] [1, 4, 2, 4, 2, 29] ME 1.23199 labels[i] [2, 4, 2, 3, 2, 30] ME -1.23199 labels[i] [2, 3, 2, 4, 2, 30] ME -1.23199 labels[i] [2, 4, 2, 4, 0, 31] ME -3.3287 labels[i] [2, 4, 2, 4, 1, 32] ME -3.4362 labels[i] [2, 4, 2, 4, 2, 33] ME 0.0878 labels[i] [2, 4, 2, 4, 3, 34] ME -7.2668 2J= 4 En. 0.63221 mu (n=1) -0.12025 Q (n=1) -1.75135 wfl: He6_ckpot_j4.wav wfr: He6_ckpot_j0.wav mdims J2=4 2 J2=0 5 Mtots=(4, 0) Mred.(E2) (1,1) -1.811 B(E2) (1<=1) 3.281 B(E2) (1=>1) 0.656 ──────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 1.36ms / 18.9% 274KiB / 22.4% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────── prep 1 189μs 73.8% 189μs 53.5KiB 87.3% 53.5KiB E2 1 67.1μs 26.2% 67.1μs 7.80KiB 12.7% 7.80KiB ──────────────────────────────────────────────────────────────────── J 0 idx [1, 27, 31] |1 2;M=0> |3 6;M=0> |4 5;M=0> 5.0820 -3.5727 3.5727 -3.5727 0.5937 1.6643 3.5727 1.6643 0.5937 E -3.909812 -0.4899 -0.6165 0.6165 E 2.258000 0.0000 -0.7071 -0.7071 E 7.921112 -0.8718 0.3464 -0.3464 J 1 idx [7, 13] |1 5;M=0> |2 4;M=0> 3.9152 -0.3672 -0.3672 3.9152 E 3.548000 -0.7071 -0.7071 E 4.282400 -0.7071 0.7071 J 2 idx [8, 14, 29, 33] |1 5;M=0> |2 4;M=0> |3 6;M=0> |4 5;M=0> 2.9758 -0.5722 -0.8712 -0.8712 -0.5722 2.9758 -0.8712 -0.8712 -0.8712 -0.8712 2.3019 0.0439 -0.8712 -0.8712 0.0439 2.3019 E 0.632210 0.4958 0.4958 0.5041 0.5041 E 2.258000 0.0000 0.0000 -0.7071 0.7071 E 3.548000 0.7071 -0.7071 -0.0000 0.0000 E 4.117290 0.5041 0.5041 -0.4958 -0.4958 J 0 idx [3, 13, 41, 57, 73, 89] |1 8;M=0> |2 7;M=0> |3 12;M=0> |4 11;M=0> |5 10;M=0> |6 9;M=0> 4.9600 -0.1220 -1.7864 1.7864 -1.7864 1.7864 -0.1220 4.9600 1.7864 -1.7864 1.7864 -1.7864 -1.7864 1.7864 1.4258 0.8322 -0.8322 0.8322 1.7864 -1.7864 0.8322 1.4258 0.8322 -0.8322 -1.7864 1.7864 -0.8322 0.8322 1.4258 0.8322 1.7864 -1.7864 0.8322 -0.8322 0.8322 1.4258 E -3.909812 -0.3464 0.3464 -0.4359 0.4359 -0.4359 0.4359 E 2.258000 0.0000 0.0000 0.6271 -0.1393 -0.7664 0.0000 E 2.258000 -0.0000 -0.0000 -0.5229 -0.8045 -0.2816 0.0000 E 2.258000 -0.0000 0.0000 0.2887 -0.2887 0.2887 0.8660 E 4.838000 -0.7071 -0.7071 0.0000 -0.0000 -0.0000 0.0000 E 7.921112 -0.6165 0.6165 0.2449 -0.2449 0.2449 -0.2449 J 1 idx [4, 9, 14, 19, 42, 47, 58, 65, 74, 90] |1 8;M=0> |1 11;M=0> |2 7;M=0> |2 10;M=0> |3 12;M=0> |4 8;M=0> |4 11;M=0> |5 7;M=0> |5 10;M=0> |6 9;M=0> 2.6919 0.4259 -2.1461 -0.4259 0.8395 -0.4259 -0.2798 0.4259 -0.2798 0.8395 0.4259 2.0909 0.4259 1.4571 1.0752 1.8243 -0.3584 -1.8243 -0.3584 1.0752 -2.1461 0.4259 2.6919 -0.4259 0.8395 -0.4259 -0.2798 0.4259 -0.2798 0.8395 -0.4259 1.4571 -0.4259 2.0909 -1.0752 -1.8243 0.3584 1.8243 0.3584 -1.0752 0.8395 1.0752 0.8395 -1.0752 0.7117 -1.0752 0.5154 1.0752 0.5154 -1.5463 -0.4259 1.8243 -0.4259 -1.8243 -1.0752 2.0909 0.3584 1.4571 0.3584 -1.0752 -0.2798 -0.3584 -0.2798 0.3584 0.5154 0.3584 2.0862 -0.3584 -0.1718 0.5154 0.4259 -1.8243 0.4259 1.8243 1.0752 1.4571 -0.3584 2.0909 -0.3584 1.0752 -0.2798 -0.3584 -0.2798 0.3584 0.5154 0.3584 -0.1718 -0.3584 2.0862 0.5154 0.8395 1.0752 0.8395 -1.0752 -1.5463 -1.0752 0.5154 1.0752 0.5154 0.7117 E -5.432987 -0.0138 -0.3973 -0.0138 0.3973 0.4070 0.3973 -0.1357 -0.3973 -0.1357 0.4070 E -1.272797 0.5382 -0.2027 0.5382 0.2027 -0.3396 0.2027 0.1132 -0.2027 0.1132 -0.3396 E 2.258000 0.0000 0.0000 0.0000 -0.0000 -0.2951 -0.0000 0.0677 -0.0000 -0.9531 0.0000 E 2.258000 0.0000 -0.0000 0.0000 0.0000 0.6068 0.0000 -0.2023 -0.0000 -0.2023 -0.7416 E 2.258000 0.0000 -0.0000 -0.0000 -0.0000 -0.3078 0.0000 -0.9511 -0.0000 0.0278 0.0000 E 3.058734 0.4584 0.2260 0.4584 -0.2260 0.4110 -0.2260 -0.1370 0.2260 -0.1370 0.4110 E 3.548000 -0.0000 -0.6556 0.0000 -0.6556 0.0000 0.2649 0.0000 0.2649 -0.0000 0.0000 E 3.548000 0.0000 0.2649 -0.0000 0.2649 -0.0000 0.6556 -0.0000 0.6556 -0.0000 0.0000 E 4.282400 0.0000 -0.5000 -0.0000 0.5000 -0.0000 -0.5000 -0.0000 0.5000 -0.0000 0.0000 E 4.838000 0.7071 -0.0000 -0.7071 -0.0000 0.0000 -0.0000 0.0000 -0.0000 0.0000 0.0000 J 2 idx [10, 20, 43, 48, 59, 66, 75, 91] |1 11;M=0> |2 10;M=0> |3 12;M=0> |4 8;M=0> |4 11;M=0> |5 7;M=0> |5 10;M=0> |6 9;M=0> 2.2474 -1.3006 -0.4356 -0.7284 -0.4356 -0.7284 0.4356 0.4356 -1.3006 2.2474 -0.4356 -0.7284 -0.4356 -0.7284 0.4356 0.4356 -0.4356 -0.4356 2.2799 0.4356 0.0220 0.4356 -0.0220 -0.0220 -0.7284 -0.7284 0.4356 2.2474 0.4356 -1.3006 -0.4356 -0.4356 -0.4356 -0.4356 0.0220 0.4356 2.2799 0.4356 -0.0220 -0.0220 -0.7284 -0.7284 0.4356 -1.3006 0.4356 2.2474 -0.4356 -0.4356 0.4356 0.4356 -0.0220 -0.4356 -0.0220 -0.4356 2.2799 0.0220 0.4356 0.4356 -0.0220 -0.4356 -0.0220 -0.4356 0.0220 2.2799 E -0.509900 -0.5000 -0.5000 -0.0000 -0.5000 0.0000 -0.5000 0.0000 0.0000 E 0.632213 0.3506 0.3506 0.3565 -0.3506 0.3565 -0.3506 -0.3565 -0.3565 E 2.258000 0.0000 0.0000 0.3437 -0.0000 0.4029 -0.0000 -0.0963 0.8428 E 2.258000 0.0000 0.0000 0.0812 -0.0000 -0.6375 -0.0000 -0.7431 0.1868 E 2.258000 0.0000 0.0000 -0.7908 0.0000 0.4258 -0.0000 -0.4343 0.0693 E 3.548000 0.7004 -0.7004 -0.0000 0.0975 0.0000 -0.0975 0.0000 0.0000 E 3.548000 0.0975 -0.0975 -0.0000 -0.7004 -0.0000 0.7004 -0.0000 -0.0000 E 4.117287 -0.3565 -0.3565 0.3506 0.3565 0.3506 0.3565 -0.3506 -0.3506 J 0 idx [1, 27, 31] |7 8;M=0> |9 12;M=0> |10 11;M=0> 5.0820 -3.5727 3.5727 -3.5727 0.5937 1.6643 3.5727 1.6643 0.5937 E -3.909812 -0.4899 -0.6165 0.6165 E 2.258000 0.0000 -0.7071 -0.7071 E 7.921112 -0.8718 0.3464 -0.3464 J 1 idx [7, 13] |7 11;M=0> |8 10;M=0> 3.9152 -0.3672 -0.3672 3.9152 E 3.548000 -0.7071 -0.7071 E 4.282400 -0.7071 0.7071 J 2 idx [8, 14, 29, 33] |7 11;M=0> |8 10;M=0> |9 12;M=0> |10 11;M=0> 2.9758 -0.5722 -0.8712 -0.8712 -0.5722 2.9758 -0.8712 -0.8712 -0.8712 -0.8712 2.3019 0.0439 -0.8712 -0.8712 0.0439 2.3019 E 0.632210 0.4958 0.4958 0.5041 0.5041 E 2.258000 0.0000 0.0000 -0.7071 0.7071 E 3.548000 0.7071 -0.7071 -0.0000 0.0000 E 4.117290 0.5041 0.5041 -0.4958 -0.4958 sampling... O20 Z,N=(8,12) c(8,8) v(0,4) mdim: 81 ( 1.91 ) sntf: interaction_file/random_snts/tmp_0.snt labels[i] [1, 4, 1, 4, 0, 31] ME -0.8286883336720193 labels[i] [1, 4, 1, 4, 1, 32] ME -4.9505916626687005 labels[i] [1, 5, 1, 4, 1, 33] ME 0.6575442821581348 labels[i] [1, 4, 1, 5, 1, 33] ME 0.6575442821581348 labels[i] [2, 4, 1, 4, 1, 34] ME -0.6575442821581348 labels[i] [1, 4, 2, 4, 1, 34] ME -0.6575442821581348 labels[i] [2, 5, 1, 4, 0, 35] ME -2.3728603419417698 labels[i] [1, 4, 2, 5, 0, 35] ME -2.3728603419417698 labels[i] [2, 5, 1, 4, 1, 36] ME -0.5134224656800418 labels[i] [1, 4, 2, 5, 1, 36] ME -0.5134224656800418 labels[i] [2, 6, 1, 4, 1, 37] ME -1.5761161850044243 labels[i] [1, 4, 2, 6, 1, 37] ME -1.5761161850044243 labels[i] [3, 5, 1, 4, 1, 38] ME 1.5761161850044243 labels[i] [1, 4, 3, 5, 1, 38] ME 1.5761161850044243 labels[i] [3, 6, 1, 4, 0, 39] ME -2.8154862958231273 labels[i] [1, 4, 3, 6, 0, 39] ME -2.8154862958231273 labels[i] [3, 6, 1, 4, 1, 40] ME 0.4642999373073406 labels[i] [1, 4, 3, 6, 1, 40] ME 0.4642999373073406 labels[i] [1, 5, 1, 5, 1, 41] ME -1.4000211252068215 labels[i] [1, 5, 1, 5, 2, 42] ME -1.102069252915439 labels[i] [1, 6, 1, 5, 2, 43] ME -0.06902345012369304 labels[i] [1, 5, 1, 6, 2, 43] ME -0.06902345012369304 labels[i] [2, 4, 1, 5, 1, 44] ME 1.5873455756127004 labels[i] [1, 5, 2, 4, 1, 44] ME 1.5873455756127004 labels[i] [2, 4, 1, 5, 2, 45] ME -2.5879627585891742 labels[i] [1, 5, 2, 4, 2, 45] ME -2.5879627585891742 labels[i] [2, 5, 1, 5, 1, 46] ME 0.03297119606554287 labels[i] [1, 5, 2, 5, 1, 46] ME 0.03297119606554287 labels[i] [2, 5, 1, 5, 2, 47] ME 0.9274081446364085 labels[i] [1, 5, 2, 5, 2, 47] ME 0.9274081446364085 labels[i] [2, 6, 1, 5, 1, 48] ME 1.2449702728304235 labels[i] [1, 5, 2, 6, 1, 48] ME 1.2449702728304235 labels[i] [2, 6, 1, 5, 2, 49] ME 0.21396881983880364 labels[i] [1, 5, 2, 6, 2, 49] ME 0.21396881983880364 labels[i] [3, 4, 1, 5, 2, 50] ME -0.8494515641064767 labels[i] [1, 5, 3, 4, 2, 50] ME -0.8494515641064767 labels[i] [3, 5, 1, 5, 1, 51] ME -0.7249884478390762 labels[i] [1, 5, 3, 5, 1, 51] ME -0.7249884478390762 labels[i] [3, 5, 1, 5, 2, 52] ME 0.8929836193290698 labels[i] [1, 5, 3, 5, 2, 52] ME 0.8929836193290698 labels[i] [3, 6, 1, 5, 1, 53] ME -0.5447077998251015 labels[i] [1, 5, 3, 6, 1, 53] ME -0.5447077998251015 labels[i] [3, 6, 1, 5, 2, 54] ME 0.11725460322809281 labels[i] [1, 5, 3, 6, 2, 54] ME 0.11725460322809281 labels[i] [1, 6, 1, 6, 2, 55] ME 0.26164770783132096 labels[i] [1, 6, 1, 6, 3, 56] ME -0.1520279275534626 labels[i] [2, 4, 1, 6, 2, 57] ME 0.8494515641064767 labels[i] [1, 6, 2, 4, 2, 57] ME 0.8494515641064767 labels[i] [2, 5, 1, 6, 2, 58] ME -1.4205421341009796 labels[i] [1, 6, 2, 5, 2, 58] ME -1.4205421341009796 labels[i] [2, 5, 1, 6, 3, 59] ME -0.9914321421683235 labels[i] [1, 6, 2, 5, 3, 59] ME -0.9914321421683235 labels[i] [2, 6, 1, 6, 2, 60] ME 0.6621755580086577 labels[i] [1, 6, 2, 6, 2, 60] ME 0.6621755580086577 labels[i] [2, 6, 1, 6, 3, 61] ME -0.7807866018624267 labels[i] [1, 6, 2, 6, 3, 61] ME -0.7807866018624267 labels[i] [3, 4, 1, 6, 2, 62] ME 0.6398039765466128 labels[i] [1, 6, 3, 4, 2, 62] ME 0.6398039765466128 labels[i] [3, 4, 1, 6, 3, 63] ME -2.59088879479599 labels[i] [1, 6, 3, 4, 3, 63] ME -2.59088879479599 labels[i] [3, 5, 1, 6, 2, 64] ME -0.4973777108506151 labels[i] [1, 6, 3, 5, 2, 64] ME -0.4973777108506151 labels[i] [3, 5, 1, 6, 3, 65] ME 0.39692359365768287 labels[i] [1, 6, 3, 5, 3, 65] ME 0.39692359365768287 labels[i] [3, 6, 1, 6, 2, 66] ME -1.3836760156674237 labels[i] [1, 6, 3, 6, 2, 66] ME -1.3836760156674237 labels[i] [3, 6, 1, 6, 3, 67] ME -1.9653855779886489 labels[i] [1, 6, 3, 6, 3, 67] ME -1.9653855779886489 labels[i] [2, 4, 2, 4, 1, 68] ME -1.4000211252068215 labels[i] [2, 4, 2, 4, 2, 69] ME -1.102069252915439 labels[i] [2, 5, 2, 4, 1, 70] ME -0.03297119606554287 labels[i] [2, 4, 2, 5, 1, 70] ME -0.03297119606554287 labels[i] [2, 5, 2, 4, 2, 71] ME -0.9274081446364085 labels[i] [2, 4, 2, 5, 2, 71] ME -0.9274081446364085 labels[i] [2, 6, 2, 4, 1, 72] ME -0.7249884478390762 labels[i] [2, 4, 2, 6, 1, 72] ME -0.7249884478390762 labels[i] [2, 6, 2, 4, 2, 73] ME 0.8929836193290698 labels[i] [2, 4, 2, 6, 2, 73] ME 0.8929836193290698 labels[i] [3, 4, 2, 4, 2, 74] ME 0.06902345012369304 labels[i] [2, 4, 3, 4, 2, 74] ME 0.06902345012369304 labels[i] [3, 5, 2, 4, 1, 75] ME 1.2449702728304235 labels[i] [2, 4, 3, 5, 1, 75] ME 1.2449702728304235 labels[i] [3, 5, 2, 4, 2, 76] ME 0.21396881983880364 labels[i] [2, 4, 3, 5, 2, 76] ME 0.21396881983880364 labels[i] [3, 6, 2, 4, 1, 77] ME 0.5447077998251015 labels[i] [2, 4, 3, 6, 1, 77] ME 0.5447077998251015 labels[i] [3, 6, 2, 4, 2, 78] ME -0.11725460322809281 labels[i] [2, 4, 3, 6, 2, 78] ME -0.11725460322809281 labels[i] [2, 5, 2, 5, 0, 79] ME -0.8103570075021671 labels[i] [2, 5, 2, 5, 1, 80] ME -1.540403041102693 labels[i] [2, 5, 2, 5, 2, 81] ME -0.5793164135030677 labels[i] [2, 5, 2, 5, 3, 82] ME -3.1928868333326856 labels[i] [2, 6, 2, 5, 1, 83] ME 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1.5651290159364473 labels[i] [3, 6, 2, 5, 2, 93] ME -1.123074704890196 labels[i] [2, 5, 3, 6, 2, 93] ME -1.123074704890196 labels[i] [3, 6, 2, 5, 3, 94] ME 0.47888167403335935 labels[i] [2, 5, 3, 6, 3, 94] ME 0.47888167403335935 labels[i] [2, 6, 2, 6, 1, 95] ME -2.525740889317086 labels[i] [2, 6, 2, 6, 2, 96] ME -0.9595364097417097 labels[i] [2, 6, 2, 6, 3, 97] ME -1.7037088035724919 labels[i] [2, 6, 2, 6, 4, 98] ME -4.185491327756058 labels[i] [3, 4, 2, 6, 2, 99] ME 0.4973777108506151 labels[i] [2, 6, 3, 4, 2, 99] ME 0.4973777108506151 labels[i] [3, 4, 2, 6, 3, 100] ME -0.39692359365768287 labels[i] [2, 6, 3, 4, 3, 100] ME -0.39692359365768287 labels[i] [3, 5, 2, 6, 1, 101] ME 4.595126707848649 labels[i] [2, 6, 3, 5, 1, 101] ME 4.595126707848649 labels[i] [3, 5, 2, 6, 2, 102] ME -1.8182699032724563 labels[i] [2, 6, 3, 5, 2, 102] ME -1.8182699032724563 labels[i] [3, 5, 2, 6, 3, 103] ME 0.7799146043173492 labels[i] [2, 6, 3, 5, 3, 103] ME 0.7799146043173492 labels[i] [3, 5, 2, 6, 4, 104] ME -1.4779777057367534 labels[i] [2, 6, 3, 5, 4, 104] ME -1.4779777057367534 labels[i] [3, 6, 2, 6, 1, 105] ME -3.1425628861201 labels[i] [2, 6, 3, 6, 1, 105] ME -3.1425628861201 labels[i] [3, 6, 2, 6, 2, 106] ME -0.5281689130534641 labels[i] [2, 6, 3, 6, 2, 106] ME -0.5281689130534641 labels[i] [3, 6, 2, 6, 3, 107] ME -1.4495505857672257 labels[i] [2, 6, 3, 6, 3, 107] ME -1.4495505857672257 labels[i] [3, 6, 2, 6, 4, 108] ME 0.8355383588316839 labels[i] [2, 6, 3, 6, 4, 108] ME 0.8355383588316839 labels[i] [3, 4, 3, 4, 2, 109] ME 0.26164770783132096 labels[i] [3, 4, 3, 4, 3, 110] ME -0.1520279275534626 labels[i] [3, 5, 3, 4, 2, 111] ME -0.6621755580086577 labels[i] [3, 4, 3, 5, 2, 111] ME -0.6621755580086577 labels[i] [3, 5, 3, 4, 3, 112] ME 0.7807866018624267 labels[i] [3, 4, 3, 5, 3, 112] ME 0.7807866018624267 labels[i] [3, 6, 3, 4, 2, 113] ME -1.3836760156674237 labels[i] [3, 4, 3, 6, 2, 113] ME -1.3836760156674237 labels[i] [3, 6, 3, 4, 3, 114] ME -1.9653855779886489 labels[i] [3, 4, 3, 6, 3, 114] ME -1.9653855779886489 labels[i] [3, 5, 3, 5, 1, 115] ME -2.525740889317086 labels[i] [3, 5, 3, 5, 2, 116] ME -0.9595364097417097 labels[i] [3, 5, 3, 5, 3, 117] ME -1.7037088035724919 labels[i] [3, 5, 3, 5, 4, 118] ME -4.185491327756058 labels[i] [3, 6, 3, 5, 1, 119] ME 3.1425628861201 labels[i] [3, 5, 3, 6, 1, 119] ME 3.1425628861201 labels[i] [3, 6, 3, 5, 2, 120] ME 0.5281689130534641 labels[i] [3, 5, 3, 6, 2, 120] ME 0.5281689130534641 labels[i] [3, 6, 3, 5, 3, 121] ME 1.4495505857672257 labels[i] [3, 5, 3, 6, 3, 121] ME 1.4495505857672257 labels[i] [3, 6, 3, 5, 4, 122] ME -0.8355383588316839 labels[i] [3, 5, 3, 6, 4, 122] ME -0.8355383588316839 labels[i] [3, 6, 3, 6, 0, 123] ME -3.6223068688369247 labels[i] [3, 6, 3, 6, 1, 124] ME -0.4616355003640481 labels[i] [3, 6, 3, 6, 2, 125] ME 0.7674837948691882 labels[i] [3, 6, 3, 6, 3, 126] ME -0.6087124196337927 labels[i] [3, 6, 3, 6, 4, 127] ME 0.6530002060621195 labels[i] [3, 6, 3, 6, 5, 128] ME -6.022073179475143 J 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0.5235473260645531 labels[i] [3, 6, 3, 6, 5, 128] ME -3.598385069516964 J [0.0, 0.0, 0.0] En. -23.408900741228265 -20.345926548593102 -14.688548713140861 sntf: interaction_file/random_snts/tmp_4.snt labels[i] [1, 4, 1, 4, 0, 31] ME -0.865263786257216 labels[i] [1, 4, 1, 4, 1, 32] ME -4.252373539463505 labels[i] [1, 5, 1, 4, 1, 33] ME -0.27362314078371913 labels[i] [1, 4, 1, 5, 1, 33] ME -0.27362314078371913 labels[i] [2, 4, 1, 4, 1, 34] ME 0.27362314078371913 labels[i] [1, 4, 2, 4, 1, 34] ME 0.27362314078371913 labels[i] [2, 5, 1, 4, 0, 35] ME 0.027429167223494522 labels[i] [1, 4, 2, 5, 0, 35] ME 0.027429167223494522 labels[i] [2, 5, 1, 4, 1, 36] ME -1.6531038793731587 labels[i] [1, 4, 2, 5, 1, 36] ME -1.6531038793731587 labels[i] [2, 6, 1, 4, 1, 37] ME -1.9152360302850784 labels[i] [1, 4, 2, 6, 1, 37] ME -1.9152360302850784 labels[i] [3, 5, 1, 4, 1, 38] ME 1.9152360302850784 labels[i] [1, 4, 3, 5, 1, 38] ME 1.9152360302850784 labels[i] [3, 6, 1, 4, 0, 39] ME -3.1741388861135182 labels[i] [1, 4, 3, 6, 0, 39] ME -3.1741388861135182 labels[i] [3, 6, 1, 4, 1, 40] ME 1.4010675222609146 labels[i] [1, 4, 3, 6, 1, 40] ME 1.4010675222609146 labels[i] [1, 5, 1, 5, 1, 41] ME -3.165273577738563 labels[i] [1, 5, 1, 5, 2, 42] ME -1.7386371496836532 labels[i] [1, 6, 1, 5, 2, 43] ME -0.16965196682564082 labels[i] [1, 5, 1, 6, 2, 43] ME -0.16965196682564082 labels[i] [2, 4, 1, 5, 1, 44] ME 2.6083965677288243 labels[i] [1, 5, 2, 4, 1, 44] ME 2.6083965677288243 labels[i] [2, 4, 1, 5, 2, 45] ME -1.2988984765626632 labels[i] [1, 5, 2, 4, 2, 45] ME -1.2988984765626632 labels[i] [2, 5, 1, 5, 1, 46] ME -0.2812676525955656 labels[i] [1, 5, 2, 5, 1, 46] ME -0.2812676525955656 labels[i] [2, 5, 1, 5, 2, 47] ME -0.1840302374578082 labels[i] [1, 5, 2, 5, 2, 47] ME -0.1840302374578082 labels[i] [2, 6, 1, 5, 1, 48] ME 0.9129039188032854 labels[i] [1, 5, 2, 6, 1, 48] ME 0.9129039188032854 labels[i] [2, 6, 1, 5, 2, 49] ME -0.31397724939758515 labels[i] [1, 5, 2, 6, 2, 49] ME -0.31397724939758515 labels[i] [3, 4, 1, 5, 2, 50] ME -1.1770804195153313 labels[i] [1, 5, 3, 4, 2, 50] ME -1.1770804195153313 labels[i] [3, 5, 1, 5, 1, 51] ME -1.9168734478975016 labels[i] [1, 5, 3, 5, 1, 51] ME -1.9168734478975016 labels[i] [3, 5, 1, 5, 2, 52] ME -1.699678237141911 labels[i] [1, 5, 3, 5, 2, 52] ME -1.699678237141911 labels[i] [3, 6, 1, 5, 1, 53] ME 0.7449668804829638 labels[i] [1, 5, 3, 6, 1, 53] ME 0.7449668804829638 labels[i] [3, 6, 1, 5, 2, 54] ME -1.5230115345092021 labels[i] [1, 5, 3, 6, 2, 54] ME -1.5230115345092021 labels[i] [1, 6, 1, 6, 2, 55] ME -0.8069659059379767 labels[i] [1, 6, 1, 6, 3, 56] ME -0.641887081793187 labels[i] [2, 4, 1, 6, 2, 57] ME 1.1770804195153313 labels[i] [1, 6, 2, 4, 2, 57] ME 1.1770804195153313 labels[i] [2, 5, 1, 6, 2, 58] ME -0.9578699255444505 labels[i] [1, 6, 2, 5, 2, 58] ME -0.9578699255444505 labels[i] [2, 5, 1, 6, 3, 59] ME -0.06511883889406807 labels[i] [1, 6, 2, 5, 3, 59] ME -0.06511883889406807 labels[i] [2, 6, 1, 6, 2, 60] ME -0.18404961518103213 labels[i] [1, 6, 2, 6, 2, 60] ME -0.18404961518103213 labels[i] [2, 6, 1, 6, 3, 61] ME 0.34318916715768266 labels[i] [1, 6, 2, 6, 3, 61] ME 0.34318916715768266 labels[i] [3, 4, 1, 6, 2, 62] ME -0.7743919531985247 labels[i] [1, 6, 3, 4, 2, 62] ME -0.7743919531985247 labels[i] [3, 4, 1, 6, 3, 63] ME -2.8094792016237045 labels[i] [1, 6, 3, 4, 3, 63] ME -2.8094792016237045 labels[i] [3, 5, 1, 6, 2, 64] ME 1.3815153995279539 labels[i] [1, 6, 3, 5, 2, 64] ME 1.3815153995279539 labels[i] [3, 5, 1, 6, 3, 65] ME 1.3542509429518628 labels[i] [1, 6, 3, 5, 3, 65] ME 1.3542509429518628 labels[i] [3, 6, 1, 6, 2, 66] ME -1.9859744089140905 labels[i] [1, 6, 3, 6, 2, 66] ME -1.9859744089140905 labels[i] [3, 6, 1, 6, 3, 67] ME 0.060322852396141616 labels[i] [1, 6, 3, 6, 3, 67] ME 0.060322852396141616 labels[i] [2, 4, 2, 4, 1, 68] ME -3.165273577738563 labels[i] [2, 4, 2, 4, 2, 69] ME -1.7386371496836532 labels[i] [2, 5, 2, 4, 1, 70] ME 0.2812676525955656 labels[i] [2, 4, 2, 5, 1, 70] ME 0.2812676525955656 labels[i] [2, 5, 2, 4, 2, 71] ME 0.1840302374578082 labels[i] [2, 4, 2, 5, 2, 71] ME 0.1840302374578082 labels[i] [2, 6, 2, 4, 1, 72] ME -1.9168734478975016 labels[i] [2, 4, 2, 6, 1, 72] ME -1.9168734478975016 labels[i] [2, 6, 2, 4, 2, 73] ME -1.699678237141911 labels[i] [2, 4, 2, 6, 2, 73] ME -1.699678237141911 labels[i] [3, 4, 2, 4, 2, 74] ME 0.16965196682564082 labels[i] [2, 4, 3, 4, 2, 74] ME 0.16965196682564082 labels[i] [3, 5, 2, 4, 1, 75] ME 0.9129039188032854 labels[i] [2, 4, 3, 5, 1, 75] ME 0.9129039188032854 labels[i] [3, 5, 2, 4, 2, 76] ME -0.31397724939758515 labels[i] [2, 4, 3, 5, 2, 76] ME -0.31397724939758515 labels[i] [3, 6, 2, 4, 1, 77] ME -0.7449668804829638 labels[i] [2, 4, 3, 6, 1, 77] ME -0.7449668804829638 labels[i] [3, 6, 2, 4, 2, 78] ME 1.5230115345092021 labels[i] [2, 4, 3, 6, 2, 78] ME 1.5230115345092021 labels[i] [2, 5, 2, 5, 0, 79] ME -3.7682501912980686 labels[i] [2, 5, 2, 5, 1, 80] ME -3.2824991143818205 labels[i] [2, 5, 2, 5, 2, 81] ME 0.8666977377757881 labels[i] [2, 5, 2, 5, 3, 82] ME -2.581267755215301 labels[i] [2, 6, 2, 5, 1, 83] ME -1.4074137266167566 labels[i] [2, 5, 2, 6, 1, 83] ME -1.4074137266167566 labels[i] [2, 6, 2, 5, 2, 84] ME 0.4140147455412026 labels[i] [2, 5, 2, 6, 2, 84] ME 0.4140147455412026 labels[i] [2, 6, 2, 5, 3, 85] ME -1.3691524121110767 labels[i] [2, 5, 2, 6, 3, 85] ME -1.3691524121110767 labels[i] [3, 4, 2, 5, 2, 86] ME -0.9578699255444505 labels[i] [2, 5, 3, 4, 2, 86] ME -0.9578699255444505 labels[i] [3, 4, 2, 5, 3, 87] ME -0.06511883889406807 labels[i] [2, 5, 3, 4, 3, 87] ME -0.06511883889406807 labels[i] [3, 5, 2, 5, 1, 88] ME 1.4074137266167566 labels[i] [2, 5, 3, 5, 1, 88] ME 1.4074137266167566 labels[i] [3, 5, 2, 5, 2, 89] ME -0.4140147455412026 labels[i] [2, 5, 3, 5, 2, 89] ME -0.4140147455412026 labels[i] [3, 5, 2, 5, 3, 90] ME 1.3691524121110767 labels[i] [2, 5, 3, 5, 3, 90] ME 1.3691524121110767 labels[i] [3, 6, 2, 5, 0, 91] ME -3.286190570655982 labels[i] [2, 5, 3, 6, 0, 91] ME -3.286190570655982 labels[i] [3, 6, 2, 5, 1, 92] ME 3.235566268733425 labels[i] [2, 5, 3, 6, 1, 92] ME 3.235566268733425 labels[i] [3, 6, 2, 5, 2, 93] ME -0.14824927152479328 labels[i] [2, 5, 3, 6, 2, 93] ME -0.14824927152479328 labels[i] [3, 6, 2, 5, 3, 94] ME 1.4008446784438393 labels[i] [2, 5, 3, 6, 3, 94] ME 1.4008446784438393 labels[i] [2, 6, 2, 6, 1, 95] ME -4.090617994851622 labels[i] [2, 6, 2, 6, 2, 96] ME -2.2162398939842323 labels[i] [2, 6, 2, 6, 3, 97] ME -0.30488909720555485 labels[i] [2, 6, 2, 6, 4, 98] ME -2.644274422277959 labels[i] [3, 4, 2, 6, 2, 99] ME -1.3815153995279539 labels[i] [2, 6, 3, 4, 2, 99] ME -1.3815153995279539 labels[i] [3, 4, 2, 6, 3, 100] ME -1.3542509429518628 labels[i] [2, 6, 3, 4, 3, 100] ME -1.3542509429518628 labels[i] [3, 5, 2, 6, 1, 101] ME 3.1464384307648885 labels[i] [2, 6, 3, 5, 1, 101] ME 3.1464384307648885 labels[i] [3, 5, 2, 6, 2, 102] ME -1.0915859046512848 labels[i] [2, 6, 3, 5, 2, 102] ME -1.0915859046512848 labels[i] [3, 5, 2, 6, 3, 103] ME 2.803200819299146 labels[i] [2, 6, 3, 5, 3, 103] ME 2.803200819299146 labels[i] [3, 5, 2, 6, 4, 104] ME -1.4810878303141968 labels[i] [2, 6, 3, 5, 4, 104] ME -1.4810878303141968 labels[i] [3, 6, 2, 6, 1, 105] ME -1.247218088724401 labels[i] [2, 6, 3, 6, 1, 105] ME -1.247218088724401 labels[i] [3, 6, 2, 6, 2, 106] ME 0.9096290835784387 labels[i] [2, 6, 3, 6, 2, 106] ME 0.9096290835784387 labels[i] [3, 6, 2, 6, 3, 107] ME -1.205178118190052 labels[i] [2, 6, 3, 6, 3, 107] ME -1.205178118190052 labels[i] [3, 6, 2, 6, 4, 108] ME 1.6558845826557949 labels[i] [2, 6, 3, 6, 4, 108] ME 1.6558845826557949 labels[i] [3, 4, 3, 4, 2, 109] ME -0.8069659059379767 labels[i] [3, 4, 3, 4, 3, 110] ME -0.641887081793187 labels[i] [3, 5, 3, 4, 2, 111] ME 0.18404961518103213 labels[i] [3, 4, 3, 5, 2, 111] ME 0.18404961518103213 labels[i] [3, 5, 3, 4, 3, 112] ME -0.34318916715768266 labels[i] [3, 4, 3, 5, 3, 112] ME -0.34318916715768266 labels[i] [3, 6, 3, 4, 2, 113] ME -1.9859744089140905 labels[i] [3, 4, 3, 6, 2, 113] ME -1.9859744089140905 labels[i] [3, 6, 3, 4, 3, 114] ME 0.060322852396141616 labels[i] [3, 4, 3, 6, 3, 114] ME 0.060322852396141616 labels[i] [3, 5, 3, 5, 1, 115] ME -4.090617994851622 labels[i] [3, 5, 3, 5, 2, 116] ME -2.2162398939842323 labels[i] [3, 5, 3, 5, 3, 117] ME -0.30488909720555485 labels[i] [3, 5, 3, 5, 4, 118] ME -2.644274422277959 labels[i] [3, 6, 3, 5, 1, 119] ME 1.247218088724401 labels[i] [3, 5, 3, 6, 1, 119] ME 1.247218088724401 labels[i] [3, 6, 3, 5, 2, 120] ME -0.9096290835784387 labels[i] [3, 5, 3, 6, 2, 120] ME -0.9096290835784387 labels[i] [3, 6, 3, 5, 3, 121] ME 1.205178118190052 labels[i] [3, 5, 3, 6, 3, 121] ME 1.205178118190052 labels[i] [3, 6, 3, 5, 4, 122] ME -1.6558845826557949 labels[i] [3, 5, 3, 6, 4, 122] ME -1.6558845826557949 labels[i] [3, 6, 3, 6, 0, 123] ME -1.7704456823557593 labels[i] [3, 6, 3, 6, 1, 124] ME 0.5826784484824222 labels[i] [3, 6, 3, 6, 2, 125] ME -0.4687180582024001 labels[i] [3, 6, 3, 6, 3, 126] ME -1.463580057381362 labels[i] [3, 6, 3, 6, 4, 127] ME 0.6029669246978929 labels[i] [3, 6, 3, 6, 5, 128] ME -2.813984522273272 J [0.0, 0.0, 0.0] En. -28.599774628745756 -20.891012289992609 -18.778717056216323 make TDmat... O20 Z,N=(8,12) c(8,8) v(0,4) mdim: 81 ( 1.91 ) Dim 15 solving EC vals [-23.632085643518984, -18.25445671219643, -13.962557528463073] ln 3 num_ev_target 3 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 9 lmax 40 e2max 8 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 1.11 MB d6j_lj 0.28 MB d9j_lsj 0.46 KB dictHOB 0.46 KB ModelSpace: {e1max 2 e3max 4} File: {e1max 4 e2max 8 e3max 4} Reading 3nf... interaction_file/small_3BME_N3LOlnl_4_8_4.me3j.gz size of dict_idx_ThBME: 733 1.0922551155090332e-5 GB count_ME (File) 24890 Allocating v3bme... # of 3BME: 13260 Mem. 9.87947e-05 GB Storing 3BME to v3bme... Building V3monopole... Number of keys for V3mono: 1928 norm(Vmon3) = 16.64280445859748 target: He6 Ref. => Z=2 N=4 E: 8.160870 = E1b 67.69872 + E2b -59.53581 ( -5.785 -37.223 -16.528), + E3b -0.00204 EMP2 -9.58767 1b -0.00000 pp -0.00728 pn -10.38129 nn -5.17598 EMP3 -0.82059 pp 0.787 hh -1.462 ph -0.145 E_HF 8.16087 E_MBPT(3) = -2.2474 Eexp: -29.271 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). N3max 5 J12max 18 jmax_9j 10 hit 5257 14513 size d6j_int 0.07 MB d6j_lj 0.28 MB d9j_int 2.30 MB d9j_lsj 0.53 MB num6j 554006 maxj36 80 lmin 10 lmax 20 jmax 20 Lammax 5 HOB # 616 size HOB 0.07 MB Calculating CFPsCalculating inner integrals... Xmax_tpe 11 N3max 5 L3max 4 nch_integ 1595 chs 0.15 MB Calculating JacobiHO matrix elements # matrix element: |NiJT> 296 # matrix element:|(nlsjtNJT)JT> 893 J = 1 P = 1 T = 1 dimp 44 dimo 15 normC 3.87298 normV 11.36065 normCVC 3.62208 J = 1 P = -1 T = 1 dimp 68 dimo 23 normC 4.79583 normV 14.97909 normCVC 5.12019 J = 3 P = 1 T = 1 dimp 61 dimo 20 normC 4.47214 normV 8.94593 normCVC 2.59556 J = 3 P = -1 T = 1 dimp 100 dimo 33 normC 5.74456 normV 12.40079 normCVC 3.94982 J = 5 P = 1 T = 1 dimp 54 dimo 18 normC 4.24264 normV 5.12539 normCVC 1.60243 J = 5 P = -1 T = 1 dimp 96 dimo 32 normC 5.65685 normV 8.82962 normCVC 3.30004 J = 7 P = 1 T = 1 dimp 36 dimo 12 normC 3.46410 normV 1.88857 normCVC 0.61117 J = 7 P = -1 T = 1 dimp 74 dimo 25 normC 5.00000 normV 3.96749 normCVC 1.37854 J = 9 P = 1 T = 1 dimp 18 dimo 6 normC 2.44949 normV 0.59146 normCVC 0.26294 J = 9 P = -1 T = 1 dimp 46 dimo 15 normC 3.87298 normV 1.33756 normCVC 0.39467 J = 1 P = 1 T = 3 dimp 22 dimo 7 normC 2.64575 normV 1.77115 normCVC 0.60613 J = 1 P = -1 T = 3 dimp 34 dimo 11 normC 3.31662 normV 3.70179 normCVC 1.47068 J = 3 P = 1 T = 3 dimp 29 dimo 9 normC 3.00000 normV 2.25832 normCVC 0.77588 J = 3 P = -1 T = 3 dimp 50 dimo 17 normC 4.12311 normV 2.83248 normCVC 1.12464 J = 5 P = 1 T = 3 dimp 27 dimo 9 normC 3.00000 normV 1.24458 normCVC 0.52630 J = 5 P = -1 T = 3 dimp 48 dimo 16 normC 4.00000 normV 1.98330 normCVC 0.75215 J = 7 P = 1 T = 3 dimp 17 dimo 5 normC 2.23607 normV 0.46380 normCVC 0.08991 J = 7 P = -1 T = 3 dimp 37 dimo 12 normC 3.46410 normV 0.90028 normCVC 0.38426 J = 9 P = 1 T = 3 dimp 9 dimo 3 normC 1.73205 normV 0.11571 normCVC 0.02684 J = 9 P = -1 T = 3 dimp 23 dimo 8 normC 2.82843 normV 0.31217 normCVC 0.16329 Preparing lab kets... emax 2 e2max 4 J 1 P 1 T 1 nlab 8 ndim 10 ndim123 29 J 1 P -1 T 1 nlab 14 ndim 25 ndim123 73 J 3 P 1 T 1 nlab 8 ndim 11 ndim123 34 J 3 P -1 T 1 nlab 17 ndim 32 ndim123 98 J 5 P 1 T 1 nlab 4 ndim 7 ndim123 21 J 5 P -1 T 1 nlab 9 ndim 25 ndim123 75 J 7 P 1 T 1 nlab 1 ndim 2 ndim123 6 J 7 P -1 T 1 nlab 3 ndim 13 ndim123 38 J 9 P 1 T 1 nlab 0 ndim 0 ndim123 0 J 9 P -1 T 1 nlab 1 ndim 3 ndim123 10 J 1 P 1 T 3 nlab 4 ndim 4 ndim123 14 J 1 P -1 T 3 nlab 7 ndim 10 ndim123 35 J 3 P 1 T 3 nlab 3 ndim 4 ndim123 15 J 3 P -1 T 3 nlab 8 ndim 15 ndim123 47 J 5 P 1 T 3 nlab 2 ndim 3 ndim123 10 J 5 P -1 T 3 nlab 4 ndim 10 ndim123 35 J 7 P 1 T 3 nlab 0 ndim 0 ndim123 2 J 7 P -1 T 3 nlab 1 ndim 5 ndim123 18 J 9 P 1 T 3 nlab 0 ndim 0 ndim123 0 J 9 P -1 T 3 nlab 0 ndim 1 ndim123 4 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB # of two-body states 78 # of sp states 6 # of channels 2bstate 31 #TBME = 890 E(2H): bare = -2.224578 srg = -2.224578 Diff.1.486e-10 it = 1 -0.8100 -3.2000 5.4000 1.2640 -0.1200 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -4.47e+00 logllh -3.57e-01 logpost -4.83e+00 Acc.Rate 0.00 it = 2 -0.8100 -3.2000 5.4000 1.2640 -0.1200 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -4.47e+00 logllh -3.57e-01 logpost -4.83e+00 Acc.Rate 0.00 it = 3 -0.8252 -3.6084 5.4106 0.1010 0.1640 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -2.80e+00 logllh -3.57e-01 logpost -3.16e+00 Acc.Rate 33.33 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB # of two-body states 78 # of sp states 6 # of channels 2bstate 31 #TBME = 890 E(2H): bare = -2.224578 srg = -2.224578 Diff.1.486e-10 it = 1 -0.9667 -3.0000 6.0000 2.0000 0.5000 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -7.03e-01 logllh -3.57e-01 logpost -1.06e+00 it = 2 -1.2000 -4.0000 4.6667 -2.0000 -1.5000 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -4.44e-01 logllh -3.57e-01 logpost -8.01e-01 it = 3 -0.9667 -3.0000 6.0000 2.0000 0.5000 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -7.03e-01 logllh -3.57e-01 logpost -1.06e+00 Since optional_parameters.jl is not found, the default parameters will be used. You can specify the parameters with optional argument, fn_params like make_chiEFTint(;fn_params="PATH_TO_YOUR_FILE"). size of dWS (jmax 5 lmax 40 e2max 4 Nnmax 20): dtri 4.46 MB dcgm0 1.11 MB d6j_int 0.07 MB d6j_lj 0.02 MB d9j_lsj 0.83 MB dictHOB 0.03 MB # of two-body states 78 # of sp states 6 # of channels 2bstate 31 #TBME = 890 E(2H): bare = -2.224578 srg = -2.224578 Diff.1.486e-10 it = 1 -0.9667 -3.0000 2.0000 2.0000 1.5000 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -8.71e-01 logllh -3.57e-01 logpost -1.23e+00 it = 2 -0.7333 -5.0000 3.3333 -2.0000 0.5000 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -2.69e-01 logllh -3.57e-01 logpost -6.26e-01 it = 3 -1.2000 -4.0000 6.0000 0.6667 -0.5000 E: -21.634862 = E1b 51.94183 + E2b -73.57669 ( -9.101 -54.336 -10.141), + E3b 0.00000 EMP2 -3.03824 1b -0.00000 pp -0.04171 pn -2.96288 nn -0.03366 EMP3 -0.24071 pp -0.208 hh -0.621 ph 0.589 E_HF -21.63486 E_MBPT(3) = -24.9138 Eexp: -28.296 eval: logprior -3.21e-01 logllh -3.57e-01 logpost -6.79e-01 Test Summary: | Pass Total Time NuclearToolkit.jl | 30 30 22m15.0s Testing NuclearToolkit tests passed Testing completed after 1351.22s PkgEval succeeded after 2093.66s