44 lines
1.4 KiB
Julia
44 lines
1.4 KiB
Julia
using Arpack, SparseArrays
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include("ho_basis.jl")
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Λ = 0
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m = 1.0
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Va = -2
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Ra = 2
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E_max = 40
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μω_global = 0.3
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# due to simple relative coordinates
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μω = μω_global * 2
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μ = m/2
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println("No of threads = ", Threads.nthreads())
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@time "Basis" begin
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Es, n1s, l1s, n2s, l2s = get_2p_basis(E_max, Λ)
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mask1 = (n2s .== n2s') .&& (l2s .== l2s')
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mask2 = (n1s .== n1s') .&& (l1s .== l1s')
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end
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println("Basis size = ", length(Es))
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println("Constructing KE matrices")
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@time "T1" T1 = get_sp_T_matrix(n1s, l1s; mask=mask1, μω_gen=μω, μ=μ)
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@time "T2" T2 = get_sp_T_matrix(n2s, l2s; mask=mask2, μω_gen=μω, μ=μ)
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@time "T_cross" T_cross = get_2p_p1p2_matrix(n1s, l1s, n2s, l2s, Λ, μω, μω) ./ (2*μ)
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println("Constructing PE matrices")
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V_elem(l, n1, n2) = Va * V_Gaussian(Ra, l, n1, n2; μω_gen=μω)
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V_relative_elem(l, n1, n2) = Va * V_Gaussian(Ra, l, n1, n2; μω_gen=μω_global)
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@time "V1" V1 = get_sp_V_matrix(V_elem, n1s, l1s; mask=mask1)
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@time "V2" V2 = get_sp_V_matrix(V_elem, n2s, l2s; mask=mask2)
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@time "V relative" V_relative = get_sp_V_matrix(V_relative_elem, n1s, l1s; mask=mask1)
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@time "Moshinsky brackets" U = Moshinsky_transform(Es, n1s, l1s, n2s, l2s, Λ)
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@time "V12" V12 = U' * V_relative * U
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println("Calculating spectrum")
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@time "H" H = T1 + T2 + T_cross + V1 + V2 + V12
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@time "Eigenvalues" evals, _ = eigs(H, nev=3, ncv=30, which=:SR, maxiter=5000, tol=1e-5, ritzvec=false, check=1)
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display(evals) |