40 lines
1.0 KiB
Julia
40 lines
1.0 KiB
Julia
using Arpack, SparseArrays
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include("ho_basis.jl")
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include("p_space.jl")
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E_max = 20
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ω = 1.0
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Λ = 0
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m = 1.0
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Va = -5
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Ra = sqrt(3)
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Vb = 2
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Rb = sqrt(10)
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μ1 = m * 1/2
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μ2 = m * 2/3
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c1 = 1/sqrt(2)
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c2 = sqrt(2)
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println("No of threads = ", Threads.nthreads())
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Es, n1s, l1s, n2s, l2s = get_2p_basis(E_max)
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println("Basis size = ", length(Es))
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println("Constructing KE matrices")
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@time "T1" T1 = sp_T_matrix(n1s, l1s; ω=ω, μ=c1^2 * μ1)
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@time "T2" T2 = sp_T_matrix(n2s, l2s; ω=ω, μ=c2^2 * μ2)
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println("Constructing PE matrices")
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V_l(l, n1, n2) = Va * V_Gaussian(Ra, l, n1, n2; ω=ω) + Vb * V_Gaussian(Rb, l, n1, n2; ω=ω)
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@time "V1" V1 = sp_V_matrix(V_l, n1s, l1s)
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@time "V relative" V_relative = V1 + sp_V_matrix(V_l, n2s, l2s)
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@time "Moshinsky brackets" U = Moshinsky_transform(Es, n1s, l1s, n2s, l2s, Λ)
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@time "V2" V2 = U' * V_relative * U
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println("Calculating spectrum")
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@time "H" H = T1 + T2 + V1 + V2
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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) |