42 lines
1.1 KiB
Julia
42 lines
1.1 KiB
Julia
using Arpack, SparseArrays, LRUCache
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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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V_of_r(r) = 2 * exp(-(r-3)^2 / (1.5)^2)
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E_max = 30
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μω_global = 0.5 * exp(-2im * pi / 9)
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# due to Jacobi coordinates
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μ1ω1 = μω_global * 1/2
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μ2ω2 = μω_global * 2
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μ1 = m * 1/2
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μ2 = m * 2/3
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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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l_max = max(maximum(l1s), maximum(l2s))
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n_max = max(maximum(n1s), maximum(n2s))
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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=μ1ω1, μ=μ1)
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@time "T2" T2 = get_sp_T_matrix(n2s, l2s; mask=mask2, μω_gen=μ2ω2, μ=μ2)
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println("Constructing PE matrices")
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@time "V" V = get_jacobi_V_matrix(V_of_r, E_max, Λ, μ1ω1, μω_global)
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println("Calculating spectrum")
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@time "H" H = T1 + T2 + V
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@time "Eigenvalues" evals, _ = eigs(H, nev=5, ncv=50, which=:LI, maxiter=5000, tol=1e-5, ritzvec=false, check=1)
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display(evals) |