using NuclearToolkit using SpecialFunctions # Gaussian potentials in HO space N_nl(n, l) = (-1)^n * sqrt(1/sqrt(pi) * (1/2)^(l+1) * 2^(n+2*l+3) * factorial(n) / Iterators.prod((2*n+2*l+1):-2:1)) prefactor(n, l, k) = (-1)^k * binomial(n + l + 1/2, n - k) / factorial(k) Talmi(l, R, k1, k2) = (1/2) / (1 + 1/R^2)^(3/2 + l + k1 + k2) * gamma(3/2 + l + k1 + k2) V_Gaussian(R, l, n1, n2) = N_nl(n1, l) * N_nl(n2, l) * sum([prefactor(n1, l, k1) * prefactor(n2, l, k2) * Talmi(l, R, k1, k2) for (k1, k2) in Iterators.product(0:n1, 0:n2)]) function get_sp_basis(E_max) Es = Int[] ns = Int[] ls = Int[] # E = 2*n + l for E in 0 : E_max for n in 0 : E ÷ 2 l = E - 2*n push!(Es, E) push!(ns, n) push!(ls, l) end end return (Es, ns, ls) end function get_2p_basis(E_max) Es = Int[] n1s = Int[] l1s = Int[] n2s = Int[] l2s = Int[] # E = 2*n1 + l1 + 2*n2 + l2 for E in 0 : 2*E_max for n1 in 0 : E ÷ 2 for n2 in 0 : (E - 2*n1) ÷ 2 for l1 in 0 : (E - 2*n1 - 2*n2) l2 = E - 2*n1 - 2*n2 - l1 push!(Es, E) push!(n1s, n1) push!(l1s, l1) push!(n2s, n2) push!(l2s, l2) end end end end return (Es, n1s, l1s, n2s, l2s) end get_V_matrix(V_l, ls, ns) = throw("unimplemented") function sp_T_matrix(ns, ls) mat = zeros(length(ns), length(ns)) for idx in CartesianIndices(mat) (i, j) = Tuple(idx) if ls[i] == ls[j] mat[idx] = ls[i] if ns[i] == ns[j] mat[idx] += 1/4 * (4*ns[j] + 3) elseif ns[i] == ns[j] + 1 mat[idx] += -1/4 * sqrt((2*ns[j] + 2) * (2*ns[j] + 3)) elseif ns[i] == ns[j] - 1 mat[idx] += -1/4 * sqrt((2*ns[j] + 1) * 2*ns[j]) end end end return mat end get_H_matrix(V_l, ns, ls) = get_T_matrix(ns, ls) + get_V_matrix(V_l, ns, ls) function Moshinsky_transform(Es, n1s, l1s, n2s, l2s, Λ) l_max = 2*max(maximum(l1s), maximum(l2s)) # OPTIMIZE E_max = maximum(Es) # OPTIMIZE j_max = l_max # OPTIMIZE to = 0 # unused dtri = NuclearToolkit.prep_dtri(l_max) ; println("dtri prepared") dcgm0 = NuclearToolkit.prep_dcgm0(l_max) ; println("dcgm0 prepared") d6j = NuclearToolkit.prep_d6j_int(E_max, j_max, to) ; println("d6j prepared") mat = zeros(length(Es), length(Es)) s = hcat(Es, n1s, l1s, n2s, l2s) for idx in CartesianIndices(mat) (i, j) = Tuple(idx) (Elhs, N, L, n, l) = s[i, :] (Erhs, n1, l1, n2, l2) = s[j, :] if Elhs == Erhs mat[i, j] = NuclearToolkit.HObracket_d6j(N, L, n, l, n1, l1, n2, l2, Λ, 1.0, dtri, dcgm0, d6j, to) end end return mat end