169 lines
6.6 KiB
Julia
169 lines
6.6 KiB
Julia
using DifferentialEquations
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include("bisection.jl")
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const ħc = 197.33 # MeVfm
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const M_n = 939.0 # MeV/c2
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const M_p = 939.0 # MeV/c2
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const r_reg = 1E-8 # fm # regulator for the centrifugal term
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"The spherical Dirac equation that returns du=[dg, df] in-place where
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u=[g, f] are the reduced radial components evaluated at r,
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κ is the generalized angular momentum,
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p is true for proton and false for neutron,
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E in the energy in MeV,
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f1(r) = M-Φ0(r)-W0(r)-(p-0.5)*2B0(r)-p*A0(r) is a function of r in MeV (see optimized_dirac_potentials()),
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f2(r) = -M+Φ0(r)-W0(r)-(p-0.5)*2B0(r)-p*A0(r) is a function of r in MeV (see optimized_dirac_potentials()),
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r is the radius in fm.
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Reference: P. Giuliani, K. Godbey, E. Bonilla, F. Viens, and J. Piekarewicz, Frontiers in Physics 10, (2023)"
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function dirac!(du, u, (κ, E, f1, f2), r)
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(g, f) = u
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@inbounds du[1] = -(κ/(r + r_reg)) * g + (E + f1(r)) * f / ħc
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@inbounds du[2] = (κ/(r + r_reg)) * f - (E + f2(r)) * g / ħc
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end
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"Get the potentials f1 and f2 that goes into the Dirac equation, defined as
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f1(r) = M-Φ0(r)-W0(r)-(p-0.5)*2B0(r)-p*A0(r),
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f2(r) = -M+Φ0(r)-W0(r)-(p-0.5)*2B0(r)-p*A0(r)."
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function optimized_dirac_potentials(p, s::system)
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M = p ? M_p : M_n
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f1s = zero_array(s)
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f2s = zero_array(s)
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@. f1s = M - s.Φ0 - s.W0 - (p - 0.5) * 2 * s.B0 - p * s.A0
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@. f2s = -M + s.Φ0 - s.W0 - (p - 0.5) * 2 * s.B0 - p * s.A0
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f1 = linear_interpolation(rs(s), f1s)
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f2 = linear_interpolation(rs(s), f2s)
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return (f1, f2)
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end
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"Solve the Dirac equation and return the wave function u(r)=[g(r), f(r)] where
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divs is the number of mesh divisions so solution would be returned as a 2×(1+divs) matrix,
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shooting method divides the interval into two partitions at r_max/2, ensuring convergence at both r=0 and r=r_max,
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the other parameters are the same from dirac!(...)."
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function solveNucleonWf(κ, p, E, s::system; shooting=true, normalize=true, algo=Tsit5())
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(f1, f2) = optimized_dirac_potentials(p, s)
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if shooting
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@assert s.divs % 2 == 0 "divs must be an even number when shooting=true"
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prob = ODEProblem(dirac!, [0, 1], (s.r_max, s.r_max / 2))
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sol = solve(prob, algo, p=(κ, E, f1, f2), saveat=Δr(s))
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wf_right = reverse(hcat(sol.u...); dims=2)
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next_r_max = s.r_max / 2 # for the next step
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else
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next_r_max = s.r_max
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end
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prob = ODEProblem(dirac!, [0, 1], (0, next_r_max))
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sol = solve(prob, algo, p=(κ, E, f1, f2), saveat=Δr(s))
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wf = hcat(sol.u...)
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if shooting # join two segments
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rescale_factor_g = wf[1, end] / wf_right[1, 1]
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rescale_factor_f = wf[2, end] / wf_right[2, 1]
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@assert isfinite(rescale_factor_g) && isfinite(rescale_factor_f) "Cannot rescale the right partition"
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isapprox(rescale_factor_g, rescale_factor_f; rtol=0.03) || @warn "Discontinuity between two partitions"
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wf_right_rescaled = wf_right .* ((rescale_factor_g + rescale_factor_f) / 2)
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wf = hcat(wf[:, 1:(end - 1)], wf_right_rescaled)
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end
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if normalize
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norm = sum(wf .* wf) * Δr(s) # integration by Reimann sum
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wf = wf ./ sqrt(norm)
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end
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return wf
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end
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"Returns a function that solves the Dirac equation and returns g(r=r_max) where
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r_max is the outer boundary in fm,
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the other parameters are the same from dirac!(...)."
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function boundaryValueFunc(κ, p, s::system; dtype=Float64, algo=Tsit5())
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prob = ODEProblem(dirac!, convert.(dtype, [0, 1]), (0, s.r_max))
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(f1, f2) = optimized_dirac_potentials(p, s)
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func(E) = solve(prob, algo, p=(κ, E, f1, f2), saveat=[s.r_max], save_idxs=[1])[1, 1]
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return func
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end
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"Find all bound energies between E_min (=850.0) and E_max (=938.0) where
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tol_digits determines the precision for root finding and the threshold for identifying duplicates,
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the other parameters are the same from dirac!(...)."
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function findEs(κ, p, s::system, E_min=850.0, E_max=938.0, tol_digits=5)
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func = boundaryValueFunc(κ, p, s)
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Es = find_all_zeros(func, E_min, E_max; partitions=20, tol=1/10^tol_digits)
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return unique(E -> round(E; digits=tol_digits), Es)
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end
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"Find all orbitals and return two lists containing κ values and corresponding energies for a single species where
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the other parameters are defined above"
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function findAllOrbitals(p, s::system, E_min=850.0, E_max=938.0)
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κs = Int[]
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Es = Float64[]
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# start from κ=-1 and go both up and down
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for direction in [-1, 1]
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for κ in direction * (1:100) # cutoff is 100
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new_Es = findEs(κ, p, s, E_min, E_max)
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if isempty(new_Es); break; end
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append!(Es, new_Es)
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append!(κs, fill(κ, length(new_Es)))
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end
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end
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return (κs, Es)
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end
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"For a given list of κ values with corresponding energies, attempt to fill Z_or_N lowest lying orbitals and return occupancy numbers"
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function fillNucleons(Z_or_N::Int, κs, Es)
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sort_i = sortperm(Es)
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occ = zeros(Int, length(κs))
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for i in sort_i
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if Z_or_N ≤ 0; break; end;
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max_occ = 2 * j_κ(κs[i]) + 1
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occ[i] = min(max_occ, Z_or_N)
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Z_or_N -= occ[i]
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end
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Z_or_N == 0 || @warn "All orbitals could not be filled"
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return occ
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end
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"Total angular momentum j for a given κ value"
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j_κ(κ::Int) = abs(κ) - 1/2
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"Orbital angular momentum l for a given κ value"
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l_κ(κ::Int) = abs(κ) - (κ < 0) # since true = 1 and false = 0
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"Calculate scalar and vector densities of a nucleon species on [0,r_max] divided into (divs+1) points and returns them as vectors (ρ_s, ρ_v) where
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the arrays κs, Es, occs tabulate the energies and occupation numbers corresponding to each κ,
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the other parameters are defined above"
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function calculateNucleonDensity(κs, Es, occs, p, s::system)
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ρr2 = zeros(2, s.divs + 1) # ρ×r² values
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for (κ, E, occ) in zip(κs, Es, occs)
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wf = solveNucleonWf(κ, p, E, s; shooting=true, normalize=true)
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wf2 = wf .* wf
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ρr2 += (occ / (4 * pi)) * wf2 # 2j+1 factor is accounted in the occupancy number
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end
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r2s = rs(s).^2
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ρ = ρr2 ./ transpose(r2s)
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ρ[:, 1] .= ρ[:, 2] # dirty fix for NaN at r=0
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ρ_s = ρ[1, :] - ρ[2, :] # g^2 - f^2
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ρ_v = ρ[1, :] + ρ[2, :] # g^2 + f^2
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return (ρ_s, ρ_v)
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end
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"Solve the Dirac equation and calculate scalar and vector densities of a nucleon species where
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the other parameters are defined above"
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function solveNucleonDensity(p, s::system, E_min=850.0, E_max=938.0)
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κs, Es = findAllOrbitals(p, s, E_min, E_max)
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occs = fillNucleons(Z_or_N(s, p), κs, Es)
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return calculateNucleonDensity(κs, Es, occs, p, s)
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end
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