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#!/usr/bin/env julia
using Plots
using LinearAlgebra
using DifferentialEquations
# useful functions:
function H(psi, dx) # action of Hamiltonian on wavefunction
Hpsi = zeros(ComplexF64, size(psi))
# -(1/2) * laplacian(psi) (m = hbar = 1)
Hpsi[2:end-1] = 0.5 * (2.0 * psi[2:end-1] - psi[3:end] - psi[1:end-2]) / (dx * dx)
# periodic boundary conditions
#Hpsi[1] = 0.5 * (2.0*psi[1] - psi[2] - psi[end])/(dx*dx)
#Hpsi[end] = 0.5 * (2.0*psi[end] - psi[end-1] - psi[1])/(dx*dx)
return Hpsi
end
derivative(psi, dx) = -1.0im * H(psi, dx)
function initialWavefunction(x::Vector{Float64}, x0 = 10.0, Delta = 1.0, k = 4.0)
Delta2 = Delta^2
return exp.(-(x .- x0) .^ 2 / Delta2) .* exp.(1.0im * k * x)
end
function normalization(psi, dx) # normalization of wavefunction
n2 = dot(psi, psi) * dx
return sqrt(n2)
end
prob(psi) = real(psi .* conj(psi))
# The actual simulation
N = 400 # number of lattice points
L = 20.0 # x runs from 0 to L
dx = L / N
x = range(0.0, L, N) |> collect # lattice along x-axis
#println(x)
# initial wavefunction has position (x0), width (Delta), and momentum (k)
psi0 = initialWavefunction(x, 10.0, 1.0, 0.0)
# normalize wavefunction
n = normalization(psi0, dx)
psi0 = psi0 / n
println("norm = ", normalization(psi0, dx))
# plot initial wavefunction and probability density
plot(prob(psi0))
# integrate forward in time
tf = 1.0
dt = 0.0001
tspan = (0.0, tf)
function timeEvolve(psi0, tf, dt) # second order Runge-Kutta algorithm
psi = psi0
for t in range(0, stop = tf, step = dt)
psiMid = psi + 0.5 * dt * derivative(psi, dx)
psi = psi + dt * derivative(psiMid, dx)
end
return psi
end
tendency(psi, dx, t) = derivative(psi, dx) # use ODE solver
problem = ODEProblem(tendency, psi0, tspan, dx) # specify ODE
sol = solve(problem, Tsit5(), reltol = 1e-12, abstol = 1e-12) # solve using Tsit5 algorithm to specified accuracy
# compare initial and final wavefunction probabilities
#psi = timeEvolve(psi0, tf, dt)
psi = sol[:, end]
times = sol.t
# check that normalization hasn't deviated too far from 1.0
println("norm = ", normalization(psi, dx))
plot([prob(psi0), prob(psi)])
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