Numerical solution of PDE:s, Part 6: Adiabatic approximation for quantum dynamics

Having solved the time-dependent Schrödinger equation both in real and imaginary time, we can move forward to investigate systems where the potential energy function V has an explicit time dependence in it:


In this kind of systems, the expectation value of the Hamiltonian operator doesn’t have to stay constant.

Time-dependent perturbation theory is one method for finding approximate solutions for this kind of problems, but here I will handle a simpler example, which is called adiabatic approximation.

Suppose that the potential energy function V(x,t) is known. Now, let’s say that we also know the solutions of the time-independent Schrödinger equation


for any value of t. I denote the solutions as \psi_n (x;t), where it is understood that x is a variable and t is a parameter. Now, if the function V(x,t) changes very slowly as a function of time, i.e. its partial derivative with respect to t is small at all points of the domain, we can use the adiabatic approximation, which says that if the initial state \Psi (x,0) is the ground state for the potential V(x,0), then the state at time t is the ground state for the potential V(x,t).


So, we can change a ground state of one potential V_1 (x) into the ground state of another potential $V_2 (x)&bg=ffffff&fg=000000$ by making a continuous change from V_1 (x) to V_2 (x) slowly enough.

Let’s test this by chooosing a function V as


i.e. a Hookean potential that moves to the positive x-direction with constant speed. If we set the wavefunction at t=0 to


which is the ground state corresponding to V(x,0), the time depelopment of the wavepacket should be like


which means that is moves with the same constant speed as the bottom of the potential V. This can be calculated with the R-Code below:

library(graphics) #load the graphics library needed for plotting

lx <- 6.0 #length of the computational domain
lt <- 15.0 #length of the simulation time interval
nx <- 100 #number of discrete lattice points
nt <- 300 #number of timesteps
dx <- lx/nx #length of one discrete lattice cell
dt <- lt/nt #length of timestep

V = c(1:nx) #potential energies at discrete points

for(j in c(1:nx)) {
V[j] = as.complex(2*(j*dx-3)*(j*dx-3)) #harmonic potential

kappa1 = (1i)*dt/(2*dx*dx) #an element needed for the matrices
kappa2 <- c(1:nx) #another element

for(j in c(1:nx)) {
kappa2[j] <- as.complex(kappa1*2*dx*dx*V[j])

psi = as.complex(c(1:nx)) #array for the wave function values

for(j in c(1:nx)) {
psi[j] = as.complex(exp(-(j*dx-3)*(j*dx-3))) #Gaussian initial wavefunction

xaxis <- c(1:nx)*dx #the x values corresponding to the discrete lattice points

A = matrix(nrow=nx,ncol=nx) #matrix for forward time evolution
B = matrix(nrow=nx,ncol=nx) #matrix for backward time evolution

for(j in c(1:nx)) {
for(k in c(1:nx)) {
if(j==k) {
A[j,k] = 1 + 2*kappa1 + kappa2[j]
B[j,k] = 1 - 2*kappa1 - kappa2[j]
if((j==k+1) || (j==k-1)) {
A[j,k] = -kappa1 #off-diagonal elements
B[j,k] = kappa1

for (k in c(1:nt)) { #main time stepping loop

for(j in c(1:nx)) {
V[j] = as.complex(2*(j*dx-3-k*dt*0.05)*(j*dx-3-k*dt*0.05)) #time dependent potential

for(j in c(1:nx)) {
kappa2[j] <- as.complex(kappa1*2*dx*dx*V[j])

for(l in c(1:nx)) {
for(m in c(1:nx)) {
if(l==m) {
A[l,m] = 1 + 2*kappa1 + kappa2[m]
B[l,m] = 1 - 2*kappa1 - kappa2[m]
if((l==m+1) || (l==m-1)) {
A[l,m] = -kappa1
B[l,m] = kappa1
sol <- solve(A,B%*%psi) #solve the system of equations

for (l in c(1:nx)) {
psi[l] <- sol[l]

if(k %% 3 == 1) { #make plots of psi(x) on every third timestep
jpeg(file = paste("plot_",k,".jpg",sep=""))
plot(xaxis,abs(psi)^2,xlab="position (x)", ylab="Abs(Psi)^2",ylim=c(0,2))
title(paste("|psi(x,t)|^2 at t =",k*dt))
lines(xaxis, abs(psi)^2)
lines(xaxis, V)

and in the following sequences of images you see that the approximation is quite good for v = 0.05

As an animation, this process looks like shown below:

By doing the same calculation again, but this time with v = 3, the image sequence looks like this:

where it is obvious that the approximation doesn’t work anymore.



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