juliaquantumcontrol / krotov.jl Goto Github PK

using Test
using QuantumControl
using LinearAlgebra
using StableRNGs
using QuantumControlTestUtils.DummyOptimization: dummy_control_problem
using QuantumControl.Controls: get_controls, discretize_on_midpoints
using QuantumControl.Functionals: J_T_re

rng = StableRNG(1244561944)

# The problem occurs when the controls are actually pulses (on the midpoints of
# the time grid), so that the optimization does not have to call
# `discretize_on_midpoints` internally
problem = dummy_control_problem(; pulses_as_controls=true)
nt = length(problem.tlist)
guess_pulse = QuantumControl.Controls.get_controls(problem.objectives)[1]
@test length(guess_pulse) == nt - 1
guess_pulse_copy = copy(QuantumControl.Controls.get_controls(problem.objectives)[1])

# Optimizing this should not modify the original generator in any way
res = optimize(problem; method=:krotov, J_T=J_T_re, iter_stop=2)
opt_control = res.optimized_controls[1]
@test length(opt_control) == nt  # optimized_controls are always *on* tlist
opt_pulse = discretize_on_midpoints(opt_control, problem.tlist)
post_pulse = QuantumControl.Controls.get_controls(problem.objectives)[1]

# * The generator should still have the exact same objects as controls
@test guess_pulse ≡ post_pulse
# * These objects should not have been modified
@test norm(guess_pulse_copy - guess_pulse) ≈ 0.0  # FAILS
# * But the values of the optimized pulse should differ from the pulse in the
#   generator
@test norm(post_pulse - opt_pulse) > 0.1  # FAILS