Currently, a noisy simulation that requires Hamiltonian randomization (from eg "doppler" or "amplitude" noise) and collapse operators (from eg. "dephasing") is solving the master equation multiple times, each time sampling the final state to give to NoisyResults. This is inefficient because the master equation is wasting significant time to calculate the final density matrix state, which we ultimately ignore.
In this particular case, we could instead use the Monte Carlo solver.
Currently, a noisy simulation that requires Hamiltonian randomization (from eg "doppler" or "amplitude" noise) and collapse operators (from eg. "dephasing") is solving the master equation multiple times, each time sampling the final state to give to
NoisyResults. This is inefficient because the master equation is wasting significant time to calculate the final density matrix state, which we ultimately ignore. In this particular case, we could instead use the Monte Carlo solver.