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The Monte Carlo wave-function method: A robust adaptive algorithm and a study in convergence
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DOI：10.1016/j.cpc.2018.12.015.png)
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Abstract
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We present a stepwise adaptive-timestep version of the Quantum Jump (Monte Carlo wave-function) algorithm. Our method has proved to remain robust even for problems where the integrating implementation of the Quantum Jump method is numerically problematic. The only specific parameter of our algorithm is the single a priory parameter of the Quantum Jump method, the maximal allowed total jump probability per timestep. We study the convergence of ensembles of trajectories to the solution of the full master equation as a function of this parameter. This study is expected to pertain to any possible implementation of the Quantum Jump method. (C) 2018 Elsevier B.V. All rights reserved.
Keywords:
Monte Carlo wave function
Quantum jumps
Stochastic simulations
Open quantum systems
Markov approximation
Adaptive stepsize
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