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An adaptive Monte Carlo wave-function method and its convergence properties

Miklós Kornyik, András Vukics

Published Mar 22, 2018• 0 citations
OpenAlex

Abstract

We present a version of the Quantum Jump (Monte Carlo wave-function) algorithm which has been upgraded to use adaptive time step. A single parameter describing the maximal allowed total jump probability per time step governs the convergence of ensembles of trajectories to the solution of the full master equation.

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The Monte Carlo wave function method or the quantum-trajectory-jump approach is a powerful tool to study dissipative dynamics governed by the Markovian master equation, in particular for high-dimensional systems and when it is difficult to simulate directly. We extend this method to the non-Markovian case described by the generalized Lindblad master equation. Two examples to illustrate the method are presented and discussed. The results show that the method can correctly reproduce the dissipative dynamics for the system. The difference between this method and the traditional Markovian jump approach and the computational efficiency of this method is also discussed.
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