Abstract
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.
| Original language | English |
|---|---|
| Journal | Computer Physics Communications |
| DOIs | |
| Publication status | Accepted/In press - jan. 1 2019 |
Fingerprint
ASJC Scopus subject areas
- Hardware and Architecture
- Physics and Astronomy(all)
Cite this
The Monte Carlo wave-function method : A robust adaptive algorithm and a study in convergence. / Kornyik, M.; Vukics, A.
In: Computer Physics Communications, 01.01.2019.Research output: Article
}
TY - JOUR
T1 - The Monte Carlo wave-function method
T2 - A robust adaptive algorithm and a study in convergence
AU - Kornyik, M.
AU - Vukics, A.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
KW - Adaptive stepsize
KW - Markov approximation
KW - Monte Carlo wave function
KW - Open quantum systems
KW - Quantum jumps
KW - Stochastic simulations
UR - http://www.scopus.com/inward/record.url?scp=85059555390&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059555390&partnerID=8YFLogxK
U2 - 10.1016/j.cpc.2018.12.015
DO - 10.1016/j.cpc.2018.12.015
M3 - Article
AN - SCOPUS:85059555390
JO - Computer Physics Communications
JF - Computer Physics Communications
SN - 0010-4655
ER -