A dynamical Monte Carlo algorithm for master equations with time-dependent transition rates
Journal of Statistical Physics, ISSN: 0022-4715, Vol: 89, Issue: 3-4, Page: 709-734
1997
- 30Citations
- 44Captures
- 1Mentions
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
A Monte Carlo algorithm for simulating master equations with time-dependent transition rates is described. It is based on a waiting time image, and takes into account that the system can become frozen when the transition rates tend to zero fast enough in time. An analytical justification is provided. The algorithm reduces to the Bortz-Kalos Lebowitz one when the transition rates are constant. Since the exact evaluation of waiting times is rather involved in general, a simple and efficient iterative method for accurately calculating them is introduced. As an example, the algorithm is applied to a one-dimensional Ising system with Glauber dynamics. It is shown that it reproduces the exact analytical results, being more efficient than the direct implementation of the Metropolis algorithm.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=0141526060&origin=inward; http://dx.doi.org/10.1007/bf02765541; http://link.springer.com/10.1007/BF02765541; http://www.springerlink.com/index/pdf/10.1007/BF02765541; http://link.springer.com/content/pdf/10.1007/BF02765541; http://link.springer.com/content/pdf/10.1007/BF02765541.pdf; http://link.springer.com/article/10.1007/BF02765541/fulltext.html; http://www.springerlink.com/index/10.1007/BF02765541; https://dx.doi.org/10.1007/bf02765541; https://link.springer.com/article/10.1007/BF02765541
Springer Nature
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know