Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 71 tok/s
Gemini 2.5 Pro 58 tok/s Pro
GPT-5 Medium 35 tok/s Pro
GPT-5 High 25 tok/s Pro
GPT-4o 101 tok/s Pro
Kimi K2 236 tok/s Pro
GPT OSS 120B 469 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Parareal exponential $θ$-scheme for longtime simulation of stochastic Schrödinger equations with weak damping (1803.09188v1)

Published 25 Mar 2018 in math.NA

Abstract: A parareal algorithm based on an exponential $\theta$-scheme is proposed for the stochastic Schr\"odinger equation with weak damping and additive noise. It proceeds as a two-level temporal parallelizable integrator with the exponential $\theta$-scheme as the propagator on the coarse grid. The proposed algorithm in the linear case increases the convergence order from one to $k$ for $\theta\in[0,1]\setminus{\frac12}$. In particular, the convergence order increases to $2k$ when $\theta=\frac12$ due to the symmetry of the algorithm. Furthermore, the algorithm is proved to be suitable for longtime simulation based on the analysis of the invariant distributions for the exponential $\theta$-scheme. The convergence condition for longtime simulation is also established for the proposed algorithm in the nonlinear case, which indicates the superiority of implicit schemes. Numerical experiments are dedicated to illustrate the best choice of the iteration number $k$, as well as the convergence order of the algorithm for different choices of $\theta$.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.