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 134 tok/s
Gemini 2.5 Pro 41 tok/s Pro
GPT-5 Medium 26 tok/s Pro
GPT-5 High 35 tok/s Pro
GPT-4o 99 tok/s Pro
Kimi K2 192 tok/s Pro
GPT OSS 120B 440 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Quasi-Invariance under Flows Generated by Non-Linear PDEs (1311.0200v7)

Published 1 Nov 2013 in math.AP

Abstract: The paper is concerned with the change of probability measures $\mu$ along non-random probability measure valued trajectories $\nu_t$, $t\in [-1,1]$. Typically solutions to non-linear PDEs, modeling spatial development as time progresses, generate such trajectories. Depending on in which direction the map $\nu\equiv\nu_0\mapsto\nu_t$ does not exit the state space, for $t\in [-1,0]$ or for $t\in [0,1]$, quasi-invariance of the measure $\mu$ under the map $\nu\mapsto\nu_t$ is established and the Radon-Nikodym derivative of $\mu\circ\nu_t$ with respect to $\mu$ is determined. It is also investigated how Fr\'echet differentiability of the solution map of the PDE can contribute to the existence of this Radon-Nikodym derivative. The first application is a certain Boltzmann type equation. Here the Fr\'echet derivative of the solution map is calculated explicitly and quasi-invariance is established. The second application is a PDE related to the asymptotic behavior of a Fleming-Viot type particle system. Here quasi-invariance is obtained and it is demonstrated how this result can be used in order to derive a corresponding integration by parts formula.

Summary

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

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

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

Authors (1)

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

Collections

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