Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Sharma, Upanshu"'
We introduce a variational structure for the Fourier-Cattaneo (FC) system which is a second-order hyperbolic system. This variational structure is inspired by the large-deviation rate functional for the Kac process which is closely linked to the FC s
Externí odkaz:
http://arxiv.org/abs/2211.07265
Autor:
Renger, D. R. Michiel, Sharma, Upanshu
Using the theory of large deviations, macroscopic fluctuation theory provides a framework to understand the behaviour of non-equilibrium dynamics and steady states in diffusive systems. We extend this framework to a minimal model of non-equilibrium n
Externí odkaz:
http://arxiv.org/abs/2205.05327
Autor:
Hilder, Bastian, Sharma, Upanshu
Coarse-graining techniques play a central role in reducing the complexity of stochastic models, and are typically characterised by a mapping which projects the full state of the system onto a smaller set of variables which captures the essential feat
Externí odkaz:
http://arxiv.org/abs/2201.10256
Macroscopic equations arising out of stochastic particle systems in detailed balance (called dissipative systems or gradient flows) have a natural variational structure, which can be derived from the large-deviation rate functional for the density of
Externí odkaz:
http://arxiv.org/abs/2103.14384
We study the convergence to equilibrium of an underdamped Langevin equation that is controlled by a linear feedback force. Specifically, we are interested in sampling the possibly multimodal invariant probability distribution of a Langevin system at
Externí odkaz:
http://arxiv.org/abs/2103.05096
Autor:
Sharma, Upanshu, Zhang, Wei
Calculating averages with respect to probability measures on submanifolds is often necessary in various application areas such as molecular dynamics, computational statistical mechanics and Bayesian statistics. In recent years, various numerical sche
Externí odkaz:
http://arxiv.org/abs/2011.02835
This work is concerned with model reduction of stochastic differential equations and builds on the idea of replacing drift and noise coefficients of preselected relevant, e.g. slow variables by their conditional expectations. We extend recent results
Externí odkaz:
http://arxiv.org/abs/1911.06081
In this paper we introduce a new generalisation of the relative Fisher Information for Markov jump processes on a finite or countable state space, and prove an inequality which connects this object with the relative entropy and a large deviation rate
Externí odkaz:
http://arxiv.org/abs/1812.04358
Coarse-graining is central to reducing dimensionality in molecular dynamics, and is typically characterized by a mapping which projects the full state of the system to a smaller class of variables. While extensive literature has been devoted to coars
Externí odkaz:
http://arxiv.org/abs/1809.10498
In this paper we present a variational technique that handles coarse-graining and passing to a limit in a unified manner. The technique is based on a duality structure, which is present in many gradient flows and other variational evolutions, and whi
Externí odkaz:
http://arxiv.org/abs/1507.03207