Fluctuation relations and coarse-graining

Fluctuation relations and coarse-graining

We consider the application of fluctuation relations to the dynamics of coarse-grained systems, as might arise in a hypothetical experiment in which a system is monitored with a low-resolution measuring apparatus. We analyze a stochastic, Markovian jump process with a specific structure that lends itself naturally to coarse-graining. A perturbative analysis yields a reduced stochastic jump proc...

Fluctuation-preserving coarse graining for biochemical systems.

Finite stochastic Markov models play a major role in modeling biological systems. Such models are a coarse-grained description of the underlying microscopic dynamics and can be considered mesoscopic. The level of coarse-graining is to a certain extent arbitrary since it depends on the resolution of accommodating measurements. Here we present a systematic way to simplify such stochastic descript...

Coarse graining

Multiscale simulations For nearly all systems of interest to us, the most transferrable and fundamental description of matter is one that invokes quantum mechanics. At the highest level of accuracy, this amounts to solving Schrodinger’s equation for all of the subatomic particles in a system. Computationally, many approximations need to be made in order to use ab initio methods, and even these ...

Predictive coarse-graining

Brute-force molecular dynamics simulations are limited by the exuberant number of degrees of freedom and the relatively small time-steps. As a result, only relatively small assemblies of molecules over small time spans are accessible with current and foreseeable computational capabilities. In order to overcome this limitation, coarse-grained models have been proposed which employ a much smaller...

Shape-Based Coarse Graining