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Found 6 papers, 1 papers with code
Generative methods for sampling transition paths in molecular dynamics
Molecular systems often remain trapped for long times around some local minimum of the potential energy function, before switching to another one -- a behavior known as metastability.
Chasing Collective Variables using Autoencoders and biased trajectories
In this context, approaches where the CVs are learned in an iterative way using adaptive biasing have been proposed: at each iteration, the learned CV is used to perform free energy adaptive biasing to generate new data and learn a new CV.
Quasi-stationary distribution for the Langevin process in cylindrical domains, part I: existence, uniqueness and long-time convergence
Consider the Langevin process, described by a vector (position, momentum) in $\mathbb{R}^{d}\times\mathbb{R}^d$.
Probability Spectral Theory
The exit from a metastable state: concentration of the exit point distribution on the low energy saddle points, part 2
We consider the first exit point distribution from a bounded domain $\Omega$ of the stochastic process $(X_t)_{t\ge 0}$ solution to the overdamped Langevin dynamics $$d X_t = -\nabla f(X_t) d t + \sqrt{h} \ d B_t$$ starting from deterministic initial conditions in $\Omega$, under rather general assumptions on $f$ (for instance, $f$ may have several critical points in $\Omega$).
Analysis of PDEs Mathematical Physics Mathematical Physics Probability
A new implementation of the Generalized Parallel Replica dynamics for the long time simulation of metastable biochemical systems
Metastability is one of the major encountered obstacle when performing long molecular dynamics simulations, and many methods were developed to address this challenge.
Chemical Physics Computational Physics
Hybrid Monte Carlo methods for sampling probability measures on submanifolds
In order to avoid biases in the invariant probability measures sampled by discretizations of these stochastically perturbed Hamiltonian dynamics, a Metropolis rejection procedure can be considered.
Numerical Analysis Numerical Analysis 65P10, 65C40, 82-08
