Coder Social home page Coder Social logo

reform's Introduction

Replica Exchange FOR openmM (REFORM)

A simple implementation of replica exchange MD simulations for OpenMM.

Core ideas of parallel tempering/replica exchange

Run simulations of multiple replicas of a MD system at different temperatures in parallel. Attempt to exchange configurations (atomic positions and scaled velocities) every certain time interval.

Steps for each attempt of exchanging:

  • Propose a pair (or multiple pairs) of replicas for checking.
  • For each proposed pair (assuming the replicas are A and B), extract from the simulation context the corresponding potential energies U_A and U_B. Then calculate the swapping probability p=e^{(\beta_A - \beta_B)(U_A-U_B)}, where \beta_A=1/(k_B \times T_A) is the inverse temperature and similarly for \beta_B. After that, generate a random number from U(0, 1) and test if it is smaller than p. This serves as the acceptance criterion for the swapping similar to the Metropolis-Hastings algorithm.
  • Perform the swapping(s) between the replicas when the proposal(s) got accepted. In case when Langevin integrator is used, the velocities should be scaled by a factor \sqrt{\frac{\beta_{old}}{\beta_{new}}}

Physcially, swappings following the above process will not affect the fact that each replica samples the Boltzmann distribution of the conformational space of the system at its temperature. However, the exchange can help the simulation at lower temperature to faster get out of local energy minima, thus exploring the conformational space more efficiently. One need to note that the kinetics are not preserved when replica exchange method is used.

References and continue reading:

Design goals and road maps

  • An abstract class for holding and enabling access to multiple replicas.
  • Core replica exchange functionalities.
  • Implementation of the multiple replicas with OpenMM.
  • Interfaces to the users.
  • Some test systems.
  • Implementation of multiple replicas with the replicated_systems (speedups for small systems and for neural network force fields).
  • Implementation of multiple replicas with concurrency in Python.

Copyright

Copyright (c) 2020-2021, noegroup, published under the MIT License (a copy can be found in this repo)

Acknowledgements

Project based on the Computational Molecular Science Python Cookiecutter version 1.3.

reform's People

Contributors

yaoyic avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.