Shadow hybrid Monte Carlo: an efficient propagator in phase space of macromolecules

DOI10.1016/j.jcp.2004.04.016zbMath1115.65383OpenAlexW2125155341MaRDI QIDQ1887750

Scott S. Hampton, Jesús A. Izaguirre

Publication date: 22 November 2004

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2004.04.016

zbMATH Keywords

Symplectic integratorHybrid Monte CarloSampling methodsConformational samplingModified Hamiltonian

Mathematics Subject Classification ID

Stochastic analysis applied to problems in fluid mechanics (76M35) Numerical methods for Hamiltonian systems including symplectic integrators (65P10)

Related Items (18)

Markov Chain Importance Sampling—A Highly Efficient Estimator for MCMC ⋮ Multiple-time-stepping generalized hybrid Monte Carlo methods ⋮ Thread-Parallel Anisotropic Mesh Adaptation ⋮ Estimating the speed-up of adaptively restrained Langevin dynamics ⋮ Finite element model updating using Hamiltonian Monte Carlo techniques ⋮ Combining stochastic and deterministic approaches within high efficiency molecular simulations ⋮ Optimal tuning of the hybrid Monte Carlo algorithm ⋮ GSHMC: An efficient method for molecular simulation ⋮ On the estimation and correction of discretization error in molecular dynamics averages ⋮ A Metropolis adjusted Nosé-Hoover thermostat ⋮ Theoretical and numerical comparison of some sampling methods for molecular dynamics ⋮ Extra chance generalized hybrid Monte Carlo ⋮ Coupling control variates for Markov chain Monte Carlo ⋮ A comparison of generalized hybrid Monte Carlo methods with and without momentum flip ⋮ Modified Hamiltonian Monte Carlo for Bayesian inference ⋮ Multi-stage splitting integrators for sampling with modified Hamiltonian Monte Carlo methods ⋮ Geometric integrators and the Hamiltonian Monte Carlo method ⋮ Geometric Integration of Measure-Preserving Flows for Sampling

Uses Software

• ProtoMol

Cites Work

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• Molecular modeling and simulation. An interdisciplinary guide
• The Nosé-Poincaré method for constant temperature molecular dynamics
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• Bayesian learning for neural networks
• Practical Construction of Modified Hamiltonians
• Long-Time-Step Methods for Oscillatory Differential Equations
• Backward Error Analysis for Numerical Integrators
• Targeted Mollified Impulse: A Multiscale Stochastic Integrator for Long Molecular Dynamics Simulations
• ProtoMol, an object-oriented framework for prototyping novel algorithms for molecular dynamics
• Monte Carlo sampling methods using Markov chains and their applications

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