Go with the winners: a general Monte Carlo strategy

DOI10.1016/S0010-4655(02)00205-9zbMath1002.65004arXivcond-mat/0201313MaRDI QIDQ696401

Peter Grassberger

Publication date: 12 September 2002

Published in: Computer Physics Communications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/cond-mat/0201313

zbMATH Keywords

reaction-diffusion systemspercolationpolymersMarkov chainstatistical physicsquantum Monte Carlolattice animalssequence alignmentpruned-enriched Rosenbluth methodsequential Monte Carlo simulations with resampling

Mathematics Subject Classification ID

Related Items (17)

Numerical study of extreme mechanical force exerted by a turbulent flow on a bluff body by direct and rare-event sampling techniques ⋮ On the stability of positive semigroups ⋮ Efficient large deviation estimation based on importance sampling ⋮ A review of Monte Carlo simulations of polymers with PERM ⋮ Monte Carlo methods for rough free energy landscapes: population annealing and parallel tempering ⋮ Simulating rare events in dynamical processes ⋮ GPU accelerated population annealing algorithm ⋮ Breakdown of the finite-time and -population scalings of the large deviation function in the large-size limit of a contact process ⋮ Approximate Optimal Controls via Instanton Expansion for Low Temperature Free Energy Computation ⋮ Adaptive sampling of large deviations ⋮ Limit theorems for cloning algorithms ⋮ Computing return times or return periods with rare event algorithms ⋮ Efficient characterisation of large deviations using population dynamics ⋮ Instanton based importance sampling for rare events in stochastic PDEs ⋮ Rare event simulation for stochastic dynamics in continuous time ⋮ Effective driven dynamics for one-dimensional conditioned Langevin processes in the weak-noise limit ⋮ Fast Approximation of the $p$-Radius, Matrix Pressure, or Generalized Lyapunov Exponent for Positive and Dominated Matrices

Cites Work

• Phase transitions of single semistiff polymer chains
• On the number of incipient spanning clusters
• Depth-First Search and Linear Graph Algorithms
• Two-dimensional oriented self-avoiding walks with parallel contacts
• Monte Carlo strategies in scientific computing

This page was built for publication: Go with the winners: a general Monte Carlo strategy