Parallel tempering: theory, applications, and new perspectives.

By D. J. Earl, M. Deem. Physical Chemistry, Chemical Physics - PCCP, 2005

1,474 citations recorded by the source corpus.

We review the history of the parallel tempering simulation method. From its origins in data analysis, the parallel tempering method has become a standard workhorse of physicochemical simulations. We discuss the theory behind the method and its various generalizations. We mention a selected set of the many applications that have become possible with the introduction of parallel tempering, and we suggest several promising avenues for future research.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/05c50bb494617e1fb01c39580777a5d8c9e6f139

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors (2020, methodology): “, 1983; Bertsimas and Tsitsiklis, 1993), parallel tempering (Hansmann, 1997; Earl and Deem, 2005), simulated tempering (Marinari and Parisi, 1992; Neal, 1993), Wang-Landau algorithm (Wang and Landau, 2001), and path sampling (Gelman and Meng, 1998; Yao et al.”
MCMC Using Hamiltonian Dynamics (2011, background): “ng problems with such isolated modes that involve sampling from a series of distributions that are more diﬀuse than the distribution of interest. Such schemes include parallel tempering (Geyer, 1991; Earl and Deem, 2005), simulated tempering (Marinari and Parisi, 1992), tempered transitions (Neal, 1”
Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis (2012, methodology): “In addition, FILM3 uses Replica Exchange Monte Carlo (sometimes called parallel tempering) (53) to identify low energy conformations in place of simulated annealing.”
Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer (2018, methodology): “PT has been used effectively in multiple research fields [39], and often performs better than SA, due to the increased mixing.”
Where are we with light sterile neutrinos? (2019, positive): “After each affine invariant proposal and update step, a parallel tempering update [82] occurs with a probability of 10%.”
Handbook of Markov Chain Monte Carlo (2011, neutral): “Such schemes include parallel tempering (Geyer, 1991; Earl and Deem, 2005), simulated tempering (Marinari and Parisi, 1992), tempered transitions (Neal, 1996b), and annealed importance sampling (Neal, 2001).”
On the inner workings of Monte Carlo codes (2013, background): “[235–239] Open ensembles provide an effective means for overcoming some of the problems associated with slow relaxation phenomena.”
Quantum annealing for industry applications: introduction and review (2021, neutral): “QAGA was tested on three input classes (bimodal spin glasses, anti-cluster inputs, and deceptive cluster loops) against a suite of classical algorithms: simulated annealing (SA) [87], parallel tempering (PT) [156] and parallel tempering with isoenergetic cluster moves (PT-ICM) [49].”
Robustness of community structure in networks. (2007, methodology): “…distribution of modularity values for a variety of networks, both real and computer generated, using a simulated annealing technique similar to that of Reichardt and Bornholdt [29] combined with a parallel tempering scheme of the type commonly used to equilibrate simulations of glassy systems [30].”
Sampling-Based Path Planning on Configuration-Space Costmaps (2010, methodology): “Furthermore, another direction is to incorporate in the planner other methods inspired by Monte Carlo optimization techniques, such as stochastic tunneling [28] or parallel tempering [29].”
Parallel tempering is efficient for learning restricted Boltzmann machines (2010, neutral): “method called parallel tempering (PT) [9].”