English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The Jarzynski estimator is a powerful tool that uses nonequilibriumstatistical physics to numerically obtain partition functions of probabilitydistributions. The estimator reconstructs partition functions with trajectoriesof the simulated Langevin dynamics through the Jarzynski equality. However, theoriginal estimator suffers from slow convergence because it depends on raretrajectories of stochastic dynamics. In this paper, we present a method tosignificantly accelerate the convergence by introducing deterministic virtualtrajectories generated in augmented state space under the Hamiltonian dynamics.We theoretically show that our approach achieves second-order accelerationcompared to a naive estimator with the Langevin dynamics and zero varianceestimation on harmonic potentials. We also present numerical experiments onthree multimodal distributions and a practical example where the proposedmethod outperforms the conventional method, and provide theoreticalexplanations.

Accelerated Jarzynski Estimator with Deterministic Virtual Trajectories