Accelerating multi-species field-theoretic simulations using Bayesian optimization

Field-theoretic simulations can be stabilized and accelerated through judiciously chosen relaxation coefficients. We demonstrate how these optimal coefficients can be obtained using Bayesian optimization.

Authors

Institutions

Publication Details

Journal
Molecular Systems Design & Engineering
Published
2025-01-01
DOI
https://doi.org/10.1039/d5me00100e
Citations
1
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
1.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accelerating multi-species field-theoretic simulations using Bayesian optimization

Joshua Lequieu, Andrew Golembeski, Ritvind Suketana
1 citations
Molecular Systems Design & Engineering
Probabilistic and Robust Engineering Design
1.40
article

Accelerating multi-species field-theoretic simulations using Bayesian optimization

Joshua Lequieu, Andrew Golembeski, Ritvind Suketana
article en
1 citations

Abstract

Field-theoretic simulations can be stabilized and accelerated through judiciously chosen relaxation coefficients. We demonstrate how these optimal coefficients can be obtained using Bayesian optimization.

Molecular Systems Design & EngineeringVol. 10(11)
Drexel University (US)
National Science Foundation, Drexel University, Division of Materials Research
Openalex Percentile: Top 14%
Probabilistic and Robust Engineering Design
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.