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The identification of trajectories that contribute to the reaction rate is the crucial dynamical ingredient in any classical chemical reactivity calculation. This problem often requires a full scale numerical simulation of the dynamics, in…

Statistical Mechanics · Physics 2012-06-20 Thomas Bartsch , F. Revuelta , R. M. Benito , F. Borondo

Ab initio instanton rate theory is a computational method for rigorously including tunnelling effects into calculations of chemical reaction rates based on a potential-energy surface computed on the fly from electronic-structure theory.…

Chemical Physics · Physics 2018-05-08 Gabriel Laude , Danilo Calderini , David P. Tew , Jeremy O. Richardson

The efficiency of path sampling simulations can be improved considerably using the approach of path swapping. For this purpose, we have devised a new algorithmic procedure based on the transition interface sampling technique. In the same…

Statistical Mechanics · Physics 2009-11-13 Titus S. van Erp

Many problems in materials science and biology involve particles interacting with strong, short-ranged bonds, that can break and form on experimental timescales. Treating such bonds as constraints can significantly speed up sampling their…

Numerical Analysis · Mathematics 2020-12-02 Miranda Holmes-Cerfon

A combinatorial intervention, consisting of multiple treatments applied to a single unit with potentially interactive effects, has substantial applications in fields such as biomedicine, engineering, and beyond. Given $p$ possible…

Machine Learning · Computer Science 2025-06-05 Divya Shyamal , Jiaqi Zhang , Caroline Uhler

We present an efficient sampling method for computing a partition function and accelerating configuration sampling. The method performs a random walk in the $\lambda$ space, with $\lambda$ being any thermodynamic variable that characterizes…

Computational Physics · Physics 2010-03-02 Cheng Zhang , Jianpeng Ma

The use of random sampling in decision-making and control has become popular with the ease of access to graphic processing units that can generate and calculate multiple random trajectories for real-time robotic applications. In contrast to…

Robotics · Computer Science 2022-03-21 Hyung-Jin Yoon , Chuyuan Tao , Hunmin Kim , Naira Hovakimyan , Petros Voulgaris

In many practical applications of RL, it is expensive to observe state transitions from the environment. For example, in the problem of plasma control for nuclear fusion, computing the next state for a given state-action pair requires…

Machine Learning · Computer Science 2022-03-16 Viraj Mehta , Biswajit Paria , Jeff Schneider , Stefano Ermon , Willie Neiswanger

Previous proposals to permit non-exponential free-path statistics in radiative transfer have not included support for volume and boundary sources that are spatially uncorrelated from the scattering events in the medium. Birth-collision free…

Computational Physics · Physics 2021-02-19 Eugene d'Eon

Modern potential energy surfaces have shifted attention to molecular simulations of chemical reactions. While various methods can estimate rate constants for conformational transitions in molecular dynamics simulations, their applicability…

Chemical Physics · Physics 2024-07-10 Simon Ghysbrecht , Luca Donati , Bettina G. Keller

The quantum instanton approximation is a type of quantum transition state theory that calculates the chemical reaction rate using the reactive flux correlation function and its low order derivatives at time zero. Here we present several…

Chemical Physics · Physics 2009-11-11 Sandy Yang , Takeshi Yamamoto , William H. Miller

The interplay between stochastic chemical reactions and diffusion can generate rich spatiotemporal patterns. While the timescale for individual reaction or diffusion events may be very fast, the timescales for organization can be much…

Statistical Mechanics · Physics 2023-12-12 Schuyler B. Nicholson , Todd R. Gingrich

Continuous-time quantum Monte Carlo refers to a class of algorithms designed to sample the thermal distribution of a quantum Hamiltonian through exact expansions of the Boltzmann exponential in terms of stochastic trajectories which are…

Statistical Mechanics · Physics 2024-07-17 Luke Causer , Konstantinos Sfairopoulos , Jamie F. Mair , Juan P. Garrahan

Random batch algorithms are constructed for quantum Monte Carlo simulations. The main objective is to alleviate the computational cost associated with the calculations of two-body interactions, including the pairwise interactions in the…

Computational Physics · Physics 2020-09-01 Shi Jin , Xiantao Li

We present a method to sample reactive pathways via biased molecular dynamics simulations in trajectory space. We show that the use of enhanced sampling techniques enables unconstrained exploration of multiple reaction routes. Time…

Computational Physics · Physics 2020-07-15 Davide Mandelli , Barak Hirshberg , Michele Parrinello

Finding representative reaction pathways is necessary for understanding mechanisms of molecular processes, but is considered to be extremely challenging. We propose a new method to construct reaction paths based on mean first-passage times.…

Chemical Physics · Physics 2015-06-26 Sanghyun Park , Klaus Schulten

Sequential experimental design to discover interventions that achieve a desired outcome is a key problem in various domains including science, engineering and public policy. When the space of possible interventions is large, making an…

Machine Learning · Computer Science 2023-08-17 Jiaqi Zhang , Louis Cammarata , Chandler Squires , Themistoklis P. Sapsis , Caroline Uhler

Reaction-diffusion models are widely used to study spatially-extended chemical reaction systems. In order to understand how the dynamics of a reaction-diffusion model are affected by changes in its input parameters, efficient methods for…

Quantitative Methods · Quantitative Biology 2017-03-08 Christopher Lester , Christian A. Yates , Ruth E. Baker

Rate-equation models are a widely-used and inexpensive tool for the simulation of interstellar chemistry under a range of physical conditions. However, their application to grain-surface chemical systems necessitates a number of simplifying…

Astrophysics of Galaxies · Physics 2017-05-24 Eric R. Willis , Robin T. Garrod

Understanding causality should be a core requirement of any attempt to build real impact through AI. Due to the inherent unobservability of counterfactuals, large randomised trials (RCTs) are the standard for causal inference. But large…