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Related papers: Enhanced sampling of transition states

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The determination of efficient collective variables is crucial to the success of many enhanced sampling methods. As inspired by previous discrimination approaches, we first collect a set of data from the different metastable basins. The…

Computational Physics · Physics 2026-03-03 Enrico Trizio , Michele Parrinello

We introduce a path sampling method for obtaining statistical properties of an arbitrary stochastic dynamics. The method works by decomposing a trajectory in time, estimating the probability of satisfying a progress constraint, modifying…

Statistical Mechanics · Physics 2015-06-04 Nicholas Guttenberg , Aaron R. Dinner , Jonathan Weare

We extend the weighted ensemble (WE) path sampling method to perform rigorous statistical sampling for systems at steady state. The straightforward steady-state implementation of WE is directly practical for simple landscapes, but not when…

Biological Physics · Physics 2015-05-14 Divesh Bhatt , Bin W. Zhang , Daniel M. Zuckerman

The density of states of continuous models is known to span many orders of magnitudes at different energies due to the small volume of phase space near the ground state. Consequently, the traditional Wang-Landau sampling which uses the same…

Statistical Mechanics · Physics 2013-11-20 Yang Wei Koh , Hwee Kuan Lee , Yutaka Okabe

The sampling problem lies at the heart of atomistic simulations and over the years many different enhanced sampling methods have been suggested towards its solution. These methods are often grouped into two broad families. On the one hand…

Computational Physics · Physics 2020-11-25 Michele Invernizzi , Pablo Miguel Piaggi , Michele Parrinello

The computational study of conformational transitions in RNA and proteins with atomistic molecular dynamics often requires suitable enhanced sampling techniques. We here introduce a novel method where concurrent metadynamics are integrated…

Computational Physics · Physics 2015-09-01 Alejandro Gil-Ley , Giovanni Bussi

We address the problem of efficient phase diagram sampling by adopting active learning techniques from machine learning, and achieve an 80% reduction in the sample size (number of sampled statepoints) needed to establish the phase boundary…

Computational Physics · Physics 2018-03-12 Chengyu Dai , Isaac R. Bruss , Sharon C. Glotzer

Thermodynamic phase transitions, a central concept in physics and chemistry, are typically controlled by an interplay of enthalpic and entropic contributions. In most cases, the estimation of the enthalpy in simulations is straightforward…

Soft Condensed Matter · Physics 2025-10-30 Yamin Ben-Shimon , Barak Hirshberg , Yohai Bar-Sinai

Methods that combine collective variable (CV) based enhanced sampling and global tempering approaches are used in speeding-up the conformational sampling and free energy calculation of large and soft systems with a plethora of energy…

Computational Physics · Physics 2021-09-01 Anji Babu Kapakayala , Nisanth N. Nair

Metadynamics (MTD) is a very powerful technique to sample high-dimensional free energy landscapes, and due to its self-guiding property, the method has been successful in studying complex reactions and conformational changes. MTD sampling…

Computational Physics · Physics 2016-02-05 Shalini Awasthi , Venkat Kapil , Nisanth N. Nair

Target search by active agents in rugged energy landscapes has remained a challenge because standard enhanced sampling methods do not apply to irreversible dynamics. We overcome this non-equilibrium rare-event problem by developing an…

Soft Condensed Matter · Physics 2021-01-20 Luigi Zanovello , Michele Caraglio , Thomas Franosch , Pietro Faccioli

We investigate the kinetics and the free energy landscape of the crystallization of hard spheres from a supersaturated metastable liquid though direct simulations and forward flux sampling. In this first paper, we describe and test two…

Soft Condensed Matter · Physics 2018-08-17 David Richard , Thomas Speck

Exploring the free-energy landscape along reaction coordinates or system parameters $\lambda$ is central to many studies of high-dimensional model systems in physics, e.g. large molecules or spin glasses. In simulations this usually…

Statistical Mechanics · Physics 2018-09-05 Viveca Lindahl , Jack Lidmar , Berk Hess

Nested sampling is a Bayesian sampling technique developed to explore probability distributions lo- calised in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence…

Biomolecules · Quantitative Biology 2015-03-17 Nikolas S. Burkoff , Csilla Varnai , Stephen A. Wells , David L. Wild

Metadynamics, a member of the `flat histogram' class of advanced sampling algorithms, has been widely used in molecular simulations to drive the exploration of states separated by high free energy barriers and promote comprehensive sampling…

Computational Physics · Physics 2021-09-13 Shanghui Huang , Michael J. Quevillon , Ernesto C. Cortés-Morales , Jonathan K. Whitmer

To address the time-scale limitations in molecular dynamics (MD) simulations, numerous enhanced sampling methods have been developed to expedite the exploration of complex free energy landscapes. A commonly employed approach accelerates the…

Computational Physics · Physics 2025-06-24 Zhijun Pan , Maodong Li , Dechin Chen , Yi Isaac Yang

Many physical and chemical processes, such as folding of biopolymers, are best described as dynamics on large combinatorial energy landscapes. A concise approximate description of dynamics is obtained by partitioning the micro-states of the…

Biomolecules · Quantitative Biology 2011-01-19 Martin Mann , Konstantin Klemm

The use of external restraints is ubiquitous in advanced molecular simulation techniques. In general, restraints serve to reduce the configurational space that is available for sampling, thereby reducing the computational demands associated…

Molecular systems often remain trapped for long times around some local minimum of the potential energy function, before switching to another one -- a behavior known as metastability. Simulating transition paths linking one metastable state…

Machine Learning · Statistics 2023-02-02 Tony Lelièvre , Geneviève Robin , Inass Sekkat , Gabriel Stoltz , Gabriel Victorino Cardoso

Many problems in physics, material sciences, chemistry and biology can be abstractly formulated as a system that navigates over a complex energy landscape of high or infinite dimensions. Well-known examples include phase transitions of…

Numerical Analysis · Mathematics 2025-10-20 Weinan E , Weiqing Ren , Eric Vanden-Eijnden