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Related papers: NATPS: Nonadiabatic Transition Path Sampling Using…

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A general theoretical framework is derived for the recently developed multi-state trajectory (MST) approach from the time dependent Schr\"odinger equation, resulting in equations of motion for coupled nuclear-electronic dynamics equivalent…

Chemical Physics · Physics 2017-09-13 Guohua Tao

Nonadiabatic molecular dynamics is a key technique for investigating a broad range of photochemical and photophysical processes. Among the established approaches, surface hopping schemes are widely used and can be easily integrated with…

Chemical Physics · Physics 2025-12-23 Jakub Martinka , Mikołaj Martyka , Biman Medhi , Jiří Pittner , Pavlo O. Dral

Nonadiabatic molecular dynamics offers a powerful tool for studying the photochemistry of molecular systems. Key to any nonadiabatic molecular dynamics simulation is the definition of its initial conditions, ideally representing the initial…

Chemical Physics · Physics 2023-09-08 Antonio Prlj , Daniel Hollas , Basile F. E. Curchod

Transition path sampling is a method for estimating the rates of rare events in molecular systems based on the gradual transformation of a path distribution containing a small fraction of reactive trajectories into a biased distribution in…

Statistical Mechanics · Physics 2015-10-28 Pierre Terrier , Mihai-Cosmin Marinica , Manuel Athènes

Adiabatic techniques using multi-level systems have recently been generalised from the optical case to settings in atom optics, solid state and even classical electrodynamics. The most well known example of these is the so called STIRAP…

Quantum Physics · Physics 2010-07-23 S. McEndoo , S. Croke , J. Brophy , Th. Busch

We study the exact Time-Dependent Potential Energy Surface (TDPES) in the presence of strong non-adiabatic coupling between the electronic and nuclear motion. The concept of the TDPES emerges from the exact factorization of the full…

Chemical Physics · Physics 2013-02-07 Ali Abedi , Federica Agostini , Yasumitsu Suzuki , E. K. U. Gross

Stochastic systems often exhibit multiple viable metastable states that are long-lived. Over very long timescales, fluctuations may push the system to transition between them, drastically changing its macroscopic configuration. In realistic…

Statistical Mechanics · Physics 2023-04-14 Tobias Grafke , Alessandro Laio

We extend the DeePMD neural network architecture to predict electronic structure properties necessary to perform non-adiabatic dynamics simulations. While learning the excited state energies and forces follows a straightforward extension of…

Chemical Physics · Physics 2024-10-17 Lucien Dupuy , Neepa T. Maitra

Transition interface sampling (TIS) and replica exchange TIS (RETIS) are powerful methods for computing rates of rare events inaccessible to straightforward molecular dynamics (MD) simulations. Path reweighting extends their output,…

Chemical Physics · Physics 2026-05-15 Titus S. van Erp , Daniel T. Zhang , Elias Wils , Sina Safaei , An Ghysels

Nonadiabatic dynamical processes are one of the most important quantum mechanical phenomena in chemical, materials, biological, and environmental molecular systems, where the coupling between different electronic states is either inherent…

Chemical Physics · Physics 2022-05-24 Jian Liu , Xin He , Baihua Wu

The free energy landscapes of several fundamental processes are characterized by high barriers separating long-lived metastable states. In order to explore these type of landscapes enhanced sampling methods are used. While many such methods…

Chemical Physics · Physics 2019-04-12 Jayashrita Debnath , Michele Invernizzi , Michele Parrinello

A time-dependent no-recrossing dividing surface is shown to lead to a new criterion for identifying reactive trajectories well before they are evolved to infinite time. Numerical dynamics simulations of a dissipative anharmonic…

Statistical Mechanics · Physics 2009-11-11 Thomas Bartsch , T. Uzer , Jeremy M. Moix , Rigoberto Hernandez

The modern theory of rare events is grounded in near equilibrium ideas, however many systems of modern interest are sufficiently far from equilibrium that traditional approaches do not apply. Using the recently developed variational path…

Chemical Physics · Physics 2025-02-14 Aditya N. Singh , David T. Limmer

A new methodology of simulating nonadiabatic dynamics using frozen-width Gaussian wavepackets within the moving crude adiabatic representation with the on-the-fly evaluation of electronic structure is presented. The main feature of the new…

Chemical Physics · Physics 2018-04-04 Loïc Joubert-Doriol , Artur F. Izmaylov

The computer simulation of many molecular processes is complicated by long time scales caused by rare transitions between long-lived states. Here, we propose a new approach to simulate such rare events, which combines transition path…

Computational Physics · Physics 2023-03-23 Sebastian Falkner , Alessandro Coretti , Christoph Dellago

The chirped-pulse interaction in the adiabatic coupling regime induces cyclic permutations of the energy states of a three-level system in the $V$-type configuration, which process is known as the three-level chirped rapid adiabatic…

Atomic Physics · Physics 2016-08-24 Yunheung Song , Han-gyeol Lee , Hanlae Jo , Jaewook Ahn

On-the-fly quantum nonadiabatic dynamics for large systems greatly benefits from the adiabatic representation readily available from the electronic structure programs. However, frequently occurring in this representation conical…

The ultrafast nonadiabatic internal conversion in azomethane is explored by the on-the-fly trajectory surface-hopping simulations of photoinduced dynamics and femtosecond transient absorption (TA) pump-probe (PP) spectra at three…

Chemical Physics · Physics 2021-10-29 Chao Xu , Kunni Lin , Deping Hu , Feng Long Gu , Maxim F. Gelin , Zhenggang Lan

TAPAS is a novel adaptive sampling method for the softmax model. It uses a two pass sampling strategy where the examples used to approximate the gradient of the partition function are first sampled according to a squashed population…

Machine Learning · Computer Science 2017-07-17 Yu Bai , Sally Goldman , Li Zhang

Diffusion models have recently achieved success in solving Bayesian inverse problems with learned data priors. Current methods build on top of the diffusion sampling process, where each denoising step makes small modifications to samples…

Machine Learning · Computer Science 2025-08-19 Bingliang Zhang , Wenda Chu , Julius Berner , Chenlin Meng , Anima Anandkumar , Yang Song