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We introduce mapping-variable ring polymer molecular dynamics (MV-RPMD), a model dynamics for the direct simulation of multi-electron processes. An extension of the RPMD idea, this method is based on an exact, imaginary time path-integral…

Statistical Mechanics · Physics 2015-06-17 Nandini Ananth

This study employed an artificial intelligence-enhanced molecular simulation framework to enable efficient Path Integral Molecular Dynamics (PIMD) simulations. Owing to its modular architecture and high-throughput capabilities, the…

Chemical Physics · Physics 2025-04-01 Cheng Fan , Maodong Li , Sihao Yuan , Zhaoxin Xie , Dechin Chen , Yi Isaac Yang , Yi Qin Gao

We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application to liquid water shows that training the network with a…

Chemical Physics · Physics 2020-06-24 Grace M. Sommers , Marcos F. Calegari Andrade , Linfeng Zhang , Han Wang , Roberto Car

Quantum mechanics based ab-initio molecular dynamics (MD) simulation schemes offer an accurate and direct means to monitor the time-evolution of materials. Nevertheless, the expensive and repetitive energy and force computations required in…

Materials Science · Physics 2014-10-14 Venkatesh Botu , Rampi Ramprasad

We push the boundaries of electronic structure-based \textit{ab-initio} molecular dynamics (AIMD) beyond 100 million atoms. This scale is otherwise barely reachable with classical force-field methods or novel neural network and machine…

Raman spectroscopy is an important characterization tool with diverse applications in many areas of research. We propose a machine learning method for predicting polarizabilities with the goal of providing Raman spectra from molecular…

Materials Science · Physics 2024-02-02 Manuel Grumet , Clara von Scarpatetti , Tomáš Bučko , David A. Egger

Raman spectroscopy is a powerful experimental technique for characterizing molecules and materials that is used in many laboratories. First-principles theoretical calculations of Raman spectra are important because they elucidate the…

Materials Science · Physics 2025-06-25 David A. Egger , Manuel Grumet , Tomáš Bučko

Ab initio molecular dynamics (AIMD) simulations using hybrid density functionals and plane waves are of great interest owing to the accuracy of this approach in treating condensed matter systems. On the other hand, such AIMD calculations…

Chemical Physics · Physics 2020-01-08 Sagarmoy Mandal , Nisanth N. Nair

Computing condensed phase spectra from atomistic simulations requires calculating correlation functions from molecular dynamics and can be very expensive. A totally general, data-driven method to reduce cost is to employ an exact rewriting…

Chemical Physics · Physics 2026-01-06 Thomas Sayer

We present in detail the recently derived ab-initio molecular dynamics (AIMD) formalism [Phys. Rev. Lett. 101 096403 (2008)], which due to its numerical properties, is ideal for simulating the dynamics of systems containing thousands of…

We present a new adaptive resolution technique for efficient particle-based multiscale molecular dynamics (MD) simulations. The presented approach is tailor-made for molecular systems where atomistic resolution is required only in spatially…

Soft Condensed Matter · Physics 2007-05-23 Matej Praprotnik , Luigi Delle Site , Kurt Kremer

Polarizability is closely related to many fundamental characteristics of molecular systems and plays an indispensable role in simulating the Raman spectra. However, the calculations of polarizability for large systems still suffers from the…

Chemical Physics · Physics 2023-02-01 Mandi Fang , Shi Tang , Zheyong Fan , Yao Shi , Nan Xu , Yi He

Single-beam spectrally controlled (SBSC) two-dimensional (2D) Raman spectroscopy is a unique 2D vibrational measurement technique utilizing trains of short pulses that are generated from a single broadband pulse by pulse shaping. This…

Chemical Physics · Physics 2021-03-30 Ju-Yeon Jo , Yoshitaka Tanimura

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for…

Chemical Physics · Physics 2021-03-16 Michael Gastegger , Jörg Behler , Philipp Marquetand

Vibrational motions in electronically excited states can be observed by either time and frequency resolved infrared absorption or by off resonant stimulated Raman techniques. Multipoint correlation function expressions are derived for both…

Quantum Physics · Physics 2017-09-13 Konstantin E. Dorfman , Benjamin P. Fingerhut , Shaul Mukamel

-Molecular simulations allow the study of properties and interactions of molecular systems. This article presents an improved version of the Adaptive Resolution Scheme that links two systems having atomistic (also called fine-grained) and…

Computational Engineering, Finance, and Science · Computer Science 2017-08-01 Iuliana Marin , Virgil Tudose , Anton Hadar , Nicolae Goga , Andrei Doncescu

Path integral molecular dynamics simulations, combined with an ab initio evaluation of interactions using electronic structure theory, incorporate the quantum mechanical nature of both the electrons and nuclei, which are essential to…

Chemical Physics · Physics 2016-02-15 Ondrej Marsalek , Thomas E. Markland

Available simulation methods, suitable to describe solid-solid phase transitions occurring upon increasing of presssure and/or temperature, are based on empirical interatomic potentials: this restriction reduces the predictive power, and…

Condensed Matter · Physics 2016-08-31 P. Focher , G. L. Chiarotti , M. Bernasconi , E. Tosatti , M. Parrinello

We present SPARC: Simulation Package for Ab-initio Real-space Calculations. SPARC can perform Kohn-Sham density functional theory calculations for isolated systems such as molecules as well as extended systems such as crystals and surfaces,…

Ab initio Born-Oppenheimer molecular dynamics (AIMD) is a valuable method for simulating physico-chemical processes of complex systems, including reactive systems, and for training machine learning models and force fields. Speed and…