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Stochastic modeling has become a popular approach to quantify uncertainty in flows through heterogeneous porous media. The uncertainty in heterogeneous structure properties is often parameterized by a high-dimensional random variable. This…

Numerical Analysis · Mathematics 2013-10-22 Lijian Jiang , J. David Moulton , Jia Wei

Time series (TS) data are ubiquitous across various application areas, rendering time series forecasting (TSF) a fundamental task. With the astounding advances in large language models (LLMs), a variety of methods have been developed to…

Artificial Intelligence · Computer Science 2025-08-25 Zhuomin Chen , Dan Li , Jiahui Zhou , Shunyu Wu , Haozheng Ye , Jian Lou , See-Kiong Ng

We present a systematic and reliable methodology, termed hierarchical mean-field theory (HMFT), to study and predict the behavior of strongly coupled many-particle systems. HMFT is a simple approximation, based upon group theoretical…

Strongly Correlated Electrons · Physics 2007-05-23 Gerardo Ortiz , Cristian D. Batista

Hydrogen atom transfer (HAT) reactions are essential in many biological processes, such as radical migration in damaged proteins, but their mechanistic pathways remain incompletely understood. Simulating HAT is challenging due to the need…

Machine Learning · Computer Science 2025-11-25 Marlen Neubert , Patrick Reiser , Frauke Gräter , Pascal Friederich

Quantum-dynamical full-dimensional (15D) calculations are reported for the protonated water dimer (H5O2+) using the multiconfiguration time-dependent Hartree (MCTDH) method. The dynamics is described by curvilinear coordinates. The…

Chemical Physics · Physics 2007-11-12 Oriol Vendrell , Fabien Gatti , David Lauvergnat , Hans-Dieter Meyer

We report on an implementation of the multiconfigurational time-dependent Hartree method (MCTDH) for spin-polarized fermions (MCTDHF). Our approach is based on a mapping for opera- tors in Fock space that allows a compact and efficient…

Computational Physics · Physics 2016-03-30 Elke Fasshauer , Axel U. J. Lode

In this paper, we propose the MultiLevel Variational MultiScale (ML-VMS) method, a novel approach that seamlessly integrates a multilevel mesh strategy into the Variational Multiscale (VMS) framework. A key feature of the ML-VMS method is…

Numerical Analysis · Mathematics 2025-10-28 Lei Zhang , Jiachen Guo , Shaoqiang Tang , Thomas J. R. Hughes , Wing Kam Liu

Machine learning force fields (MLFFs), which employ neural networks to map atomic structures to system energies, effectively combine the high accuracy of first-principles calculation with the computational efficiency of empirical force…

Machine Learning · Computer Science 2025-11-17 Guangyi Dong , Zhihui Wang

``$\Delta$-machine learning" refers to a machine learning approach to bring a property such as a potential energy surface (PES) based on low-level (LL) density functional theory (DFT) energies and gradients to close to a coupled cluster…

Chemical Physics · Physics 2021-05-21 Apurba Nandi , Chen Qu , Paul Houston , Riccardo Conte , Joel M. Bowman

The multiconfiguration time-dependent Hartree-Fock (MCTDHF) method is formulated for treating the coupled electronic and nuclear dynamics of diatomic molecules without the Born- Oppenheimer approximation. The method treats the full…

Computational Physics · Physics 2015-05-27 Daniel J. Haxton , Keith V. Lawler , C. William McCurdy

Multivariate long-term time series forecasting (LTSF) supports critical applications such as traffic-flow management, solar-power scheduling, and electricity-transformer monitoring. The existing LTSF paradigms follow a three-stage pipeline…

Machine Learning · Computer Science 2026-02-03 Hyekyung Yoon , Minhyuk Lee , Imseung Park , Myungjoo Kang

Large-scale density functional theory (DFT) calculations provide a powerful tool to investigate the atomic and electronic structure of materials with complex structures. This article reviews a large-scale DFT calculation method, the…

Materials Science · Physics 2022-08-31 Ayako Nakata , David R. Bowler , Tsuyoshi Miyazaki

The multi-layer multiconfiguration time-dependent Hartree (ML-MCTDH) approach suffers from numerical instabilities whenever the wavefunction is weakly entangled. These instabilities arise from singularities in the equations of motion (EOMs)…

Chemical Physics · Physics 2024-06-19 Lachlan P. Lindoy , Benedikt Kloss , David R. Reichman

Accurate, global Potential Energy Surfaces (PES) expressed in sum-of-products (SOP) form are a prerequisite for efficient high-dimensional quantum dynamics simulations using the MCTDH method. This work introduces a methodology for…

Chemical Physics · Physics 2026-03-31 Antoine Aerts

We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a…

High Energy Physics - Phenomenology · Physics 2024-07-12 Tobias Golling , Lukas Heinrich , Michael Kagan , Samuel Klein , Matthew Leigh , Margarita Osadchy , John Andrew Raine

Achieving desired mechanical properties in additive manufacturing requires many experiments and a well-defined design framework becomes crucial in reducing trials and conserving resources. Here, we propose a methodology embracing the…

Machine Learning · Computer Science 2024-09-04 Mahsa Amiri , Zahra Zanjani Foumani , Penghui Cao , Lorenzo Valdevit , Ramin Bostanabad

To solve the many-boson Schr\"odinger equation we utilize the Multiconfigurational time-dependent Hartree method for bosons (MCTDHB). To be able to attack larger systems and/or to propagate the solution for longer times, we implement a…

Quantum Gases · Physics 2011-04-19 Alexej I. Streltsov , Kaspar Sakmann , Ofir E. Alon , Lorenz S. Cederbaum

Excitation-energy transfer (EET) and relaxation in an optically excited building block of poly(phenylene ethynylene) (PPE) dendrimers are simulated using wavepackets with the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH)…

Chemical Physics · Physics 2025-07-01 Joachim Galiana , Michèle Desouter-Lecomte , Benjamin Lasorne

This paper presents the first implementation of a coupling between advanced wave function theories and molecular density functional theory (MDFT). This method enables the modeling of solvent effect into quantum mechanical (QM) calculations…

Chemical Physics · Physics 2024-04-12 Maxime Labat , Emmanuel Giner , Guillaume Jeanmairet

In the near future, material and drug design may be aided by quantum computer assisted simulations. These have the potential to target chemical systems intractable by the most powerful classical computers. However, the resources offered by…