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We study a two-level system coupled to two quantized electromagnetic modes within the Jaynes-Cummings framework. While the single-mode model is exactly solvable due to its conserved excitation number, yielding finite-dimensional invariant…

To leverage the redundancy between the electronic structure computed at each step of first-principles molecular dynamics, we present a data-driven modeling framework for Kohn-Sham Density Functional Theory that bypasses the explicit…

Numerical Analysis · Mathematics 2026-02-27 Siu Wun Cheung , Youngsoo Choi , Jean-Luc Fattebert , Jonas Kaufman , Daniel Osei-Kuffuor

Molecular dynamics (MD) simulation based on Langevin equation has been widely used in the study of structural, thermal properties of matters in difference phases. Normally, the atomic dynamics are described by classical equations of motion…

Mesoscale and Nanoscale Physics · Physics 2018-02-06 Jing-Tao Lü , Bing-Zhong Hu , Per Hedegård , Mads Brandbyge

We investigate the matter density fluctuations \delta\rho/\rho for two dark energy (DE) models in the literature in which the cosmological term \Lambda is a running parameter. In the first model, the running LCDM model, matter and DE…

General Relativity and Quantum Cosmology · Physics 2009-04-28 Javier Grande , Reuven Opher , Ana Pelinson , Joan Sola

With the continuous growth of processing power for scientific computing, first principles Born-Oppenheimer molecular dynamics (MD) simulations are becoming increasingly popular for the study of a wide range of problems in materials science,…

Materials Science · Physics 2015-06-04 Anders M. N. Niklasson , Marc J. Cawkwell

Efficient molecular dynamics (MD) simulation is vital for understanding atomic-scale processes in materials science and biophysics. Traditional density functional theory (DFT) methods are computationally expensive, which limits the…

Machine Learning · Computer Science 2025-10-03 Hung Le , Sherif Abbas , Minh Hoang Nguyen , Van Dai Do , Huu Hiep Nguyen , Dung Nguyen

A parameterization strategy for molecular models on the basis of force fields is proposed, which allows a rapid development of models for small molecules by using results from quantum mechanical (QM) ab initio calculations and thermodynamic…

Chemical Physics · Physics 2009-04-22 Bernhard Eckl , Jadran Vrabec , Hans Hasse

We present a computationally efficient approach to solve the time-dependent Kohn-Sham equations in real-time using higher-order finite-element spatial discretization, applicable to both pseudopotential and all-electron calculations. To this…

Computational Physics · Physics 2019-10-02 Bikash Kanungo , Vikram Gavini

We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\infty$ coefficients. The methods are of Galerkin type and follow the…

Numerical Analysis · Mathematics 2025-05-20 Alexandre L. Madureira , Marcus Sarkis

We determine constraints on spatially-flat tilted dynamical dark energy XCDM and $\phi$CDM inflation models by analyzing Planck 2015 cosmic microwave background (CMB) anisotropy data and baryon acoustic oscillation (BAO) distance…

Cosmology and Nongalactic Astrophysics · Physics 2019-11-06 Junpei Ooba , Bharat Ratra , Naoshi Sugiyama

We study second-order cosmological perturbations in scalar-tensor models of dark energy that satisfy local gravity constraints, including f(R) gravity. We derive equations for matter fluctuations under a sub-horizon approximation and…

Astrophysics · Physics 2010-10-12 Takayuki Tatekawa , Shinji Tsujikawa

Motivated by the occurrence of "shattering" mass-loss observed in purely continuous fragmentation models, this work concerns the development and the mathematical analysis of a new class of hybrid discrete--continuous fragmentation models.…

Analysis of PDEs · Mathematics 2018-04-12 Graham Baird , Endre Süli

Atomic partial charges are crucial parameters in molecular dynamics (MD) simulation, dictating the electrostatic contributions to intermolecular energies, and thereby the potential energy landscape. Traditionally, the assignment of partial…

Machine Learning · Computer Science 2024-05-09 Yuanqing Wang , Iván Pulido , Kenichiro Takaba , Benjamin Kaminow , Jenke Scheen , Lily Wang , John D. Chodera

In this work, we propose a fully discrete energy stable scheme for the phase-field moving contact line model with variable densities and viscosities. The mathematical model consists of a Cahn-Hilliard equation, a Navier-Stokes equation and…

Computational Physics · Physics 2020-03-05 Guangpu Zhu , Huangxin Chen , Aifen Li , Shuyu Sun , Jun Yao

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport…

Fluid Dynamics · Physics 2025-10-22 Marina Echeverria Ferrero , Nicolas Moreno , Marco Ellero

The charge transfer and polarization effects are important components in the molecular mechanism description of bio-molecules. Classical force field with fixed point charge cannot take into the account of the non-negligible correlation…

Chemical Physics · Physics 2018-03-01 Tiange Dong , Fang Liu , Likai Du , Dongju Zhang , Jun Gao

Extended Lagrangian molecular dynamics (XLMD) is a general method for performing molecular dynamics simulations using quantum and classical many-body potentials. Recently several new XLMD schemes have been proposed and tested on several…

Numerical Analysis · Mathematics 2020-02-28 Dong An , Sara Y. Cheng , Teresa Head-Gordon , Lin Lin , Jianfeng Lu

Two-dimensional Raman and hybrid terahertz/Raman spectroscopic techniques provide invaluable insight into molecular structure and dynamics of condensed-phase systems. However, corroborating experimental results with theory is difficult due…

Chemical Physics · Physics 2022-04-13 Tomislav Begušić , Xuecheng Tao , Geoffrey A. Blake , Thomas F. Miller

Molecular dynamics (MD) simulations are used in biochemistry, physics, and other fields to study the motions, thermodynamic properties, and the interactions between molecules. Computational limitations and the complexity of these problems,…

Numerical Analysis · Mathematics 2018-01-17 F. Grogan , M. Holst , L. Lindblom , R. Amaro

Optimization algorithms are core methods by which machine learning models iteratively minimize loss functions, update parameters, learn from data, and improve performance. Momentum SGD and AdamW represent two important optimization…

Machine Learning · Computer Science 2026-05-21 Meng Zhu , Quan Xiao , Weidong Min