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Modern applications of atomic physics, including the determination of frequency standards, and the analysis of astrophysical spectra, require prediction of atomic properties with exquisite accuracy. For complex atomic systems,…

Atomic Physics · Physics 2024-08-02 Pavlo Bilous , Charles Cheung , Marianna Safronova

A quantum-field approach for describing many-particle Fermi systems at finite temperatures and with spontaneously broken symmetry has been proposed. A generalized model of self-consistent field (SCF), which allows one to describe the states…

Statistical Mechanics · Physics 2013-03-21 Yu. M. Poluektov

The computational investigation of photochemical processes often entails the calculation of excited state geometries, energies, and energy gradients. The nuclear-electronic orbital (NEO) approach treats specified nuclei, typically protons,…

We present a dynamical and dissipative lattice model, designed to mimic nuclear multifragmentation. Monte-Carlo simulations with this model show clear signature of critical behaviour and reproduce experimentally observed correlations. In…

Statistical Mechanics · Physics 2009-10-31 J. S. Sa' Martins , P. M. C. de Oliveira

We develop a micromorphic-based approach for finite element stabilization of reaction-convection-diffusion equations, by gradient enhancement of the field of interest via introducing an auxiliary variable. The well-posedness of the…

Mathematical Physics · Physics 2025-10-15 Soheil Firooz , B. Daya Reddy , Paul Steinmann

Quantum variational algorithms (QVAs) are increasingly potent tools for simulating quantum many-body systems on noisy intermediate-scale quantum (NISQ) devices. This work examines the application of the Variational Quantum Eigensolver (VQE)…

Nuclear Theory · Physics 2026-01-28 Dhritimalya Roy , Somnath Nag

Adiabatic connection models (ACMs), which interpolate between the limits of weak and strong interaction, are powerful tools to build accurate exchange-correlation functionals. If the exact weak-interaction expansion from second-order…

Chemical Physics · Physics 2022-09-08 S. Śmiga , F. Della Sala , P. Gori-Giorgi , E. Fabiano

The level density is among the most important statistical nuclear properties. It appears in Fermi's golden rule for transition rates and is an important input to the Hauser-Feshbach theory of compound nucleus reactions. We discuss empirical…

Nuclear Theory · Physics 2022-01-05 Y. Alhassid

We present Q-AMOEBA (CF), an enhanced version of the Q-AMOEBA polarizable model that integrates a geometry-dependent charge flux (CF) term while designed for an explicit treatment of nuclear quantum effects (NQE). The inclusion of CF…

Chemical Physics · Physics 2025-06-05 Nastasia Mauger , Thomas Plé , Louis Lagardère , Simon Huppert , Jean-Philip Piquemal

Interconnection studies require solving numerous instances of the AC load or power flow (AC PF) problem to simulate diverse scenarios as power systems navigate the ongoing energy transition. To expedite such studies, this work leverages…

Quantum Physics · Physics 2025-09-18 Thinh Viet Le , Md Obaidur Rahman , Vassilis Kekatos

We employ constrained path Auxiliary Field Quantum Monte Carlo (AFQMC) in the pursuit of studying physical nuclear systems using a lattice formalism. Since AFQMC has been widely used in the study of condensed-matter systems such as the…

Nuclear Theory · Physics 2024-07-16 Ryan Curry , Jayani Dissanayake , Stefano Gandolfi , Alexandros Gezerlis

Quantum-selected configuration interaction (QSCI) is a novel quantum-classical hybrid algorithm for quantum chemistry calculations. This method identifies electron configurations having large weights for the target state using quantum…

Chemical Physics · Physics 2025-03-31 Soichi Shirai , Shih-Yen Tseng , Hokuto Iwakiri , Takahiro Horiba , Hirotoshi Hirai , Sho Koh

Machine learning has the potential to revolutionize the field of molecular simulation through the development of efficient and accurate models of interatomic interactions. In particular, neural network models can describe interactions at…

Chemical Physics · Physics 2022-04-06 Ang Gao , Richard C. Remsing

An analytic gradient approach for the computation of derivatives of parity-violating (PV) potentials with respect to displacements of the nuclei in chiral molecules is described and implemented within a quasirelativistic mean-field…

Chemical Physics · Physics 2023-12-19 Sascha A Brück , Nityananda Sahu , Konstantin Gaul , Robert Berger

We introduce a novel approach for calibrating uncertainty quantification (UQ) tailored for multi-modal large language models (LLMs). Existing state-of-the-art UQ methods rely on consistency among multiple responses generated by the LLM on…

In this thesis we deal with different aspects of quantum field theory, particularly in non-perturbative but also perturbative regimes, applied to the intellectual construction that is the Standard Model for Particle Physics (SM), but also…

High Energy Physics - Phenomenology · Physics 2023-09-25 Alexandre Salas-Bernárdez

In this contribution we investigate the application of phase-field fracture models on non-linear multiscale computational homogenization schemes. In particular, we introduce different phase-fields on a two-scale problem and develop a…

Computational Engineering, Finance, and Science · Computer Science 2023-12-21 Felix Schmidt , Stefan Schuß , Christian Hesch

Dendritic growth, and the formation of material microstructure in general, necessarily involves a wide range of length scales from the atomic up to sample dimensions. The phase field approach of Langer, enhanced by optimal asymptotic…

Materials Science · Physics 2015-06-25 Nigel Goldenfeld , Badrinarayan P. Athreya , Jonathan A. Dantzig

A fully analytical approximation for the observable characteristics of many-electron atoms is developed via a complete and orthonormal hydrogen-like basis with a single-effective charge parameter for all electrons of a given atom. The basis…

Quantum Physics · Physics 2017-12-06 O. D. Skoromnik , I. D. Feranchuk , A. U. Leonau , C. H. Keitel

We extend the phase field crystal (PFC) framework to quantitative modeling of polycrystalline graphene. PFC modeling is a powerful multiscale method for finding the ground state configurations of large realistic samples that can be further…

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