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This paper concerns the construction and analysis of a numerical scheme for a mixed discrete-continuous fragmentation equation. A finite volume scheme is developed, based on a conservative formulation of a truncated version of the…

Numerical Analysis · Mathematics 2019-02-06 Graham Baird , Endre Süli

An ab initio approach formulated under an entropy-inspired repartitioning of the electronic Hamiltonian is presented. This ansatz produces orbital eigenvalues each shifted by entropic contributions expressed as subsets of scaled pair…

Chemical Physics · Physics 2025-06-10 Abdulrahman Y. Zamani , Kevin Carter-Fenk

In this paper, we develop a framework to maximize the network energy efficiency (EE) by optimizing joint user-base station~(BS) association,~subchannel assignment, and power control considering an in-band full-duplex (IBFD)-enabled…

Signal Processing · Electrical Eng. & Systems 2020-10-21 Sheyda Zarandi , Ata Khalili , Mehdi Rasti , Hina Tabassum

In the probabilistic approach to quantum many-body systems, the ground-state energy is the solution of a nonlinear scalar equation written either as a cumulant expansion or as an expectation with respect to a probability distribution of the…

Statistical Mechanics · Physics 2013-04-04 Andrea Di Stefano , Massimo Ostilli , Carlo Presilla

A general polarizable embedded (PE) quantum mechanics/molecular mechanics scheme for periodic systems is presented, describing mutual polarization of the two subsystems. The QM system, described with density functional theory (DFT), is…

To account for phenomenological theories and a set of invariants, stress and strain are usually decomposed into a pair of pressure and deviatoric stress and a pair of volumetric strain and deviatoric strain. However, the conventional…

Mathematical Physics · Physics 2012-11-15 HyunSuk Lee , Jinkyu Kim

We present an alternative approach to decompose non-negative tensors, called many-body approximation. Traditional decomposition methods assume low-rankness in the representation, resulting in difficulties in global optimization and target…

Machine Learning · Statistics 2023-10-31 Kazu Ghalamkari , Mahito Sugiyama , Yoshinobu Kawahara

Machine Learning (ML) approximations to Density Functional Theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present they are not applicable…

Chemical Physics · Physics 2020-03-05 Xiaowei Xie , Kristin A. Persson , David W. Small

In this paper we use a splitting technique to develop new multiscale basis functions for the multiscale finite element method (MsFEM). The multiscale basis functions are iteratively generated using a Green's kernel. The Green's kernel is…

Numerical Analysis · Mathematics 2012-08-17 Lijian Jiang , Michael Presho

Using many-body perturbation theory within the $G_0W_0$ approximation, we explore routes for computing the ionization potential (IP), electron affinity (EA), and fundamental gap of three gas-phase molecules -- benzene, thiophene, and (1,4)…

Materials Science · Physics 2012-10-10 Sahar Sharifzadeh , Isaac Tamblyn , Peter Doak , Pierre T. Darancet , Jeffrey B. Neaton

This paper presents a structure-preserving spatial discretization method for distributed parameter port-Hamiltonian systems. The class of considered systems are hyperbolic systems of two conservation laws in arbitrary spatial dimension and…

Numerical Analysis · Mathematics 2021-08-11 Flávio Luiz Cardoso-Ribeiro , Denis Matignon , Laurent Lefèvre

We propose a component-based (CB) parametric model order reduction (pMOR) formulation for parameterized {nonlinear} elliptic partial differential equations (PDEs). CB-pMOR is designed to deal with large-scale problems for which full-order…

Numerical Analysis · Mathematics 2022-02-22 Kathrin Smetana , Tommaso Taddei

Molecular fragment or embedding methods are powerful techniques for overcoming scalability limitations in electronic structure theory by dividing large molecular systems into individual units that are small enough to be treated using…

Chemical Physics · Physics 2017-08-14 Jason N. Byrd , Robert W. Molt, , Rodney J. Bartlett , Beverly A. Sanders

We present a novel energy-based localization procedure able to localize molecular orbitals into specific spatial regions. The method is applied to several cases including both conjugated and non-conjugated systems. The obtained localized…

Chemical Physics · Physics 2022-09-13 Tommaso Giovannini , Henrik Koch

This work explores an extension of machine learning-optimized piecewise polynomial approximation by incorporating energy optimization as an additional objective. Traditional closed-form solutions enable continuity and approximation targets…

Machine Learning · Computer Science 2025-08-08 Hannes Waclawek , Stefan Huber

A shadow molecular dynamics scheme for flexible charge models is presented, where the shadow Born-Oppenheimer potential is derived from a coarse-grained approximation of range-separated density functional theory. The interatomic potential,…

Chemical Physics · Physics 2023-07-27 James Goff , Yu Zhang , Christian F. A. Negre , Andrew Rohskopf , Anders M. N. Niklasson

In this paper, we apply the constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM) to first solving a nonlinear poroelasticity problem. The arising system consists of a nonlinear pressure equation and a…

Numerical Analysis · Mathematics 2022-05-31 Shubin Fu , Eric Chung , Tina Mai

Energy decomposition analysis (EDA) based on absolutely localized molecular orbitals provides detailed insights into intermolecular bonding by decomposing the total molecular binding energy into physically meaningful components. Here, we…

Chemical Physics · Physics 2025-09-25 Hossein Tahmasbi , Michael Beerbaum , Bartosz Brzoza , Attila Cangi , Thomas D. Kühne

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

Existing Bayesian Optimization (BO) methods typically balance exploration and exploitation to optimize costly objective functions. However, these methods often suffer from a significant one-step bias, which may lead to convergence towards…

Machine Learning · Computer Science 2025-10-23 Ruiyao Miao , Junren Xiao , Shiya Tsang , Hui Xiong , Yingnian Wu