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Direct numerical simulations (DNS) are one of the main ab initio tools to study turbulent flows. However, due to their considerable computational cost, DNS are primarily restricted to canonical flows at moderate Reynolds numbers, in which…

Fluid Dynamics · Physics 2024-09-17 Arnab Moitro , Sai Sandeep Dammati , Alexei Y. Poludnenko

Multicomponent systems are defined as chemical systems that require a quantum mechanical description of two or more different types of particles. Non-Born-Oppenheimer electron-nuclear interactions in molecules, electron-hole interactions in…

Chemical Physics · Physics 2015-10-21 Benjamin H. Ellis , Somil Aggarwal , Arindam Chakraborty

The quantum many-body bound-state problem in its computationally successful coupled cluster method (CCM) representation is reconsidered. In conventional practice one factorizes the ground-state wave functions $|\Psi\rangle= e^S…

Quantum Physics · Physics 2014-05-02 Raymond F. Bishop , Miloslav Znojil

We present an unsupervised data processing workflow that is specifically designed to obtain a fast conformational clustering of long molecular dynamics simulation trajectories. In this approach we combine two dimensionality reduction…

Chemical Physics · Physics 2023-08-09 Simon Hunkler , Kay Diederichs , Oleksandra Kukharenko , Christine Peter

Coupled cluster methods are widely regarded as the gold standard of computational quantum chemistry as they are perceived to offer the best compromise between computational cost and a high-accuracy resolution of the ground state eigenvalue…

Numerical Analysis · Mathematics 2025-12-03 Muhammad Hassan , Yvon Maday

This paper studies the large-scale subspace clustering (LSSC) problem with million data points. Many popular subspace clustering methods cannot directly handle the LSSC problem although they have been considered as state-of-the-art methods…

Machine Learning · Computer Science 2020-04-10 Jun Li , Hongfu Liu , Zhiqiang Tao , Handong Zhao , Yun Fu

Clustering techniques offer a powerful framework for analyzing complex flow dynamics and reducing computational costs in large-scale simulations. In this work, we propose a novel clustering-based approach using Vector Quantization Principal…

In this paper, we consider flow and transport problems in thin domains. The mathematical model considered in the paper is described by a system of equations for velocity, pressure, and concentration, where the flow is described by the…

Numerical Analysis · Mathematics 2021-07-07 Maria Vasilyeva , Valentin Alekseev , Eric T. Chung , Yalchin Efendiev

We consider the coupled system of equations that describe flow in fractured porous media. To describe such types of problems, multicontinuum and multiscale approaches are used. Because in multicontinuum models, the permeability of each…

Numerical Analysis · Mathematics 2023-05-31 Maria Vasilyeva

Coupled-cluster and Green's function theories are highly successful in treating many-body electron correlation, and there has been significant interest in identifying and leveraging connections between them. Here we present a diagrammatic…

Strongly Correlated Electrons · Physics 2025-07-03 Christopher J. N. Coveney , David P. Tew

Great progress has been made in the last several years towards understanding the properties of disordered electronic systems. In part, this is made possible by recent advances in quantum effective medium methods which enable the study of…

Disordered Systems and Neural Networks · Physics 2019-05-09 Hanna Terletska , Yi Zhang , Ka Ming Tam , Tom Berlijn , L. Chioncel , N. S. Vidhyadhiraja , Mark Jarrell

In the present paper, a fluid-particle coupling method is directly derived from the Navier-Stokes equations (NSE) by applying the concept of volume-filtering, yielding a physically consistent methodology to incorporate solid wall boundary…

Fluid Dynamics · Physics 2024-10-17 Max Hausmann , Hani Elmestikawy , Berend van Wachem

Clustering procedures suitable for the analysis of very high-dimensional data are needed for many modern data sets. In model-based clustering, a method called high-dimensional data clustering (HDDC) uses a family of Gaussian mixture models…

Methodology · Statistics 2017-06-28 Angelina Pesevski , Brian C. Franczak , Paul D. McNicholas

In this paper, our aim is to present (1) an embedded fracture model (EFM) for coupled flow and mechanics problem based on the dual continuum approach on the fine grid and (2) an upscaled model for the resulting fine grid equations. The…

Numerical Analysis · Mathematics 2018-11-14 Maria Vasilyeva , Eric T. Chung , Yalchin Efendiev , Jihoon Kim

A unitary coupled-cluster (UCC) form for the wavefunction in the variational quantum eigensolver has been suggested as a systematic way to go beyond the mean-field approximation and include electron correlation in solving quantum chemistry…

Quantum Physics · Physics 2018-09-12 Ilya G. Ryabinkin , Tzu-Ching Yen , Scott N. Genin , Artur F. Izmaylov

In this work, we present an upscaled model for mixed dimensional coupled flow problem in fractured porous media. We consider both embedded and discrete fracture models (EFM and DFM) as fine scale models which contain coupled system of…

Numerical Analysis · Mathematics 2018-05-25 Maria Vasilyeva , Eric T. Chung , Wing Tat Leung , Valentin Alekseev

The clustering of data into physically meaningful subsets often requires assumptions regarding the number, size, or shape of the subgroups. Here, we present a new method, simultaneous coherent structure coloring (sCSC), which accomplishes…

Machine Learning · Statistics 2019-11-26 Brooke E. Husic , Kristy L. Schlueter-Kuck , John O. Dabiri

Characterizing complex many-body phases of matter has been a central question in quantum physics for decades. Numerical methods built around approximations of the renormalization group (RG) flow equations have offered reliable and…

Strongly Correlated Electrons · Physics 2024-03-25 Jiawei Zang , Matija Medvidović , Dominik Kiese , Domenico Di Sante , Anirvan M. Sengupta , Andrew J. Millis

This paper presents Orthogonal Subspace Clustering (OSC), an innovative method for high-dimensional data clustering. We first establish a theoretical theorem proving that high-dimensional data can be decomposed into orthogonal subspaces in…

Machine Learning · Computer Science 2026-03-17 Qing-Yuan Wen , Da-Qing Zhang

Cable subsystems characterized by long, slender, and flexible structural elements are featured in numerous engineering systems. In each of them, interaction between an individual cable and the surrounding fluid is inevitable. Such a…

Computational Engineering, Finance, and Science · Computer Science 2019-11-11 Daniel Z. Huang , Philip Avery , Charbel Farhat
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