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Several methods of triclustering of three dimensional data require the specification of the cluster size in each dimension. This introduces a certain degree of arbitrariness. To address this issue, we propose a new method, namely the…

Machine Learning · Computer Science 2021-09-23 Dina Faneva Andriantsiory , Joseph Ben Geloun , Mustapha Lebbah

A method of cluster diagonalization in a systematically expanded Hilbert space is described. We discuss some applications of this procedure to models of high-T_c superconductors, like the t - J and one and three bands Hubbard models in two…

Condensed Matter · Physics 2009-10-22 Jose' Riera , Elbio Dagotto

We outline how the coupled cluster method of microscopic quantum many-body theory can be utilized in practice to give highly accurate results for the ground-state properties of a wide variety of highly frustrated and strongly correlated…

Strongly Correlated Electrons · Physics 2014-10-24 R. F. Bishop , P. H. Y. Li , C. E. Campbell

Machine learning techniques can reveal hidden structure in large data amounts and can potentially extent or even replace analytical scientific methods. In nanophotonics, modes can increase the light yield from emitters located inside the…

Optics · Physics 2018-10-02 Carlo Barth , Christiane Becker

This thesis propose an a computationally efficient method for dynamic simulation and mathematical modelling of three-phase induction machines under eccentricity conditions.

Optimization and Control · Mathematics 2023-09-14 Iman Ardekani

A fully three-dimensional (3D) magnetohydrodynamical (MHD) model is applied to simulate the evolution of the large-scale magnetic field in cluster galaxies interacting with the intra-cluster medium (ICM). As the model input we use a time…

Astrophysics · Physics 2011-05-23 K. Otmianowska-Mazur , B. Vollmer

This paper explores the use of an entropy-based technique for point cloud reconstruction with the goal of calibrating a lidar to a sensor capable of providing egomotion information. We extend recent work in this area to the problem of…

Robotics · Computer Science 2018-07-17 Jacob Lambert , Lee Clement , Matthew Giamou , Jonathan Kelly

Magneto-active elastomers exhibit large, nonlinear deformations under combined mechanical loading and magnetic fields, and their effective behavior is strongly governed by microstructural heterogeneity. Predictive modeling of these…

Computational Engineering, Finance, and Science · Computer Science 2026-03-30 L. River Spencer , Manuel K. Rausch , Chad M. Landis , Jan N. Fuhg

Electron heating and mixing during asymmetric reconnection are studied with a 3D kinetic simulation that matches plasma parameters from Magnetospheric Multiscale (MMS) spacecraft observations of a magnetopause diffusion region. The mixing…

Plasma Physics · Physics 2017-04-04 Ari Le , William Daughton , Li-Jen Chen , Jan Egedal

We consider the rank-reduced coupled-cluster theory with single and double excitations (RR-CCSD) introduced recently [Parrish \emph{et al.}, J. Chem. Phys. {\bf 150}, 164118 (2019)]. The main feature of this method is the decomposed form of…

Chemical Physics · Physics 2022-02-21 Michał Lesiuk

Recently a cluster Monte Carlo algorithm has been used very successfully in the two-dimensional Edwards-Anderson (EA) model. We show that this algorithm and a variant thereof can also be used successfully in models with a non-zero spin…

Disordered Systems and Neural Networks · Physics 2015-06-24 Thomas Jorg

Ensemble clustering integrates a set of base clustering results to generate a stronger one. Existing methods usually rely on a co-association (CA) matrix that measures how many times two samples are grouped into the same cluster according…

Machine Learning · Computer Science 2023-02-24 Yuheng Jia , Sirui Tao , Ran Wang , Yongheng Wang

Coupled-cluster theories can be used to compute ab initio electronic correlation energies of real materials with systematically improvable accuracy. However, the widely-used coupled cluster singles and doubles plus perturbative triples…

Materials Science · Physics 2024-03-01 Nikolaos Masios , Andreas Irmler , Tobias Schäfer , Andreas Grüneis

Accurately simulating the properties of liquid water remains a central challenge in molecular simulations. In this work, we use machine learning potentials to investigate how the convergence settings of electronic structure calculations…

Chemical Physics · Physics 2026-03-24 Hubert Beck , Ondrej Marsalek

We present highly accurate Monte Carlo results for simple cubic Ising lattices containing up to $256^3$ spins. These results were obtained by means of the Cluster Processor, a newly built special-purpose computer for the Wolff cluster…

Condensed Matter · Physics 2008-11-26 A. L. Talapov , H. W. J. Blöte

The effectiveness of the hyperbolic relaxation method for solving the Einstein constraint equations numerically is studied here on a variety of compact orientable three-manifolds. Convergent numerical solutions are found using this method…

General Relativity and Quantum Cosmology · Physics 2024-03-05 Fan Zhang , Lee Lindblom

In this article, we propose an efficient and spectrally accurate numerical method to compute the ground states of three-dimensional (3D) rotating dipolar Bose-Einstein condensates (BEC) under strongly anisotropic trapping potentials.The…

Numerical Analysis · Mathematics 2026-03-06 Qinglin Tang , Hanquan Wang , Shaobo Zhang , Yong Zhang

This review describes recent advances by the authors and others on the topic of incorporating experimental data into molecular simulations through maximum entropy methods. Methods which incorporate experimental data improve accuracy in…

Chemical Physics · Physics 2019-05-15 Dilnoza B. Amirkulova , Andrew D. White

We propose and study a new class of gradient communication mechanisms for communication-efficient training -- three point compressors (3PC) -- as well as efficient distributed nonconvex optimization algorithms that can take advantage of…

Machine Learning · Computer Science 2022-02-03 Peter Richtárik , Igor Sokolov , Ilyas Fatkhullin , Elnur Gasanov , Zhize Li , Eduard Gorbunov

While lateral interaction models for reactions at surfaces have steadily gained popularity and grown in terms of complexity, their use in chemical kinetics has been impeded by the low performance of current KMC algorithms. The origins of…

Computational Physics · Physics 2019-08-12 Franziska Hess
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