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We present the Continuous Empirical Cubature Method (CECM), a novel algorithm for empirically devising efficient integration rules. The CECM aims to improve existing cubature methods by producing rules that are close to the optimal,…

Numerical Analysis · Mathematics 2023-11-03 J. A. Hernandez , J. R. Bravo , S. Ares de Parga

The phase diagram of a vertex model introduced by P. Di Francesco (Nucl. Phys. B 525, 507 1998) representing the configurations of a square lattice which can fold with different bending energies along the main axes and the diagonals has…

Statistical Mechanics · Physics 2009-10-31 E. N. M. Cirillo , G. Gonnella , A. Pelizzola

The multi-reference Coupled Cluster method first proposed by Meller et al (J. Chem. Phys. 1996) has been implemented and tested. Guess values of the amplitudes of the single and double excitations (the ${\hat T}$ operator) on the top of the…

Chemical Physics · Physics 2016-04-11 Emmanuel Giner , Grégoire David , Anthony Scemama , Jean Paul Malrieu

One dimensional (1D) simulations of the flow and flooding of open channels are known to be inaccurate as the flow is multi-dimensional in nature, especially at the flooded regions. However, multi-dimensional simulations, even in two…

Numerical Analysis · Mathematics 2017-01-11 Chinedu Nwaigwe , Andreas Dedner

The problems Cluster Vertex Deletion (or Cluster-VD) and its generalization s-Club Cluster Vertex Deletion (or s-Club-VD, for any integer s>= 1), have been introduced with the aim of detecting highly-connected parts in complex systems.…

Computational Complexity · Computer Science 2025-05-13 Irena Rusu

We introduce a variational approach for extracting curves between a list of possible endpoints, based on the discretization of an energy and Smirnov's decomposition theorem for vector fields. It is used to design a bi-level minimization…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Majid Arthaud , Antonin Chambolle , Vincent Duval

The well-known Cluster Vertex Deletion problem (CVD) asks for a given graph $G$ and an integer $k$ whether it is possible to delete a set $S$ of at most $k$ vertices of $G$ such that the resulting graph $G-S$ is a cluster graph (a disjoint…

Discrete Mathematics · Computer Science 2024-02-08 Hoang-Oanh Le , Van Bang Le

We have studied electron correlations in the doped two-dimensional (2D) Hubbard model by using the coupled-cluster method (CCM) to investigate whether or not the method can be applied to correct the independent particle approximations…

Strongly Correlated Electrons · Physics 2009-10-31 Yoshihiro Asai , Hideki Katagiri

We introduce a simplified method to model the interatomic interactions of high entropy alloys based on a lookup table of cluster energies. These interactions are employed in replica exchange Monte Carlo simulations with histogram analysis…

Materials Science · Physics 2022-12-06 Andrew D. Kim , Michael Widom

We investigate the charge- and spin dynamical structure factors for the 2D one-band Hubbard model in the strong coupling regime within an extension of the Dynamical Cluster Approximation (DCA) to two-particle response functions. The full…

Strongly Correlated Electrons · Physics 2009-11-13 S. Hochkeppel , F. F. Assaad , W. Hanke

The method of calculating the free energy and thermodynamic characteristics of the classical n-vector three-dimensional (3D) magnetic model at the microscopic level without any adjustable parameters is proposed. Mathematical description is…

Statistical Mechanics · Physics 2008-11-26 Z. E. Usatenko , M. P. Kozlovskii

This paper presents an efficient optimization technique for gridless {2-D} line spectrum estimation, named decoupled atomic norm minimization (D-ANM). The framework of atomic norm minimization (ANM) is considered, which has been…

Signal Processing · Electrical Eng. & Systems 2022-04-27 Zhe Zhang , Yue Wang , Zhi Tian

Subspace clustering methods have been widely studied recently. When the inputs are 2-dimensional (2D) data, existing subspace clustering methods usually convert them into vectors, which severely damages inherent structures and relationships…

Computer Vision and Pattern Recognition · Computer Science 2020-11-04 Chong Peng , Qian Zhang , Zhao Kang , Chenglizhao Chen , Qiang Cheng

An introductory exposition of the virtual element method (VEM) is provided. The intent is to make this method more accessible to those unfamiliar with VEM. Familiarity with the finite element method for solving 2D linear elasticity problems…

Numerical Analysis · Mathematics 2023-09-25 L. L. Yaw

A differential cluster variation method (DCVM) is proposed for analysis of spinoidal decomposition in alloys. In this method, lattice symmetry operations in the presence of an infinitesimal composition gradient are utilized to deduce the…

Materials Science · Physics 2016-08-31 Zhi-Rong Liu , Huajian Gao

Enhanced sampling techniques such as umbrella sampling and metadynamics are now routinely used to provide information on how the thermodynamic potential, or free energy, depends on a small number of collective variables. The free energy…

Computational Physics · Physics 2018-08-31 Ilaria Gimondi , Gareth A. Tribello , Matteo Salvalaglio

Enhanced sampling simulations make the computational study of rare events feasible. A large family of such methods crucially depends on the definition of some collective variables (CVs) that could provide a low-dimensional representation of…

Computational Physics · Physics 2026-03-03 Jintu Zhang , Luigi Bonati , Enrico Trizio , Odin Zhang , Yu Kang , TingJun Hou , Michele Parrinello

We consider, as a simple model problem, the application of Virtual Element Methods (VEM) to the linear Magnetostatic three-dimensional problem in the formulation of F. Kikuchi. In doing so, we also introduce new serendipity VEM spaces,…

Numerical Analysis · Mathematics 2018-04-30 L. Beirão da Veiga , F. Brezzi , F. Dassi , L. D. Marini , A. Russo

The cluster variation method (CVM) is an approximation technique which generalizes the mean field approximation and has been widely applied in the last decades, mainly for finding accurate phase diagrams of Ising-like lattice models. Here…

High Energy Physics - Lattice · Physics 2015-06-25 Alessandro Pelizzola

Despite the tremendous success of convolutional neural networks (CNNs) in computer vision, the mechanism of CNNs still lacks clear interpretation. Currently, class activation mapping (CAM), a famous visualization technique to interpret…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Zhenpeng Feng , Hongbing Ji , Milos Dakovic , Xiyang Cui , Mingzhe Zhu , Ljubisa Stankovic