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We discuss a new Monte Carlo algorithm for the simulation of complex fluids. This algorithm employs geometric operations to identify clusters of particles that can be moved in a rejection-free way. It is demonstrated that this geometric…

Statistical Mechanics · Physics 2015-06-25 Erik Luijten , Jiwen Liu

The minimum sum-of-squares clustering problem (MSSC), also known as $k$-means clustering, refers to the problem of partitioning $n$ data points into $k$ clusters, with the objective of minimizing the total sum of squared Euclidean distances…

Optimization and Control · Mathematics 2025-07-18 Antonio M. Sudoso , Daniel Aloise

Nonlocal correlations play an essential role in correlated electron systems, especially in the vicinity of phase transitions and crossovers, where two-particle correlation functions display a distinct momentum dependence. In nonequilibrium…

Strongly Correlated Electrons · Physics 2023-06-29 Olivier Simard , Philipp Werner

We propose a method that incorporates explicit derivative discontinuity of the total energy with respect to the number of electrons and treats both delocalization and static correlation effects in density functional calculations. Our…

Strongly Correlated Electrons · Physics 2018-03-08 Fei Zhou , Vidvuds Ozolins

This work, for the first time, introduces two constant factor approximation algorithms with linear query complexity for non-monotone submodular maximization over a ground set of size $n$ subject to a knapsack constraint, $\mathsf{DLA}$ and…

Data Structures and Algorithms · Computer Science 2023-07-11 Canh V. Pham , Tan D. Tran , Dung T. K. Ha , My T. Thai

Dirichlet process mixture (DPM) models are widely used for semiparametric Bayesian analysis in educational and behavioral research, yet specifying the concentration parameter remains a critical barrier. Default hyperpriors often impose…

Methodology · Statistics 2026-02-09 JoonHo Lee

In this work, we extend the dual triply irreducible local expansion (D-TRILEX) approach for correlated electronic systems by introducing a cluster reference system for the diagrammatic expansion. This framework allows us to consistently…

Strongly Correlated Electrons · Physics 2026-02-26 Félix Fossati , Evgeny A. Stepanov

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

The development of numerical methods capable of simulating realistic materials with strongly correlated electrons, with controllable errors, is a central challenge in quantum many-body physics. Here we describe how a hybrid between…

Strongly Correlated Electrons · Physics 2015-04-23 Alexei A. Kananenka , Emanuel Gull , Dominika Zgid

This study introduces Skewed Fully Asynchronous Cellular Automata (SACA), a novel update scheme in cellular automata that updates the states of only two consecutive and adjacent cells, such as ci and ci+1, simultaneously at each time step.…

Formal Languages and Automata Theory · Computer Science 2025-01-07 Virendra Kumar Gautam

This paper introduces a novel methodology of adapting the representation of videos based on the dynamics of their scene content variation. In particular, we demonstrate how the clustering of dynamic mode decomposition eigenvalues can be…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Owen T. Huber , Raghu G. Raj , Tianyu Chen , Zacharie I. Idriss

We evaluate the dependence of the cluster correlation length r_c on the mean intercluster separation D_c, for three models with critical matter density, vanishing vacuum energy (Lambda = 0) and COBE normalized: a tilted CDM (tCDM) model…

Astrophysics · Physics 2009-10-31 A. Gardini , S. A. Bonometto , G. Murante , G. Yepes

This paper discusses a deterministic clustering approach to capacitated resource allocation problems. In particular, the Deterministic Annealing (DA) algorithm from the data-compression literature, which bears a distinct analogy to the…

Optimization and Control · Mathematics 2016-06-22 Mayank Baranwal , Srinivasa M. Salapaka

Recently, deep clustering, which is able to perform feature learning that favors clustering tasks via deep neural networks, has achieved remarkable performance in image clustering applications. However, the existing deep clustering…

Machine Learning · Computer Science 2018-12-12 Yazhou Ren , Ni Wang , Mingxia Li , Zenglin Xu

Traditional clustering methods often perform clustering with low-level indiscriminative representations and ignore relationships between patterns, resulting in slight achievements in the era of deep learning. To handle this problem, we…

Machine Learning · Computer Science 2019-05-07 Jianlong Chang , Yiwen Guo , Lingfeng Wang , Gaofeng Meng , Shiming Xiang , Chunhong Pan

We employ the recently introduced conformal iterative construction of Diffusion Limited Aggregates (DLA) to study the multifractal properties of the harmonic measure. The support of the harmonic measure is obtained from a dynamical process…

chao-dyn · Physics 2009-10-31 Benny Davidovich , Itamar Procaccia

Fixed node diffusion quantum Monte Carlo (FN-DMC) is an increasingly used computational approach for investigating the electronic structure of molecules, solids, and surfaces with controllable accuracy. It stands out among equally accurate…

Computational Physics · Physics 2019-10-03 Andrea Zen , Jan Gerit Brandenburg , Angelos Michaelides , Dario Alfè

Using a combined local density functional theory (LDA-DFT) and quantum Monte Carlo (QMC) dynamic cluster approximation approach, the parameter dependence of the superconducting transition temperature Tc of several single-layer hole-doped…

An electrodynamical coupled cluster (CC) methodology starting from a covariant formalism and an equal time approximation, and finally based on the Dirac-Fock picture of the electron and positron fields and Coulomb gauge, is given here. The…

Atomic Physics · Physics 2019-04-30 Sambhu N. Datta

We consider a cluster growth model on the d-dimensional lattice, called internal diffusion limited aggregation (internal DLA). In this model, random walks start at the origin, one at a time, and stop moving when reaching a site not occupied…

Probability · Mathematics 2013-06-03 Amine Asselah , Alexandre Gaudilliere