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Quantum particles in a disordered potential, photons or classical waves in a random medium, or the universe expansion in a fluctuating cosmic field, all share Anderson localization as a communality. In general, localization is enhanced for…

Disordered Systems and Neural Networks · Physics 2015-09-07 Hichem Eleuch , Michael Hilke

We generalize the typical medium dynamical cluster approximation to multiband disordered systems. Using our extended formalism, we perform a systematic study of the non-local correlation effects induced by disorder on the density of states…

Disordered Systems and Neural Networks · Physics 2015-11-11 Yi Zhang , Hanna Terletska , C. Moore , Chinedu Ekuma , Ka-Ming Tam , Tom Berlijn , Wei Ku , Juana Moreno , Mark Jarrell

Tailored coupled cluster theory represents a computationally inexpensive way to describe static and dynamical electron correlation effects. In this work, we scrutinize the performance of various tailored coupled cluster methods externally…

Chemical Physics · Physics 2021-03-24 Aleksandra Leszczyk , Mihály Máté , Örs Legeza , Katharina Boguslawski

Sparse Principal Component Analysis (PCA) methods are efficient tools to reduce the dimension (or the number of variables) of complex data. Sparse principal components (PCs) are easier to interpret than conventional PCs, because most…

Statistics Theory · Mathematics 2011-04-22 Dan Shen , Haipeng Shen , J. S. Marron

We report the experimental realization of acoustic coherent perfect absorption (CPA) of four symmetric scatterers of very different structures. The only conditions necessary for these scatterers to exhibit CPA are that both the reflection…

Classical Physics · Physics 2016-10-13 Chong Meng , Xiaonan Zhang , Suet To Tang , Min Yang , Zhiyu Yang

We present a numerical solution of the parquet approximation (PA), a conserving diagrammatic approach which is self-consistent at both the single-particle and the two-particle levels. The fully irreducible vertex is approximated by the bare…

Strongly Correlated Electrons · Physics 2010-10-05 S. X. Yang , H. Fotso , J. Liu , T. A. Maier , K. Tomko , E. F. D'Azevedo , R. T. Scalettar , T. Pruschke , M. Jarrell

Principal Component Analysis (PCA) is one of the most important methods to handle high dimensional data. However, most of the studies on PCA aim to minimize the loss after projection, which usually measures the Euclidean distance, though in…

Machine Learning · Computer Science 2019-03-19 Kai Liu , Qiuwei Li , Hua Wang , Gongguo Tang

Sparse principal component analysis (PCA) is a popular dimensionality reduction technique for obtaining principal components which are linear combinations of a small subset of the original features. Existing approaches cannot supply…

Optimization and Control · Mathematics 2022-02-22 Dimitris Bertsimas , Ryan Cory-Wright , Jean Pauphilet

We show that, in contrast to immediate intuition, Anderson localization of noninteracting particles induced by a disordered potential in free space can increase (i.e., the localization length can decrease) when the particle energy…

Quantum Gases · Physics 2012-06-19 Marie Piraud , Alain Aspect , Laurent Sanchez-Palencia

Attaining a reliable complete basis set (CBS) limit remains a significant challenge in ab initio correlated electronic-structure calculations. Building on our previous work for atoms and diatomic molecules, we present a finite-element (FE)…

Materials Science · Physics 2026-03-30 Hao Peng , Haochen Liu , Chuhao Li , Hehu Xie , Xinguo Ren

Introducing an active space approximation is inevitable for the quantum computations of chemical systems. However, this approximation ignores the electron correlations related to non-active orbitals. Here, we propose a computational method…

Quantum Physics · Physics 2024-06-06 Luca Erhart , Yuichiro Yoshida , Viktor Khinevich , Wataru Mizukami

The mixture model is undoubtedly one of the greatest contributions to clustering. For continuous data, Gaussian models are often used and the Expectation-Maximization (EM) algorithm is particularly suitable for estimating parameters from…

Machine Learning · Statistics 2025-11-25 Zineddine Tighidet , Lazhar Labiod , Mohamed Nadif

We study the problem of applying spectral clustering to cluster multi-scale data, which is data whose clusters are of various sizes and densities. Traditional spectral clustering techniques discover clusters by processing a similarity…

Machine Learning · Computer Science 2020-06-09 Xiang Li , Ben Kao , Caihua Shan , Dawei Yin , Martin Ester

The recent quantum information boom has effected a resurgence of interest in unitary coupled cluster (UCC) theory. Our group's interest in local energy landscapes of unitary ans\"atze prompted us to investigate the classical approach of…

Chemical Physics · Physics 2022-11-01 Harper R. Grimsley , Nicholas J. Mayhall

Correlation clustering is perhaps the most natural formulation of clustering. Given $n$ objects and a pairwise similarity measure, the goal is to cluster the objects so that, to the best possible extent, similar objects are put in the same…

Data Structures and Algorithms · Computer Science 2013-12-19 Francesco Bonchi , David García-Soriano , Konstantin Kutzkov

The design of sub-arrayed phased arrays (PAs) with sub-array-only amplitude and phase controls that afford arbitrary-shaped power patterns matching reference ones is addressed. Such a synthesis problem is formulated in the power pattern…

Information Theory · Computer Science 2023-10-11 Arianna Benoni , Lorenzo Poli , Paolo Rocca , Andrea Massa

This paper examines in detail the geometric structure of principal component analysis (PCA) by considering in detail the distributions of both unrotated and rotated MNIST digits in the space defined by the lowest order PCA components. Since…

Machine Learning · Computer Science 2025-10-02 David Yevick , Karolina Hutchison

Several new aspects of the subtle interplay between electronic correlations and disorder are reviewed. First, the dynamical mean-field theory (DMFT)together with the geometrically averaged ("typical") local density of states is employed to…

Strongly Correlated Electrons · Physics 2015-05-18 K. Byczuk , W. Hofstetter , U. Yu , D. Vollhardt

A new state specific correlation correction to configuration interaction singles (CIS) excitation energies is preseted using coupled cluster perturbation theory (CCPT). General expressions for CIS-CCPT are derived and expanded explicitly to…

Chemical Physics · Physics 2015-06-19 Jason N. Byrd , Victor F. Lotrich , Rodney J. Bartlett

When the number of strongly correlated electrons becomes larger, the single-reference coupled-cluster (CC) CCSD, CCSDT, etc. hierarchy displays an erratic behavior, while traditional multi-reference approaches may no longer be applicable…

Chemical Physics · Physics 2025-12-12 Ilias Magoulas , Jun Shen , Piotr Piecuch
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