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We present an extensive set of surface and chemisorption energies calculated using state of the art many-body perturbation theory. In the first part of the paper we consider ten surface reactions in the low coverage regime where…

Materials Science · Physics 2018-02-01 Per Simmendefeldt Schmidt , Kristian Sommer Thygesen

Structural phase transitions often couple to magnetic and electronic degrees of freedom, enabling emergent phenomena in solids. In high-entropy oxides (HEOs), which typically stabilize in highly symmetric cubic phases, such transitions are…

We present an application of Wertheim's Thermodynamic Perturbation Theory (TPT1) to a simple coarse grained model made of flexibly bonded Lennard-Jones monomers. We use both the Reference Hyper-Netted-Chain (RHNC) and Mean Spherical…

Statistical Mechanics · Physics 2016-08-15 L. González MacDowell , M. Mueller , C. Vega , K. Binder

The dynamical effects of ground state correlations for excitation energies and transition strengths near the superfluid phase transition are studied in the soluble two level pairing model, in the context of the particle-particle self…

Nuclear Theory · Physics 2008-11-26 E. J. V. de Passos , A. F. R. de Toledo Piza , F. Krmpotić

We propose a new high dimensional semiparametric principal component analysis (PCA) method, named Copula Component Analysis (COCA). The semiparametric model assumes that, after unspecified marginally monotone transformations, the…

Machine Learning · Statistics 2014-02-20 Fang Han , Han Liu

We outline how principal component analysis (PCA) can be applied to particle configuration data to detect a variety of phase transitions in off-lattice systems, both in and out of equilibrium. Specifically, we discuss its application to…

Computational Physics · Physics 2018-12-07 R. B. Jadrich , B. A. Lindquist , W. D. Pineros , D. Banerjee , T. M. Truskett

Principal component analysis (PCA) has achieved great success in unsupervised learning by identifying covariance correlations among features. If the data collection fails to capture the covariance information, PCA will not be able to…

Computational Physics · Physics 2021-08-24 Ziming Liu , Sitian Qian , Yixuan Wang , Yuxuan Yan , Tianyi Yang

Even if the atoms of a multicomponent alloy occupy a common lattice, their distribution is not homogeneous, and regions with different compositions can be detected. Three representative examples will be discussed: a Cantor-type system…

Materials Science · Physics 2026-05-12 Vaclav Paidar , Pavel Lejcek , Andrea Skolakova

Refractory compositionally complex alloys (RCCAs) are considered the next generation high-temperature materials. However, their high-dimensional composition spaces are too large to explore by traditional density functional theory or…

A Coherent Potential Approximation is developed for s-wave and d-wave superconductivity in disordered systems. We show that the CPA formalism reproduces the standard pair-breaking formula, the self-consistent Born Approximation and the…

Superconductivity · Physics 2009-10-31 A. M. Martin , G. Litak , B. L. Gyorffy , J. F. Annett , K. I. Wysokinski

We reconsider the theory of the half-filled lowest Landau level using the Chern-Simons formulation and study the grand-canonical potential in the random-phase approximation (RPA). Calculating the unperturbed response functions for current-…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 J. Dietel , Th. Koschny , W. Apel , W. Weller

We describe and discuss the low-temperature resistivity (and the temperature-dependent inelastic scattering rate) of several different doped 2D semiconductor systems from the perspective of the Planckian hypothesis asserting that…

Mesoscale and Nanoscale Physics · Physics 2022-11-02 Seongjin Ahn , Sankar Das Sarma

Random Phase Approximation (RPA) is the theory most commonly used to describe the excitations of many-body systems. In this article, the secular equations of the theory are obtained by using three different approaches: the equation of…

Nuclear Theory · Physics 2023-03-14 Giampaolo Co'

High-throughput methods enable accelerated discovery of novel materials in complex systems such as high-entropy alloys, which exhibit intricate phase stability across vast compositional spaces. Computational approaches, including Density…

Principal Component analysis (PCA) is a useful statistical technique that is commonly used for multivariate analysis of correlated variables. It is usually applied as a dimension reduction method: the top principal components (PCs)…

We develop asymptotic theory for principal component analysis (PCA) of a high-dimensional factor model in which the working dimension $R$ is fixed and only required to satisfy $R \ge r$, where $r$ is the true number of factors. Building on…

Statistics Theory · Mathematics 2026-05-19 Yuan Liao , Xin Tong , Wanjie Wang , Dacheng Xiu

Using the Korringa-Kohn-Rostoker coherent-potential approximation in the atomic-sphere approximation (KKR-ASA CPA) we have studied the changes in the electronic structure and the superconducting transition temperature T_{c} in Nb_{1-x}B_{2}…

Superconductivity · Physics 2009-11-10 P. Jiji Thomas Joseph , Prabhakar P. Singh

Dynamical Coherent-Potential Approximation (CPA) to correlated electrons has been extended to a system with realistic Hamiltonian which consists of the first-principles tight-binding Linear Muffintin Orbital (LMTO) bands and intraatomic…

Strongly Correlated Electrons · Physics 2008-07-08 Y. Kakehashi , T. Shimabukuro , T Tamashiro , T. Nakamura

The Random Phase Approximation (RPA) for total energies has previously been shown to provide a qualitatively correct description of static correlation in molecular systems, where density functional theory (DFT) with local functionals are…

Materials Science · Physics 2017-09-27 Thomas Olsen

The general fluctuation theory is reviewed with special attention to the role played by different ensembles, and is extended to incorporate stationary metastable states obtained in the long time limit. The fluctuation in a quantity depends…

Statistical Mechanics · Physics 2007-05-23 P. D. Gujrati
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