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We present a new paradigm for the design of exchange-correlation functionals in density-functional theory. Electron pairs are correlated explicitly by means of the recently developed second order Bethe-Goldstone equation (BGE2) approach.…

Materials Science · Physics 2018-10-19 Igor Ying Zhang , Patrick Rinke , John P. Perdew , Matthias Scheffler

In this paper, we study stochastic non-convex optimization with non-convex random functions. Recent studies on non-convex optimization revolve around establishing second-order convergence, i.e., converging to a nearly second-order optimal…

Optimization and Control · Mathematics 2017-11-02 Mingrui Liu , Tianbao Yang

Unlike macroscopic engines, the molecular machinery of living cells is strongly affected by fluctuations. Stochastic Thermodynamics uses Markovian jump processes to model the random transitions between the chemical and configurational…

Statistical Mechanics · Physics 2015-10-19 Bernhard Altaner , Artur Wachtel , Jürgen Vollmer

Self-consistent approaches to superfluid many-fermion systems in 3-dimensions (and subsequent time-dependent approaches) require a large number of diagonalizations of very large dimension hermitian matrices, which results in enormous…

Nuclear Theory · Physics 2017-04-12 Shi Jin , Aurel Bulgac , Kenneth Roche , Gabriel Wlazłowski

Stochastic gradient (SG) methods are fundamental to system identification and machine learning, enabling online parameter estimation in large-scale and streaming-data settings. As a classical identification method, the SG algorithm has been…

Optimization and Control · Mathematics 2026-05-08 Senhan Yao , Longxu Zhang

Open effective field theories provide a systematic framework for describing physical systems interacting with an environment whose microscopic details are unknown, unobservable, or uncalculable. A basic step in constructing any effective…

High Energy Physics - Theory · Physics 2026-05-25 Enrica Lausdei , Enrico Pajer

Derivation of two-time second-order correlation function by following approaches such as stochastic differential equation, coherent-state propagator, and quasi-statistical distribution function is presented. In the process, the time…

Quantum Physics · Physics 2024-06-18 Sintayehu Tesfa

The effective second-harmonic generation (SHG) coefficient is a crucial data that quantifies the efficiency of transforming fundamental frequency light into its second harmonic. With the help of the symmetry of nonlinear optical…

Optimization and Control · Mathematics 2026-02-24 Die Xiao , Yisheng Song

We discuss the consequences of spin current conservation in systems with SU(2) spin symmetry that is spontaneously broken by partial magnetic order, using a momentum-space approach. The long-distance interaction is mediated by Goldstone…

Superconductivity · Physics 2015-03-19 K. Odagiri , T. Yanagisawa

We focus on the numerical approximation of the Cahn-Hilliard type equations, and present a family of second-order unconditionally energy-stable schemes. By reformulating the equation into an equivalent system employing a scalar auxiliary…

Fluid Dynamics · Physics 2018-03-19 Suchuan Dong , Zhiguo Yang , Lianlei Lin

The multi-configurational self-consistent field theory is considered the standard starting point for almost all multireference approaches required for strongly-correlated molecular problems. The limitation of the approach is generally given…

Chemical Physics · Physics 2015-10-14 Robert E. Thomas , Qiming Sun , Ali Alavi , George H. Booth

In contexts where data samples represent a physically stable state, it is often assumed that the data points represent the local minima of an energy landscape. In control theory, it is well-known that energy can serve as an effective…

Machine Learning · Computer Science 2024-02-09 Christopher Iliffe Sprague , Arne Elofsson , Hossein Azizpour

We present a second-order strictly length-preserving and unconditionally energy-stable rotational discrete gradient (Rdg) scheme for the numerical approximation of the Oseen-Frank gradient flows with anisotropic elastic energy functional.…

Numerical Analysis · Mathematics 2023-08-25 Jie Xu , Xiaotian Yang , Zhiguo Yang

We present a brief pedagogical review of theoretical Green's function methods applicable to open quantum systems out of equilibrium in general, and single molecule junctions in particular. We briefly describe experimental advances in…

Mesoscale and Nanoscale Physics · Physics 2020-03-10 Guy Cohen , Michael Galperin

In this paper, we show how the two-particle Green function (2PGF) can be obtained within the framework of the Dual Fermion approach. This facilitates the calculation of the susceptibility in strongly correlated systems where long-ranged…

Strongly Correlated Electrons · Physics 2009-11-13 S. Brener , H. Hafermann , A. N. Rubtsov , M. I. Katsnelson , A. I. Lichtenstein

Environmental concerns are driving the search for greener yet efficient solvents. Supercritical CO2 (scCO2) is a promising candidate due to its non-toxicity and the potential for reusing CO2 emissions. It also offers a versatile range of…

Chemical Physics · Physics 2024-06-06 Mohamed Houssein Mohamed , Luc Belloni , Daniel Borgis , Francesca Ingrosso , Antoine Carof

Despite its reasonable accuracy for ground-state properties of semiconductors and insulators, second-order Moller-Plesset perturbation theory (MP2) significantly underestimates band gaps. Here, we evaluate the band gap predictions of…

Materials Science · Physics 2021-09-15 Malte F. Lange , Timothy C. Berkelbach

It is shown that solutions to the 2nd order BFKL eigenvalue equation exist for arbitrary large real values of the complex angular momentum $j$. This corresponds to a cut in the complex $j$ plane along the whole real axis, and it makes the…

High Energy Physics - Phenomenology · Physics 2009-10-31 N. Armesto , J. Bartels , M. A. Braun

We introduce an energy functional for ground-state electronic structure calculations. Its variables are the natural spin-orbitals of singlet many-body wave functions and their joint occupation probabilities deriving from controlled…

Chemical Physics · Physics 2016-12-04 Ralph Gebauer , Morrel H. Cohen , Roberto Car

Nowadays stochastic approximation methods are one of the major research direction to deal with the large-scale machine learning problems. From stochastic first order methods, now the focus is shifting to stochastic second order methods due…

Machine Learning · Computer Science 2019-12-30 Vinod Kumar Chauhan , Anuj Sharma , Kalpana Dahiya
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