English
Related papers

Related papers: Density functionals from deep learning

200 papers

A framework for developing new approximate electronic structure methods is presented, in which the correlation energy of a many-electron system in the ground state is computed as in the single-reference second-order many-body perturbation…

Chemical Physics · Physics 2011-06-15 Dimitri Laikov

One of the fundamental problems in machine learning is the estimation of a probability distribution from data. Many techniques have been proposed to study the structure of data, most often building around the assumption that observations…

Machine Learning · Statistics 2013-02-22 Oren Rippel , Ryan Prescott Adams

By combining methods of kinetic and density functional theory, we present a description of molecular fluids which accounts for their microscopic structure and thermodynamic properties as well as for the hydrodynamic behavior. We focus on…

Mesoscale and Nanoscale Physics · Physics 2015-05-18 Umberto Marini Bettolo Marconi , Simone Melchionna

An approach to generalize any kind of collinear functionals in density functional theory to non-collinear functionals is proposed. This approach, for the very first time, satisfies the correct collinear limit for any kind of functionals,…

Quantum Physics · Physics 2023-01-26 Zhichen Pu , Hao Li , Qiming Sun , Ning Zhang , Yong Zhang , Sihong Shao , Hong Jiang , Yiqin Gao , Yunlong Xiao

I review the quantum theory of the electron moving in a random environment. First, the quantum mechanics of individual particles scattered on a random potential is discussed. The quantum-mechanical description is extended to many-body…

Disordered Systems and Neural Networks · Physics 2021-09-13 Václav Janiš

Two forms of relativistic density functional are derived from Dirac equation. Based on their structure analysis model of split electron is proposed. In this model electric charge and mass of electron behave like two point-like particles. It…

Quantum Physics · Physics 2015-05-29 Kirill Koshelev

We present a rigorous formulation of generalized Kohn-Sham density-functional theory. This provides a straightforward Kohn-Sham description of many-body systems based not only on particle-density but also on any other observable. We…

Strongly Correlated Electrons · Physics 2008-02-03 M. Valiev , G. W. Fernando

We develop a novel data-driven approach to the inverse problem of classical statistical mechanics: given experimental data on the collective motion of a classical many-body system, how does one characterise the free energy landscape of that…

Statistical Mechanics · Physics 2022-03-01 Peter Yatsyshin , Serafim Kalliadasis , Andrew B. Duncan

We showcase the advantages of orbital-free density-potential functional theory (DPFT), a more flexible variant of Hohenberg-Kohn density functional theory. DPFT resolves the usual trouble with the gradient-expanded kinetic energy functional…

Quantum Gases · Physics 2021-06-16 Martin-Isbjörn Trappe , Jun Hao Hue , Berthold-Georg Englert

Spectral density functions quantify how environmental modes couple to quantum systems and govern their open dynamics. Inferring such frequency-dependent functions from time-domain measurements is an ill-conditioned inverse problem. Here, we…

Potential functional approximations are an intriguing alternative to density functional approximations. The potential functional that is dual to the Lieb density functional is defined and properties given. The relationship between…

Other Condensed Matter · Physics 2014-01-08 Attila Cangi , E. K. U. Gross , Kieron Burke

According to density functional theory, any chemical property can be inferred from the electron density, making it the most informative attribute of an atomic structure. In this work, we demonstrate the use of established physical methods…

Materials Science · Physics 2023-09-12 Ethan M. Sunshine , Muhammed Shuaibi , Zachary W. Ulissi , John R. Kitchin

Density functional theory (DFT) became a universal approach to compute ground-state and excited configurations of many-electron systems held together by an external one-body potential in condensed-matter, atomic, and molecular physics. At…

Nuclear Theory · Physics 2011-09-30 J. Dobaczewski

Nanoscale optoelectronics and molecular-electronics systems operate with current injection and nonequilibrium tunneling, phenomena that challenge consistent descriptions of the steady-state transport. The current affects the…

Other Condensed Matter · Physics 2009-11-13 Per Hyldgaard

Nuclear density functional theory (DFT) is the only microscopic, global approach to the structure of atomic nuclei. It is used in numerous applications, from determining the limits of stability to gaining a deep understanding of the…

Nuclear Theory · Physics 2015-02-06 Nicolas Schunck , Jordan D. McDonnell , Jason Sarich , Stefan M. Wild , Dave Higdon

A simple mathematical extension of quantum theory is presented. As well as opening the possibility of alternative methods of calculation, the additional formalism implies a new physical interpretation of the standard theory by providing a…

Quantum Physics · Physics 2020-03-17 Roderick Sutherland

Density scaling has a rich history in density functional theory, providing exact conditions for use in the construction of ever more accurate approximations to the unknown exchange-correlation functional. We define a conjugate potential…

Other Condensed Matter · Physics 2009-06-02 Peter Elliott , Kieron Burke

We develop an ensemble density functional theory for the fractional quantum Hall effect using a local density approximation. Model calculations for edge reconstructions of a spin-polarized quantum dot give results in good agreement with…

Condensed Matter · Physics 2009-10-28 O. Heinonen , M. I. Lubin , M. D. Johnson

Density functional theory (DFT) has become the most popular approach to electronic structure across disciplines, especially in material and chemical sciences. Last year, at least 30,000 papers used DFT to make useful predictions or give…

Chemical Physics · Physics 2017-01-05 Justin C. Smith , Francisca Sagredo , Kieron Burke

Neural network models can now recognise images, understand text, translate languages, and play many human games at human or superhuman levels. These systems are highly abstracted, but are inspired by biological brains and use only…

Neurons and Cognition · Quantitative Biology 2019-03-06 Katherine R. Storrs , Nikolaus Kriegeskorte
‹ Prev 1 8 9 10 Next ›