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Ensemble Density Functional Theory (EDFT) is a generalization of ground-state Density Functional Theory (GS DFT), which is based on an exact formal theory of finite collections of a system's ground and excited states. EDFT in various forms…

Materials Science · Physics 2024-08-27 Remi J. Leano , Aurora Pribram-Jones , David A. Strubbe

It was recently shown [Y. Suzuki, L. Lacombe, K. Watanabe, and N. T. Maitra, Phys. Rev. Lett. 119, 263401 (2017)] that peak and valley structures in the exact exchange-correlation potential of time-dependent density functional theory are…

Chemical Physics · Physics 2018-07-04 Lionel Lacombe , Yasumitsu Suzuki , Kazuyuki Watanabe , Neepa T. Maitra

The equivalence in one-electron quantum bath between the practical implementation of density matrix embedding theory (DMET) and the more recent Householder-transformed density matrix functional embedding theory has been shown previously in…

Chemical Physics · Physics 2023-07-24 Sajanthan Sekaran , Oussama Bindech , Emmanuel Fromager

The interaction between the electromagnetic field and plasmonic nanostructures leads to both the strong linear response and inherent nonlinear behavior. In this paper, a time-domain hydrodynamic model for describing the motion of electrons…

Optics · Physics 2017-09-19 Ming Fang , Zhixiang Huang , Wei E. I. Sha , Xianliang Wu

Many-body physics is one very well suited field for testing quantum algorithms and for finding working heuristics on present quantum computers. We have investigated the non-equilibrium dynamics of one- and two-electron systems, which are…

Quantum Physics · Physics 2022-07-06 Sabine Tornow , Wolfgang Gehrke , Udo Helmbrecht

An approach to non-adiabatic dynamics of atoms in molecular and condensed matter systems under general non-equilibrium conditions is proposed. In this method interaction between nuclei and electrons is considered explicitly up to the second…

Materials Science · Physics 2018-08-01 L. Kantorovich

Dynamic mode decomposition (DMD) has emerged as a popular data-driven modeling approach to identifying spatio-temporal coherent structures in dynamical systems, owing to its strong relation with the Koopman operator. For dynamical systems…

Signal Processing · Electrical Eng. & Systems 2021-10-26 Manu Krishnan , Serkan Gugercin , Pablo A. Tarazaga

Simulating the long-term dynamics of multi-scale and multi-physics systems poses a significant challenge in understanding complex phenomena across science and engineering. The complexity arises from the intricate interactions between scales…

Machine Learning · Computer Science 2025-09-22 Da Long , Shandian Zhe , Samuel Williams , Leonid Oliker , Zhe Bai

The construction of meta generalized gradient approximations based on the density matrix expansion (DME) is considered as one of the most accurate technique to design semilocal exchange energy functionals in two-dimensional density…

Materials Science · Physics 2018-05-09 Abhilash Patra , Subrata Jana , Prasanjit Samal

We argue in favour of developing a comprehensive dynamical theory for rationalizing, predicting, designing, and machine learning nonequilibrium phenomena that occur in soft matter. To give guidance for navigating the theoretical and…

Soft Condensed Matter · Physics 2024-02-28 Daniel de las Heras , Toni Zimmermann , Florian Sammüller , Sophie Hermann , Matthias Schmidt

We introduce an extension of the non-equilibrium dynamical mean field theory to incorporate the effects of static random disorder in the dynamics of a many-particle system by integrating out different disorder configurations resulting in an…

Strongly Correlated Electrons · Physics 2025-04-28 Chakradhar Rangi , Herbert F Fotso , Hanna Terletska , Juana Moreno , Ka-Ming Tam

The ground state energy of a many-electron system can be approximated by an variational approach in which the total energy of the system is minimized with respect to one and two-body reduced density matrices (RDM) instead of many-electron…

Optimization and Control · Mathematics 2017-09-01 Yongfeng Li , Zaiwen Wen , Chao Yang , Yaxiang Yuan

We present a systematic, quasi-automated methodology for generating electronic models in the framework of second-principles density functional theory (SPDFT). This approach enables the construction of accurate and computationally efficient…

The use of ring polymer molecular dynamics (RPMD) for the direct simulation of electron transfer (ET) reaction dynamics is analyzed in the context of Marcus theory, semiclassical instanton theory, and exact quantum dynamics approaches. For…

Statistical Mechanics · Physics 2011-08-19 Artur R. Menzeleev , Nandini Ananth , Thomas F. Miller

Computing ground-state properties of molecules is a promising application for quantum computers operating in concert with classical high-performance computing resources. Quantum embedding methods are a family of algorithms particularly…

Machine learning for scientific applications faces the challenge of limited data. We propose a framework that leverages a priori known physics to reduce overfitting when training on relatively small datasets. A deep neural network is…

Machine Learning · Computer Science 2019-11-22 Jonathan B. Freund , Jonathan F. MacArt , Justin Sirignano

Integration of physics principles with data-driven methods has attracted great attention in recent few years. In this study, a physics-informed dynamic mode decomposition (piDMD) method, where the mass conservation law is integrated with a…

Fluid Dynamics · Physics 2023-11-07 Dandan Li , Bidan Zhao , Shuai Lu , Junwu Wang

Frozen Density Embedding (FDE) represents a versatile embedding scheme to describe the environmental effect on the electron dynamics in molecular systems. The extension of the general theory of FDE to the real-time time-dependent Kohn-Sham…

Density functional theory (DFT), one of the most widely utilized methods available to computational chemistry, fails to describe systems with statically correlated electrons. To address this shortcoming, in previous work we transformed DFT…

Chemical Physics · Physics 2023-01-02 Daniel Gibney , Jan-Niklas Boyn , David A. Mazziotti

Quantum embedding schemes have the potential to significantly reduce the computational cost of first principles calculations, whilst maintaining accuracy, particularly for calculations of electronic excitations in complex systems. In this…

Materials Science · Physics 2022-03-10 Joseph C. A. Prentice