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The optimization of the conversion of thermal energy into work and the minimization of dissipation for nano- and mesoscopic systems is a complex challenge because of the important role fluctuations play on the dynamics of small systems. We…

Quantum Physics · Physics 2025-09-24 Alberto Rolandi

We propose an efficient dual boson scheme, which extends the DMFT paradigm to collective excitations in correlated systems. The theory is fully self-consistent both on the one- and on the two-particle level, thus describing the formation of…

Strongly Correlated Electrons · Physics 2016-01-12 E. A. Stepanov , E. G. C. P. van Loon , A. A. Katanin , A. I. Lichtenstein , M. I. Katsnelson , A. N. Rubtsov

We demonstrate that the effective Hamiltonians obtained with the downfolding procedure based on double unitary coupled cluster (DUCC) ansatz can be used in the context of Greens function coupled cluster (GFCC) formalism to calculate…

Computational Physics · Physics 2020-12-02 Nicholas P Bauman , Bo Peng , Karol Kowalski

We present a complete prescription for the numerical calculation of surface Green's functions and self-energies of semi-infinite quasi-onedimensional systems. Our work extends the results of Sanvito et al. [1] generating a robust algorithm…

Materials Science · Physics 2007-12-11 Ivan Rungger , Stefano Sanvito

A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in…

Strongly Correlated Electrons · Physics 2016-06-10 Kensaku Takai , Kota Ido , Takahiro Misawa , Youhei Yamaji , Masatoshi Imada

Time-dependent quantum mechanics provides an intuitive picture of particle propagation in external fields. Semiclassical methods link the classical trajectories of particles with their quantum mechanical propagation. Many analytical results…

Mesoscale and Nanoscale Physics · Physics 2008-03-07 Tobias Kramer , Eric J. Heller , Robert E. Parrott

The GW approximation is a well-known method to improve electronic structure predictions calculated within density functional theory. In this work, we have implemented a computationally efficient GW approach that calculates central…

Despite a large corpus of recent work on scaling up Gaussian processes, a stubborn trade-off between computational speed, prediction and uncertainty quantification accuracy, and customizability persists. This is because the vast majority of…

Machine Learning · Computer Science 2025-12-09 Marcus M. Noack , Mark D. Risser , Hengrui Luo , Vardaan Tekriwal , Ronald J. Pandolfi

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

In the nonequilibrium Green's function approach, the approximation of the correlation self-energy at the second-Born level is of particular interest, since it allows for a maximal speed-up in computational scaling when used together with…

Computational Physics · Physics 2019-11-11 Riku Tuovinen , Fabio Covito , Michael A. Sentef

The theory of Nonequilibrium Green functions (NEGF) has seen a rapid development over the recent three decades. Applications include diverse correlated many-body systems in and out of equilibrium. Very good agreement with experiments and…

Strongly Correlated Electrons · Physics 2026-04-02 Michael Bonitz , Jan-Philip Joost , Christopher Makait , Erik Schroedter , Tim Karsberger , Karsten Balzer

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

We present a systematical approach to developing arbitrarily high order, unconditionally energy stable numerical schemes for thermodynamically consistent gradient flow models that satisfy energy dissipation laws. Utilizing the energy…

Numerical Analysis · Mathematics 2020-02-19 Yuezheng Gong , Jia Zhao , Qi Wang

The disorder averaged single-particle Green's function of electrons subject to a time-dependent random potential with long-range spatial correlations is calculated by means of bosonization in arbitrary dimensions. For static disorder our…

Condensed Matter · Physics 2009-10-28 Peter Kopietz

Energy stable flux reconstruction (ESFR) is a high-order numerical method used for solving partial differential equations in computational fluid dynamics. This method is designed to preserve the energy stability of the underlying partial…

Fluid Dynamics · Physics 2023-09-08 Erwan Lambert , Siva Nadarajah

Functionals of the meta-generalized gradient approximation (MGGA) are nowadays widely used in chemistry and solid-state physics for the simulation of electronic systems like molecules, solids, or surfaces. Due to their dependency on the…

Materials Science · Physics 2022-05-31 Jan Doumont , Fabien Tran , Peter Blaha

We report an all-electron, atomic orbital (AO) based, two-component (2C) implementation of the $GW$ approximation (GWA) for closed-shell molecules. Our algorithm is based on the space-time formulation of the GWA and uses analytical…

Chemical Physics · Physics 2023-09-11 Arno Förster , Erik van Lenthe , Edoardo Spadetto , Lucas Visscher

The $GW$ approximation is a widely used framework for studying correlated materials, but it struggles with certain limitations, such as its inability to explain pseudogap phenomena. To overcome these problems, we propose a systematic…

Strongly Correlated Electrons · Physics 2024-09-26 Hui Li , Yingze Su , Junnian Xiong , Haiqing Lin , Huaqing Huang , Dingping Li

First-order stochastic methods are the state-of-the-art in large-scale machine learning optimization owing to efficient per-iteration complexity. Second-order methods, while able to provide faster convergence, have been much less explored…

Machine Learning · Statistics 2017-12-01 Naman Agarwal , Brian Bullins , Elad Hazan

We find a relation between the semiclassical approximation of the temperature (Matsubara) 2-point correlator and the corresponding classical Green function in real time at finite temperature. The anharmonic oscillator at finite temperature…

High Energy Physics - Phenomenology · Physics 2009-12-30 A. Bochkarev