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Density functional theory (DFT) and linear-response time-dependent density functional theory (LR-TDDFT) rely on an exchange-correlation (xc) approximation that provides not only energy but also its functional derivatives that enter the…

Chemical Physics · Physics 2026-04-08 Xiaoyu Zhang

We formulate a rigorous method for calculating a nonadiabatic (frequency-dependent) exchange-correlation (XC) kernel required for correct description of both equilibrium and nonequilibrium properties of strongly correlated systems within…

Strongly Correlated Electrons · Physics 2014-10-13 Volodymyr Turkowski , Talat S. Rahman

Transition path sampling is a rare-event method that estimates state-to-state timecorrelation functions in many-body systems from samples of short trajectories. In this framework, it is proposed to bias the importance function using the…

Chemical Physics · Physics 2015-03-13 Manuel Athènes , Mihai-Cosmin Marinica , Thomas Jourdan

We describe CPMC-Lab, a Matlab program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to…

Strongly Correlated Electrons · Physics 2014-10-14 Huy Nguyen , Hao Shi , Jie Xu , Shiwei Zhang

We evaluate the density matrix of an arbitrary quantum mechanical system in terms of the quantities pertinent to the solution of the time-dependent density functional theory (TDDFT) problem. Our theory utilizes the adiabatic connection…

Mesoscale and Nanoscale Physics · Physics 2019-09-04 Vladimir U. Nazarov

The self-energy-functional approach proposed recently is applied to the single-band Hubbard model at half-filling to study the Mott-Hubbard metal-insulator transition within the most simple but non-trivial approximation. This leads to a…

Strongly Correlated Electrons · Physics 2007-05-23 M. Potthoff

We propose a novel approach to parameter estimation for simulator-based statistical models with intractable likelihood. Our proposed method involves recursive application of kernel ABC and kernel herding to the same observed data. We…

Machine Learning · Statistics 2018-06-13 Takafumi Kajihara , Motonobu Kanagawa , Keisuke Yamazaki , Kenji Fukumizu

An effective low-energy model describing magnetic properties of alkali-cluster-loaded sodalites is derived by {\em ab initio} downfolding. We start with constructing an extended Hubbard model for maximally localized Wannier functions. {\em…

Strongly Correlated Electrons · Physics 2010-10-20 Kazuma Nakamura , Takashi Koretsune , Ryotaro Arita

Electronic correlated systems are often well described by dynamical mean field theory (DMFT). While DMFT studies have mainly focused hitherto on one-particle properties, valuable information is also enclosed into local two-particle Green's…

Strongly Correlated Electrons · Physics 2012-09-25 Georg Rohringer , Angelo Valli , Alessandro Toschi

A theoretical analysis of the thermodynamic response functions of the 2D single-band Hubbard model is realized by means of the composite operator method. It is shown that all the features of these quantities can be explained by looking at…

Strongly Correlated Electrons · Physics 2008-02-03 F. Mancini , D. Villani , H. Matsumoto

As the electrification process advances, enormous power flexibility is becoming available on the demand side, which can be harnessed to facilitate power system decarbonization. Hence, this paper studies the carbon-aware demand response…

Systems and Control · Electrical Eng. & Systems 2024-07-30 Xin Chen

While the ground state of magnetic materials is in general well described on the basis of spin density functional theory (SDFT), the theoretical description of finite-temperature and non-equilibrium properties require an extension beyond…

Materials Science · Physics 2022-06-22 Sergiy Mankovsky , Hubert Ebert

Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical systems. Previous works have attempted to accelerate LR-TDDFT using heterogeneous…

Hardware Architecture · Computer Science 2025-04-07 Qingcai Jiang , Buxin Tu , Xiaoyu Hao , Junshi Chen , Hong An

The DCA$^+$ algortihm was recently introduced to extend the dynamic cluster approximation (DCA) with a continuous lattice self-energy in order to achieve better convergence with cluster size. Here we extend the DCA$^+$ algorithm to the…

Strongly Correlated Electrons · Physics 2015-06-18 Peter Staar , Thomas Maier , Thomas Schulthess

The time-dependent density functional theory (TDDFT) provides a unified description of the structure and reaction. The linear approximation leads to the random-phase approximation (RPA) which is capable of describing a variety of collective…

Nuclear Theory · Physics 2016-05-09 Kai Wen , Kouhei Washiyama , Ni Fang , Takashi Nakatsukasa

Model Hamiltonians are regularly derived from first-principles data to describe correlated matter. However, the standard methods for this contain a number of largely unexplored approximations. For a strongly correlated impurity model…

This paper proposes a novel scheme for reduced-rank Gaussian process regression. The method is based on an approximate series expansion of the covariance function in terms of an eigenfunction expansion of the Laplace operator in a compact…

Machine Learning · Statistics 2020-06-26 Arno Solin , Simo Särkkä

Real-time time-dependent density functional theory (TDDFT) is widely considered to be the most accurate available method for calculating electronic stopping powers from first principles, but there have been relatively few assessments of the…

Computational Physics · Physics 2024-01-18 Alina Kononov , Alexander J. White , Katarina A. Nichols , S. X. Hu , Andrew D. Baczewski

Pump-probe experiments have turned out as a powerful tool in order to study the dynamics of competing orders in a large variety of materials. The corresponding analysis of the data often relies on standard linear-response theory generalized…

Strongly Correlated Electrons · Physics 2018-01-03 Jörg Bünemann , Götz Seibold

An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows to understand important characteristics like thermodynamic,…

Materials Science · Physics 2016-08-03 Bastian Schaefer , Stefan Goedecker