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Understanding strongly correlated systems is essential for advancing quantum chemistry and materials science, yet conventional methods like Density Functional Theory (DFT) often fail to capture their complex electronic behavior. To address…

Chemical Physics · Physics 2025-09-01 Archith Rayabharam , N. R. Aluru

The congruent transformation of the electronic Hamiltonian is developed to address the electron correlation problem in many-electron systems. The central strategy presented in this method is to perform transformation on the electronic…

Chemical Physics · Physics 2012-12-21 Jennifer M. Elward , Johannes Hoja , Arindam Chakraborty

In this study we consider the Hamiltonian approach for the construction of a map for a system with nonlinear resonant interaction, including phase trapping and phase bunching effects. We derive basic equations for a single resonant…

Variational approaches are among the most powerful modern techniques to approximately solve quantum many-body problems. These encompass both variational states based on tensor or neural networks, and parameterized quantum circuits in…

Strongly Correlated Electrons · Physics 2021-02-02 Kevin Zhang , Samuel Lederer , Kenny Choo , Titus Neupert , Giuseppe Carleo , Eun-Ah Kim

The famous, yet unsolved, Fermi-Hubbard model for strongly-correlated electronic systems is a prominent target for quantum computers. However, accurately representing the Fermi-Hubbard ground state for large instances may be beyond the…

A new approach to the path integral over fermionic fields, based on the extension of a reformulation of the adiabatic approximation to some quantum mechanical systems, is presented. A novel non-analytic contribution to the efective…

High Energy Physics - Phenomenology · Physics 2012-03-15 J. L. Cortes , J. Gamboa , S. Lepe , J. Lopez-Sarrion

This work introduces a new framework integrating port-Hamiltonian systems (PHS) and neural network architectures. This framework bridges the gap between deterministic and stochastic modeling of complex dynamical systems. We introduce new…

Mathematical Physics · Physics 2025-09-09 Luca Di Persio , Matthias Ehrhardt , Youness Outaleb , Sofia Rizzotto

The precise description of quantum nuclear fluctuations in atomistic modelling is possible by employing path integral techniques, which involve a considerable computational overhead due to the need of simulating multiple replicas of the…

Chemical Physics · Physics 2017-03-23 Venkat Kapil , Jörg Behler , Michele Ceriotti

We propose new approach for treatment of local and non-local interactions in correlated electronic systems, which uses self-energy and the two-particle irreducible vertices, obtained from (extended) dynamical mean-field theory, as an input…

Strongly Correlated Electrons · Physics 2019-03-12 A. A. Katanin

Generic mesoscopic quantum systems that interact with their environment tend to display appreciable correlations with environment that often play an important role in the physical properties of the system. However, the experimental methods…

Quantum Physics · Physics 2021-07-14 Parth Jatakia , Sai Vinjanampathy , Kasturi Saha

Strongly interacting particles in one dimension subject to external confinement have become a topic of considerable interest due to recent experimental advances and the development of new theoretical methods to attack such systems. In the…

Quantum Physics · Physics 2020-09-10 A. S. Dehkharghani , A. G. Volosniev , N. T. Zinner

Variational algorithms for strongly correlated chemical and materials systems are one of the most promising applications of near-term quantum computers. We present an extension to the variational quantum eigensolver that approximates the…

Quantum Physics · Physics 2020-08-26 William J. Huggins , Joonho Lee , Unpil Baek , Bryan O'Gorman , K. Birgitta Whaley

Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical and computational…

Strongly Correlated Electrons · Physics 2024-11-07 Jannes Nys , Gabriel Pescia , Alessandro Sinibaldi , Giuseppe Carleo

We develop a variational Monte Carlo (VMC) method for electron-phonon coupled systems. The VMC method has been extensively used for investigating strongly correlated electrons over the last decades. However, its applications to…

Strongly Correlated Electrons · Physics 2014-06-02 Takahiro Ohgoe , Masatoshi Imada

The so-called phaseless quantum Monte-Carlo method currently offers one of the best performing theoretical framework to investigate interacting Fermi systems. It allows to extract an approximate ground-state wavefunction by averaging…

Strongly Correlated Electrons · Physics 2017-03-31 Olivier Juillet , Alexandre Leprévost , Jérémy Bonnard , Raymond Frésard

Feynman's path integral approach is to sum over all possible spatio-temporal paths to reproduce the quantum wave function and the corresponding time evolution, which has enormous potential to reveal quantum processes in classical view.…

We develop a strong coupling approach for a general lattice problem. We argue that this strong coupling perspective represents the natural framework for a generalization of the dynamical mean field theory (DMFT). The main result of this…

Strongly Correlated Electrons · Physics 2009-11-10 Tudor D. Stanescu , Gabriel Kotliar

We follow up on our previous works which presented a possible approach for deriving symplectic schemes for a certain class of highly oscillatory Hamiltonian systems. The approach considers the Hamilton-Jacobi form of the equations of…

Numerical Analysis · Mathematics 2010-08-06 Matthew Dobson , Claude Le Bris , Frederic Legoll

The nonclassical behaviors of a two-level system coupled to a harmonic oscillator is investigated in the ultrastrong coupling regime. We revisit the variational solution of the ground state and find that the existing solution do not account…

Mesoscale and Nanoscale Physics · Physics 2010-09-01 Myung-Joong Hwang , Mahn-Soo Choi

Port-Hamiltonian neural networks (pHNNs) are emerging as a powerful modeling tool that integrates physical laws with deep learning techniques. While most research has focused on modeling the entire dynamics of interconnected systems, the…

Systems and Control · Electrical Eng. & Systems 2024-11-11 G. J. E. van Otterdijk , S. Moradi , S. Weiland , R. Tóth , N. O. Jaensson , M. Schoukens