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This paper aims at introducing the formal foundations of the application of reduced density-matrix theory and Green's function theory to the analysis of molecular electronic transitions. For this sake, their mechanics, applied to specific…

Chemical Physics · Physics 2022-08-09 Thibaud Etienne

The superfluid stiffness fundamentally constrains the transition temperature of superconductors, especially in the strongly coupled regime. However, accurately determining this inherently quantum many-body property in microscopic models…

Strongly Correlated Electrons · Physics 2026-04-23 Qiang Gao , Zhaoyu Han , Eslam Khalaf

Quantum computing has shown great potential in various quantum chemical applications such as drug discovery, material design, and catalyst optimization. Although significant progress has been made in quantum simulation of simple molecules,…

Quantum Physics · Physics 2023-05-30 Changsu Cao , Jinzhao Sun , Xiao Yuan , Han-Shi Hu , Hung Q. Pham , Dingshun Lv

As a new approach to efficiently describe correlation effects in the relativistic quantum world we propose to consider reduced density matrix functional theory, where the key quantity is the first-order reduced density matrix (1-RDM). In…

Chemical Physics · Physics 2022-05-05 M. Rodríguez-Mayorga , K. J. H. Giesbertz , L. Visscher

This paper derives and demonstrates a new, purely density-based ab initio approach for calculation of the energies and properties of many-electron systems. It is based upon the discovery of relationships that govern the "mechanics" of the…

Chemical Physics · Physics 2024-09-04 James C. Ellenbogen

Excited-state properties of highly correlated systems are key to understanding photosynthesis, luminescence, and the development of novel optical materials, but accurately capturing their interactions is computationally costly. We present…

Quantum Physics · Physics 2024-08-21 Irma Avdic , David A. Mazziotti

The direct variational optimization of the two-electron reduced density matrix (2RDM) can provide a reference-independent description of the electronic structure of many-electron systems that naturally captures strong or nondynamic…

Chemical Physics · Physics 2024-06-19 Run R. Li , Marcus D. Liebenthal , A. Eugene DePrince

In this work we explore the performance of approximations to electron correlation in reduced density-matrix functional theory (RDMFT) and of approximations to the observables calculated within this theory. Our analysis focuses on the…

Strongly Correlated Electrons · Physics 2015-02-26 Stefano Di Sabatino , Jan A. Berger , Lucia Reining , Pina Romaniello

Many electronic structure methods rely on the minimization of the energy of the system with respect to the one-body reduced density matrix (1-RDM). To formulate a minimization algorithm, the 1-RDM is often expressed in terms of its…

Chemical Physics · Physics 2025-04-18 Nicolas Cartier , Klaas Giesbertz

We introduce a data-driven framework for approximating the convex set of $N$-representable two-electron reduced density matrices (2-RDMs). Traditional approaches characterize this set through linear matrix inequalities that define its…

Chemical Physics · Physics 2026-03-09 Luis H. Delgado-Granados , David A. Mazziotti

Quantum algorithms for molecular electronic structure have been developed with lower computational scaling than their classical counterparts, but emerging quantum hardware is far from being capable of the coherence,connectivity and gate…

Quantum Physics · Physics 2020-04-17 Scott E. Smart , David A. Mazziotti

A model to describe electronic correlations in energy bands is considered. The model is a generalization of the conventional Hubbard model that allows for the fact that the wavefunction for two electrons occupying the same Wannier orbital…

Strongly Correlated Electrons · Physics 2009-11-07 J. E. Hirsch

Classical shadow tomography offers a scalable route to estimating properties of quantum states, but the resulting reduced density matrices (RDMs) often violate constraints that ensure they represent $N$-electron states -- known as…

The methods of quantum chemistry and solid state theory to solve the many-body problem are reviewed. We start with the definitions of reduced density matrices, their properties (contraction sum rules, spectral resolutions, cumulant…

Strongly Correlated Electrons · Physics 2007-05-23 P. Ziesche , F. Tasnadi

The second-order reduced density matrix method (the RDM method) has performed well in determining energies and properties of atomic and molecular systems, achieving coupled-cluster singles and doubles with perturbative triples (CC SD(T))…

Strongly Correlated Electrons · Physics 2012-07-23 James S. M. Anderson , Maho Nakata , Ryo Igarashi , Katsuki Fujisawa , Makoto Yamashita

Quantum state tomography is a fundamental task in quantum information science, enabling detailed characterization of correlations, entanglement, and electronic structure in quantum systems. However, its exponential measurement and…

We compute the electronic structure of two-dimensional (2D) materials decorated with self-assembled organic monolayers using density functional theory. We find that 2D materials are strongly impacted by near-field electrostatic effects…

Materials Science · Physics 2021-09-22 Qunfei Zhou , Bukuru Anaclet , Trevor Steiner , Michele Kotiuga , Pierre Darancet

A reduced-density-matrix (RDM)-based approach to {\em ab initio} cavity quantum electrodynamics (QED) is developed. The expectation value of the Pauli-Fierz Hamiltonian is expressed in terms of one- and two-body electronic and photonic…

Chemical Physics · Physics 2022-11-23 Joel D. Mallory , A. Eugene DePrince

Molecular dynamics simulations are indispensable for exploring the behavior of atoms and molecules. Grounded in quantum mechanical principles, quantum molecular dynamics provides high predictive power but its computational cost is dominated…

Chemical Physics · Physics 2025-09-10 Siu Wun Cheung , Youngsoo Choi , Jean-Luc Fattebert , Daniel Osei-Kuffuor

Choosing optimal representation methods of atomic and electronic structures is essential when machine learning properties of materials. We address the problem of representing quantum states of electrons in a solid for the purpose of machine…

Computational Physics · Physics 2022-02-08 Nikolaj Rørbæk Knøsgaard , Kristian Sommer Thygesen