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Entanglement is the key resource for quantum technologies and is at the root of exciting many-body phenomena. However, quantifying the entanglement between two parts of a real-world quantum system is challenging when it interacts with its…

Quantum Physics · Physics 2023-03-22 Christian Carisch , Oded Zilberberg

In the past two decades, the density matrix renormalization group (DMRG) has emerged as an innovative new method in quantum chemistry relying on a theoretical framework very different from that of traditional electronic structure…

Computational Physics · Physics 2020-02-18 Alberto Baiardi , Markus Reiher

We present the reaction-coordinate polaron-transform (RCPT) framework for generating effective Hamiltonian models to treat nonequilibrium open quantum systems at strong coupling with their surroundings. Our approach, which is based on two…

Quantum Physics · Physics 2022-11-11 Nicholas Anto-Sztrikacs , Ahsan Nazir , Dvira Segal

Density-functional theory (DFT) has revolutionized computer simulations in chemistry and material science. A faithful implementation of the theory requires self-consistent calculations. However, this effort involves repeatedly diagonalizing…

Quantum Physics · Physics 2023-07-17 Taehee Ko , Xiantao Li , Chunhao Wang

We present a universal thermodynamic framework for quantum systems that may be strongly coupled to thermal environments. Unlike previous approaches, our method enables a clear definition of thermostatic properties while preserving the same…

Quantum Physics · Physics 2026-04-16 Ignacio González , Sagnik Chakraborty , Ángel Rivas

We study one dimensional models of diatomic molecules where both the electrons and nuclei are treated as quantum particles, going beyond the usual Born-Oppenheimer approximation. The continuous system is approximated by a grid which…

Strongly Correlated Electrons · Physics 2020-10-02 Mingru Yang , Steven R. White

Density fitting is used throughout quantum chemistry to simplify the electron-electron interaction energy (EE). A fundamental property of quantum chemistry, and DFT in particular, is that a variational principle connects the EE to a…

Materials Science · Physics 2016-06-08 Brett I Dunlap , Mark C Palenik

Thin beams made of magnetorheological elastomers embedded with hard magnetic particles (hard-MREs) are capable of large deflections under an applied magnetic field. We propose a comprehensive framework, comprising a beam model and 3D finite…

Soft Condensed Matter · Physics 2021-07-01 Dong Yan , Arefeh Abbasi , Pedro M. Reis

We present a novel multi-scale embedding scheme that links conventional QM/MM embedding and bootstrap embedding (BE) to allow simulations of large chemical systems on limited quantum devices. We also propose a mixed-basis BE scheme that…

We use concepts from quantum cryptography to relate the entanglement in many-body mixed states to standard correlation functions. If a system can be used as a resource for distilling private keys -- random classical bits that are shared by…

Quantum Physics · Physics 2026-03-13 Samuel J. Garratt , Max McGinley

In a recent letter we presented a framework for predicting the concentrations of many-particle local structures inside the bulk liquid as a route to assessing changes in the liquid approaching dynamical arrest. Central to this framework was…

Statistical Mechanics · Physics 2019-12-25 Joshua F. Robinson , Francesco Turci , Roland Roth , C. Paddy Royall

Given a partition of a large system into an active quantum mechanical (QM) region and its environment, we present a simple way of embedding the QM region into an effective electrostatic potential representing the environment. This potential…

Chemical Physics · Physics 2017-07-20 Stephan Mohr , Michel Masella , Laura E. Ratcliff , Luigi Genovese

Multi-configurational wave-function theory (MC-WFT) that combines complete active space self-consistent field (CASSCF) approach with subsequent state interaction (SI) treatment of spin-orbit coupling (SOC), abbreviated as CASSCF-SO, plays…

Chemical Physics · Physics 2025-03-11 Zhe-Bin Guan , Hong Jiang

Packing problems have been a source of fascination for millenia and their study has produced a rich literature that spans numerous disciplines. Investigations of hard-particle packing models have provided basic insights into the structure…

Statistical Mechanics · Physics 2018-08-01 Salvatore Torquato

Dephasing is the loss of phase coherence due to the interaction of an electron with the environment. The most common approach to model dephasing in light-matter interaction is the relaxation time approximation. Surprisingly, its use in…

A critical challenge for density functional theory (DFT) in practice is its limited ability to treat static electron correlation, leading to errors in its prediction of charges, multiradicals, and reaction barriers. Recently, we combined…

Chemical Physics · Physics 2024-11-05 Daniel Gibney , Jan-Niklas Boyn , David A. Mazziotti

We present a quantum theoretical treatment of light-matter coupling in the system consisting of a quantum dot and a spherical core-shell metal-dielectric multilayer nanoparticle. It is shown that both weak and strong coupling regimes can be…

Optics · Physics 2015-12-18 Mehedi Hasan , Ivan Iorsh , Pavel Belov

We investigate the entanglement for a model of a particle moving in the lattice (many-body system). The interaction between the particle and the lattice is modelled using Hooke's law. The Feynman path integral approach is applied to compute…

Mathematical Physics · Physics 2014-06-26 Chisanupong Puttarprom , Sikarin Yoo-Kong , Monsit Tanasittikisol , Watchara Liewrian

Repulsively interacting particles in a periodic potential can form bound composite objects, whose dissociation is suppressed by a band gap. Nearly pure samples of such repulsively bound pairs of cold atoms -- "dimers" -- have recently been…

Other Condensed Matter · Physics 2008-03-31 David Petrosyan , Bernd Schmidt , James R. Anglin , Michael Fleischhauer

This paper introduces a novel approach to probabilistic deep learning, kernel density matrices, which provide a simpler yet effective mechanism for representing joint probability distributions of both continuous and discrete random…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Raúl Ramos-Pollán , Joseph A. Gallego-Mejia
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