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A large collaboration carefully benchmarks 20 first principles many-body electronic structure methods on a test set of 7 transition metal atoms, and their ions and monoxides. Good agreement is attained between the 3 systematically converged…

Many-body forces are sometimes a relevant ingredient in various fields, such as atomic, nuclear or hadronic physics. Their precise structure is generally difficult to uncover. So, phenomenological effective forces are often used in…

Quantum Physics · Physics 2018-07-19 Claude Semay , Guillaume Sicorello

We develop a variational approach at finite temperature that incorporates many-body correlation self-consistently. The grand potential is constructed in terms of Green's function expressed by the variational parameters. We apply this…

Quantum Gases · Physics 2019-05-30 Akimitsu Kirikoshi , Wataru Kohno , Takafumi Kita

A finite-temperature many-body perturbation theory is presented that expands in power series the electronic grand potential, chemical potential, internal energy, and entropy on an equal footing. Sum-over-states and sum-over-orbitals…

Chemical Physics · Physics 2020-07-15 So Hirata , Punit K. Jha

Many-body forces, and specially three-body forces, are sometimes a relevant ingredient in various fields, such as atomic, nuclear or hadronic physics. As their precise structure is generally difficult to uncover or to implement,…

Quantum Physics · Physics 2024-03-12 Lorenzo Cimino , Clara Tourbez , Cyrille Chevalier , Gwendolyn Lacroix , Claude Semay

Many-body descriptors are widely used to represent atomic environments in the construction of machine learned interatomic potentials and more broadly for fitting, classification and embedding tasks on atomic structures. It was generally…

Introducing low-energy effective Hamiltonians is usual to grasp most correlations in quantum many-body problems. For instance, such effective Hamiltonians can be treated at the mean-field level to reproduce some physical properties of…

Quantum Gases · Physics 2025-01-09 Raphaël Photopoulos , Antoine Boulet

We describe and test an implicit solvent all-atom potential for simulations of protein folding and aggregation. The potential is developed through studies of structural and thermodynamic properties of 17 peptides with diverse secondary…

Biomolecules · Quantitative Biology 2009-04-09 Anders Irbäck , Simon Mitternacht , Sandipan Mohanty

We propose a new many-body method based on the correlation functions, in which the multiple products of the correlation functions are expanded into the many-body diagrams using the cluster expansion method and every diagram is independently…

In this work we develop a complete variational many-body theory for a system of $N$ trapped bosons interacting via a general two-body potential. In this theory both the many-body basis functions {\em and} the respective expansion…

Other Condensed Matter · Physics 2009-11-11 Alexej I. Streltsov , Ofir E. Alon , Lorenz S. Cederbaum

Dense neutrino gases form in extreme astrophysical sites, and the flavor content of the neutrinos likely has an important impact on the subsequent dynamical evolution of their environment. Through coherent forward scattering among…

High Energy Physics - Phenomenology · Physics 2023-01-18 Joshua D. Martin , A. Roggero , Huaiyu Duan , J. Carlson

A correlated many-body calculation is presented to characterize the Shannon information entropy of trapped interacting bosons. We reformulate the one-body Shannon information entropy in terms of the one-body probability density. The minimum…

Quantum Gases · Physics 2013-09-16 Sudip Kumar Haldar , Barnali Chakrabarti , Tapan Kumar Das , Anindya Biswas

Quantifying the effects of amino acid mutations in proteins presents a significant challenge due to the vast combinations of residue sites and amino acid types, making experimental approaches costly and time-consuming. The Potts model has…

Methodology · Statistics 2025-05-22 Bingying Dai , Yinan Lin , Kejue Jia , Zhao Ren , Wen Zhou

With the evolution of numerical methods, we are now aiming at not only qualitative understanding but also quantitative prediction and design of quantum many-body phenomena. As a novel numerical approach, machine learning techniques have…

Strongly Correlated Electrons · Physics 2024-12-20 Yusuke Nomura , Masatoshi Imada

Recent developments of experimental techniques in the field of ultra-cold gases open a path to study the crossover from 'few' to 'many' on the quantum level. In this case, accurate description of inter-particle correlations is very…

Quantum Gases · Physics 2018-03-23 Marcin Płodzień , Dariusz Wiater , Andrzej Chrostowski , Tomasz Sowiński

In many-body theory it is often useful to renormalize short-distance, high-momentum components of an interaction via unitary transformations. Such transformations preserve the on-shell physical observables of the two-body system (mostly…

Nuclear Theory · Physics 2014-11-21 Calvin W. Johnson

In this work we derive a systematic short-range expansion of the many-body wave function. At leading order, the wave function is factorized to a zero-energy $s$-wave correlated pair and spectator particles, while terms that include energy…

Nuclear Theory · Physics 2023-07-13 Ronen Weiss , Diego Lonardoni , Stefano Gandolfi

A three-body potential function can account for interactions among triples of particles which are uncaptured by pairwise interaction functions such as Coulombic or Lennard-Jones potentials. Likewise, a multibody potential of order $n$ can…

Computational Physics · Physics 2015-05-28 Dongryeol Lee , Arkadas Ozakin , Alexander G. Gray

A common situation in quantum many-body physics is that the underlying theories are known but too complicated to solve efficiently. In such cases one usually builds simpler effective theories as low-energy or large-scale alternatives to the…

Quantum Physics · Physics 2023-09-07 Yongdan Yang , Zongkang Zhang , Xiaosi Xu , Bing-Nan Lu , Ying Li

Accurately predicting protein melting temperature changes (Delta Tm) is fundamental for assessing protein stability and guiding protein engineering. Leveraging multi-modal protein representations has shown great promise in capturing the…

Machine Learning · Computer Science 2025-03-25 Daiheng Zhang , Yan Zeng , Xinyu Hong , Jinbo Xu
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