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Related papers: Factorization in large-scale many-body calculation…

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In this chapter we focus first on the theoretical methods and relevant computational approaches to calculate the electronic structure of atoms, molecules, and clusters containing heavy elements for which relativistic effects become…

Chemical Physics · Physics 2021-10-05 Simone Taioli , Stefano Simonucci

We consider energetics and structural properties of a many particle system in one dimension with pairwise contact interactions confined in a parabolic external potential. To render the problem analytically solvable, we use the harmonic…

Quantum Gases · Physics 2012-12-20 J. R. Armstrong , N. T. Zinner , D. V. Fedorov , A. S. Jensen

A self-consistent many-body approach is proposed to build a first-principles crystal field theory, where crystal field parameters are calculated ab initio. Many-body theory is used to write the energy of the interacting system as a function…

Strongly Correlated Electrons · Physics 2010-09-17 Christian Brouder

One of the useful and practical methods for solving quantum-mechanical many-body systems is to recast the full problem into a form of the effective interaction acting within a model space of tractable size. Many of the effective-interaction…

Nuclear Theory · Physics 2015-06-11 Kenji Suzuki , Hiroo Kumagai , Masayuki Matsuzaki , Ryoji Okamoto

We present a scalable framework for accurately modeling many-body interactions in surface-code quantum processor units (QPUs). Combining a concise diagrammatic formalism with high-precision numerical methods, our approach efficiently…

Quantum Physics · Physics 2025-07-09 Xuexin Xu , Kuljeet Kaur , Chloé Vignes , Mohammad H. Ansari , John M. Martinis

The integrability of one dimensional quantum mechanical many-body problems with general contact interactions is extensively studied. It is shown that besides the pure (repulsive or attractive) $\delta$-function interaction there is another…

Quantum Physics · Physics 2009-11-06 Sergio Albeverio , Ludwik Dabrowski , Shao-Ming Fei

The partitioning of a system model will condition the structure of the controller as well as its design. In order to partition a system model, one has to know what states and inputs to group together to define subsystem models. For a given…

Systems and Control · Computer Science 2017-11-22 Romain Guicherd , Paul A. Trodden , Andrew R. Mills , Visakan Kadirkamanathan

Many matrices associated with fast transforms posess a certain low-rank property characterized by the existence of several block partitionings of the matrix, where each block is of low rank. Provided that these partitionings are known,…

Numerical Analysis · Mathematics 2023-07-04 Léon Zheng , Gilles Puy , Elisa Riccietti , Patrick Pérez , Rémi Gribonval

We examine the relation between inter-particle interactions and real-time equilibration in one-dimensional lattice systems with hard-core constraints. Focusing on the roles of interactions, our results demonstrate that in the presence of…

Quantum Gases · Physics 2025-03-04 Wei-Han Li

Group theoretic method for the systematic study of multi-quark states is developed. The calculation of matrix elements of many body Hamiltonian is simplified by transforming the physical bases (quark cluster bases) to symmetry bases (group…

High Energy Physics - Phenomenology · Physics 2007-11-13 Hongxia Huang , Chengrong Deng , Jialun Ping , Fan Wang , T. Goldman

The simulation of open quantum systems coupled to a reservoir through multiple channels remains a substantial challenge. This kind of open quantum system arises when considering the radiationless decay of excited states that are coupled to…

Quantum Physics · Physics 2023-07-14 Hanggai Nuomin , Jiaxi Wu , Peng Zhang , David N. Beratan

Recent successes in Monte Carlo methods for simulating fermionic quantum impurity models have been based on diagrammatic resummation techniques, but are restricted by the need to sum over factorially large classes of diagrams individually.…

Strongly Correlated Electrons · Physics 2018-10-03 Aviel Boag , Emanuel Gull , Guy Cohen

Factorization Machine (FM) is a widely used supervised learning approach by effectively modeling of feature interactions. Despite the successful application of FM and its many deep learning variants, treating every feature interaction…

Machine Learning · Computer Science 2019-02-28 Fuxing Hong , Dongbo Huang , Ge Chen

In the age of big data and interpretable machine learning, approaches need to work at scale and at the same time allow for a clear mathematical understanding of the method's inner workings. While there exist inherently interpretable…

Computation · Statistics 2023-02-02 David Rügamer

Characterization of qubit couplings in many-body quantum systems is essential for benchmarking quantum computation and simulation. We propose a tomographic measurement scheme to determine all the coupling terms in a general many-body…

Quantum Physics · Physics 2015-10-06 Sheng-Tao Wang , Dong-Ling Deng , Lu-Ming Duan

Achieving an accurate description of fermionic systems typically requires considerably many more orbitals than fermions. Previous resource analyses of quantum chemistry simulation often failed to exploit this low fermionic number…

Quantum Physics · Physics 2022-05-24 Sam McArdle , Earl Campbell , Yuan Su

A variational formulation for the calculation of interacting fermion systems based on the density-matrix functional theory is presented. Our formalism provides for a natural integration of explicit many-particle effects into standard…

Strongly Correlated Electrons · Physics 2013-05-29 Peter E. Bloechl , Christian F. J. Walther , Thomas Pruschke

Quantum Monte Carlo (QMC) methods are one of the most important tools for studying interacting quantum many-body systems. The vast majority of QMC calculations in interacting fermion systems require a constraint to control the sign problem.…

Strongly Correlated Electrons · Physics 2016-12-08 Mingpu Qin , Hao Shi , Shiwei Zhang

We present a novel input scheme for general second-quantized Hamiltonians of relativistic or non-relativistic many-fermion systems. This input scheme incorporates the fermionic anticommutation relations, particle number variations, and…

Quantum Physics · Physics 2025-05-16 Weijie Du , James P. Vary

Matrix factorization is a very common machine learning technique in recommender systems. Bayesian Matrix Factorization (BMF) algorithms would be attractive because of their ability to quantify uncertainty in their predictions and avoid…

Machine Learning · Computer Science 2020-04-15 Tom Vander Aa , Xiangju Qin , Paul Blomstedt , Roel Wuyts , Wilfried Verachtert , Samuel Kaski