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Related papers: Real-time scattering in the lattice Schwinger mode…

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Tensor models play an increasingly prominent role in many fields, notably in machine learning. In several applications, such as community detection, topic modeling and Gaussian mixture learning, one must estimate a low-rank signal from a…

Machine Learning · Statistics 2022-06-16 José Henrique de Morais Goulart , Romain Couillet , Pierre Comon

Tensor network methods have become a powerful class of tools to capture strongly correlated matter, but methods to capture the experimentally ubiquitous family of models at finite temperature beyond one spatial dimension are largely…

Quantum Physics · Physics 2019-02-27 A. Kshetrimayum , M. Rizzi , J. Eisert , R. Orus

We discuss the Heider model in the presence of an external social field. This field was introduced to break the symmetry between the probabilities of hostile and friendly relationships. We consider the system in the presence of fluctuations…

Statistical Mechanics · Physics 2025-12-05 Zdzisław Burda , Maciej Wołoszyn , Krzysztof Malarz , Krzysztof Kułakowski

Tensor networks are a powerful tool for many-body ground states with limited entanglement. These methods can nonetheless fail for certain time-dependent processes - such as quantum transport or quenches - where entanglement growth is linear…

Strongly Correlated Electrons · Physics 2020-05-20 Gabriela Wojtowicz , Justin E. Elenewski , Marek M. Rams , Michael Zwolak

In this work we propose a series-expansion thermal tensor network (SETTN) approach for efficient simulations of quantum lattice models. This continuous-time SETTN method is based on the numerically exact Taylor series expansion of…

Strongly Correlated Electrons · Physics 2017-04-12 Bin-Bin Chen , Yun-Jing Liu , Ziyu Chen , Wei Li

The study of confinement in quantum spin chains has seen a large surge of interest in recent years. It is not only important for understanding a range of effective one-dimensional condensed matter realizations, but also shares some of the…

Quantum Gases · Physics 2022-10-21 Joseph Vovrosh , Rick Mukherjee , Alvise Bastianello , Johannes Knolle

The lattice dynamics of coesite has been studied by a combination of diffuse x-ray scattering, inelastic x-ray scattering and an ab initio lattice dynamics calculation. The combined technique gives access to the full lattice dynamics in…

Tensor networks provide a natural language for non-invertible symmetries in general Hamiltonian lattice models. We use ZX-diagrams, which are tensor network presentations of quantum circuits, to define a non-invertible operator implementing…

Quantum Physics · Physics 2025-10-28 Pranay Gorantla , Shu-Heng Shao , Nathanan Tantivasadakarn

We introduce a numerical tensor-network method to compute the statistics of the charge transferred across an interface partitioning an interacting one-dimensional many-body lattice system with $U(1)$ symmetry. Our approach is based on a…

Quantum Physics · Physics 2026-04-01 Hari Kumar Yadalam , Mark T. Mitchison

Manifest gauge-invariance requires that observable states in the standard-model are described by composite operators, which involve additional Higgs contributions beyond perturbation theory. This field-theoretical effect has been confirmed…

High Energy Physics - Phenomenology · Physics 2020-06-17 Axel Maas , Simon Fernbach , Lukas Lechner , Simon Plätzer , Robert Schöfbeck , Pascal Törek

A quadrature-based finite-difference lattice Boltzmann model is developed that is suitable for simulating relativistic flows of massless particles. We briefly review the relativistc Boltzmann equation and present our model. The quadrature…

Fluid Dynamics · Physics 2017-09-26 Robert Blaga , Victor E. Ambrus

We study relativistic scattering when one only has access to a subset of the particles, using the language of quantum measurement theory. We give an exact, non-perturbative formula for the von Neumann entanglement entropy of an apparatus…

High Energy Physics - Theory · Physics 2016-06-13 Daniel Carney , Laurent Chaurette , Gordon Semenoff

Characterizing and controlling entanglement in quantum materials is crucial for the development of next-generation quantum technologies. However, defining a quantifiable figure of merit for entanglement in macroscopic solids is…

Strongly Correlated Electrons · Physics 2023-06-27 Jordyn Hales , Utkarsh Bajpai , Tongtong Liu , Denitsa R. Baykusheva , Mingda Li , Matteo Mitrano , Yao Wang

Integrating machine learning techniques in established numerical solvers represents a modern approach to enhancing computational fluid dynamics simulations. Within the lattice Boltzmann method (LBM), the collision operator serves as an…

Computational Physics · Physics 2024-12-12 Mario Christopher Bedrunka , Tobias Horstmann , Ben Picard , Dirk Reith , Holger Foysi

A four-way coupling scheme for the direct numerical simulation of particle-laden flows is developed and analyzed. It employs a novel adaptive multi-relaxation time lattice Boltzmann method to simulate the fluid phase efficiently. The…

Computational Physics · Physics 2020-03-04 Christoph Rettinger , Ulrich Rüde

We report an accurate and efficient classical simulation of a kicked Ising quantum system on the heavy-hexagon lattice. A simulation of this system was recently performed on a 127 qubit quantum processor using noise mitigation techniques to…

Quantum Physics · Physics 2024-01-29 Joseph Tindall , Matt Fishman , Miles Stoudenmire , Dries Sels

We study the motion of a particle in a 3-dimensional lattice in the presence of a Coulomb potential, but we demonstrate semiclassicaly that the trajectories will always remain in a plane which can be taken as a rectangular lattice. The…

Quantum Physics · Physics 2024-07-01 Diego Sanjinés , Evaristo Mamani , Javier Velasco

Aiming at a better understanding of anomalous and topological effects in gauge theories out-of-equilibrium, we study the real-time dynamics of a prototype model for CP-violation, the massive Schwinger model with a $\theta$-term. We identify…

Quantum Physics · Physics 2019-02-13 T. V. Zache , N. Mueller , J. T. Schneider , F. Jendrzejewski , J. Berges , P. Hauke

Tensor networks were developed in the context of many-body physics as compressed representations of multiparticle quantum states. These representations mitigate the exponential complexity of many-body systems by capturing only the most…

Machine Learning · Computer Science 2026-04-17 Guillermo Valverde , Igor García-Olaizola , Giannicola Scarpa , Alejandro Pozas-Kerstjens

We introduce a numerical approach to calculate the statistics of work done on 1D quantum lattice systems initially prepared in thermal equilibrium states. This approach is based on two tensor-network techniques: Time Evolving Block…

Statistical Mechanics · Physics 2022-01-04 Jiayin Gu , Fan Zhang , H. T. Quan
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