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In this work we study the inverse quantum scattering via deep learning regression, which is implemented via a Multilayer Perceptron. A step-by-step method is provided in order to obtain the potential parameters. A circular boundary-wall…

Computational Physics · Physics 2023-07-20 A. C. Maioli

The effective residual interaction for a system of hadrons has a long tradition in theoretical physics. It has been mostly addressed in terms of boson exchange models. The aim of this review is to describe approaches based on lattice field…

High Energy Physics - Lattice · Physics 2007-05-23 H. Rudolf Fiebig , Harald Markum

A systematic way to constructing optimized interpolating operators for two-hadron systems is developed by incorporating inter-hadron spatial wavefunctions. The wavefunctions can be obtained from an iterative process with an appropriate…

High Energy Physics - Lattice · Physics 2025-07-15 Yan Lyu , Sinya Aoki , Takumi Doi , Tetsuo Hatsuda , Kotaro Murakami , Takuya Sugiura

We present a model for the structure of baryons in which the valence partons interact through a linear potential. This model can be derived from QCD in the approximation where the transverse momenta are ignored. We compare the parton…

High Energy Physics - Phenomenology · Physics 2014-11-17 G. S. Krishnaswami , S. G. Rajeev

Robust control design for quantum systems is a challenging and key task for practical technology. In this work, we apply neural networks to learn the control problem for the semiclassical Schr\"odinger equation, where the control variable…

Numerical Analysis · Mathematics 2023-05-31 Yating Wang , Liu Liu

We review recent lattice QCD activities with emphasis on the impact on nuclear physics. In particular, the progress toward the determination of nuclear and baryonic forces (potentials) using Nambu-Bethe-Salpeter (NBS) wave functions is…

High Energy Physics - Lattice · Physics 2012-12-10 Takumi Doi , for HAL QCD Collaboration

The lattice technique of studying the strong interaction of matter is used to obtain predictions of the hadronic spectrum. These simulations were performed by the UKQCD collaboration using full (unquenched) QCD. Details of the results, a…

High Energy Physics - Lattice · Physics 2009-10-31 C. R. Allton

Deep neural networks provide flexible frameworks for learning data representations and functions relating data to other properties and are often claimed to achieve 'super-human' performance in inferring relationships between input data and…

Materials Science · Physics 2021-05-26 Keith T. Butler , Manh Duc Le , Jeyarajan Thiyagalingam , Toby G. Perring

Lattice Gauge Theory enables an ab initio study of the low-energy properties of Quantum Chromodynamics, the theory of the strong interaction. I begin these lectures by presenting the lattice formulation of QCD, and then outline the…

Nuclear Theory · Physics 2017-08-23 D. G. Richards

We present an overview of recent efforts to calculate the interactions among hadrons using lattice QCD. After outlining the techniques that are used to extract scattering parameters, we detail the latest calculations of meson-meson…

High Energy Physics - Lattice · Physics 2008-12-18 Silas R. Beane , Kostas Orginos , Martin J. Savage

We propose a general framework to extract microscopic interactions from raw configurations with deep neural networks. The approach replaces the modeling Hamiltonian by the neural networks, in which the interaction is encoded. It can be…

Computational Physics · Physics 2020-08-19 Lingxiao Wang , Yin Jiang , Kai Zhou

A method to extract nucleon-nucleon (NN) potentials from the Bethe-Salpeter amplitude in lattice QCD is presented. It is applied to the two nucleons on the lattice with quenched QCD simulations. By disentangling the mixing between the…

High Energy Physics - Lattice · Physics 2014-11-20 T. Hatsuda

The interaction between $\Lambda_c$ and a nucleon ($N$) is investigated by employing the HAL QCD method in the (2+1)-flavor lattice QCD on a $(2.9~\mathrm{fm})^3$ volume at $m_\pi \simeq 410,~570,~700$ MeV. We study the central potential in…

In this work we outline a program for lattice QCD that would provide a first step toward understanding the strong and weak interactions of strange baryons. The study of hypernuclear physics has provided a significant amount of information…

Nuclear Theory · Physics 2014-11-18 S. R. Beane , P. F. Bedaque , A. Parreno , M. J. Savage

Numerical lattice quantum chromodynamics studies of the strong interaction are important in many aspects of particle and nuclear physics. Such studies require significant computing resources to undertake. A number of proposed methods…

High Energy Physics - Lattice · Physics 2021-04-08 Phiala E. Shanahan , Amalie Trewartha , William Detmold

This chapter provides a pedagogical introduction to theoretical studies of hadrons based on the fundamental theory of strong interactions - Quantum ChromoDynamics. A perturbative expansion in the strong coupling is not applicable at…

High Energy Physics - Lattice · Physics 2025-05-16 Sasa Prelovsek

We present full accounts of a method to extract nucleon-nucleon (NN) potentials from the Bethe-Salpter amplitude in lattice QCD. The method is applied to two nucleons on the lattice with quenched QCD simulations. By disentangling the mixing…

High Energy Physics - Lattice · Physics 2010-04-30 Sinya Aoki , Tetsuo Hatsuda , Noriyoshi Ishii

The Hubbard model provides a test bed to investigate the complex behaviour arising from electron-electron interaction in strongly-correlated systems and naturally emerges as the foundation model for lattice density functional theory (DFT).…

Strongly Correlated Electrons · Physics 2025-01-29 Eoghan Cronin , Rajarshi Tiwari , Stefano Sanvito

Historically, lattice studies of QCD have concentrated on understanding the properties and structure of an isolated hadron. Recently, there have efforts at understanding the interactions between hadrons. In this talk I will review two…

Nuclear Theory · Physics 2017-08-23 D. G. Richards

As a key property of hadrons, the total width is quite difficult to obtain in theory due to the extreme complexity of the strong and electroweak interactions. In this work, a deep neural network model with the Transformer architecture is…

High Energy Physics - Phenomenology · Physics 2026-02-06 Xin Tong , Wei Feng , Weiwei Xu , Chao-Hsi Chang , Guo-Li Wang , Qiang Li