Related papers: Building Hadron Potentials from Lattice QCD with D…

We present a new approach for predictive modeling and its uncertainty quantification for mechanical systems, where coarse-grained models such as constitutive relations are derived directly from observation data. We explore the use of a…

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron-proton collisions. In particular, we use simulated data from the ZEUS experiment at the…

The approximated partial wave decomposition method to the discrete data on a cubic lattice, developed by C. W. Misner, is applied to the calculation of $S$-wave hadron-hadron scatterings by the HAL QCD method in lattice QCD. We consider the…

Hadronization is a non-perturbative process, which theoretical description can not be deduced from first principles. Modeling hadron formation requires several assumptions and various phenomenological approaches. Utilizing state-of-the-art…

We present a new supervised deep-learning approach to the problem of the extraction of smeared spectral densities from Euclidean lattice correlators. A distinctive feature of our method is a model-independent training strategy that we…

Comprehensive study of generalized baryon-baryon ($BB$) interaction including strangeness is one of the important subject of nuclear physics. In order to obtain a complete set of isospin-base baryon interactions, we perform a large scale…

Deep learning methods have been shown to be effective in representing ground-state wave functions of quantum many-body systems. Existing methods use convolutional neural networks (CNNs) for square lattices due to their image-like…

We review our strategy to study hadron interactions from lattice QCD using newly proposed potential method. We first explain our strategy in the case of nuclear potentials and its application to nuclear physics. We then discuss the origin…

Recently a new approach to calculate the nuclear potential from lattice QCD has been proposed. In the approach the nuclear potential is constructed from Bethe-Salpeter (BS) wave functons through the Schroedinger equation. The procedure…

The aim of these lectures is to give a self-contained introduction to nonrelativistic potential models, to their formulation as well as to their possible applications. At the price of some lack of (in a mathematical sense) rigorous…

Using deep neural networks for identifying physics objects at the Large Hadron Collider (LHC) has become a powerful alternative approach in recent years. After successful training of deep neural networks, examining the trained networks not…

We present our latest study of Lambda-Nucleon (LN) interaction by using lattice QCD, following up on our report at LATTICE 2008. We have calculated not only the scattering lengths but also the central and tensor potentials, which are…

Correlation functions of hadrons can be accessed in high-energy collisions of atomic nuclei, revealing information about the underlying interaction. This work complements experimental efforts to study nucleon-deuteron $Nd$ -- with $N=p$…

We study $S$-wave interactions in the $I\left(J^{p}\right)=1/2\left(1/2^{-}\right)$ $\Lambda_{c}K^{+}-pD_{s}$ system on the basis of the coupled-channel HAL QCD method. The potentials which are faithful to QCD S-matrix below the $ pD^{*} $…

I give an overview of efforts in the last year to calculate interactions among hadrons using lattice QCD. Results discussed include the extraction of low-energy phase shifts and three-body interactions, and the study of pion and kaon…

We describe an efficient algorithm to compute a large number of baryon-baryon interactions from $NN$ to $\Xi\Xi$ by means of HAL QCD method, which lays the groundwork for the nearly physical point lattice QCD calculation with volume…

Molecular dynamics (MD) simulation, which is considered an important tool for studying physical and chemical processes at the atomic scale, requires accurate calculations of energies and forces. Although reliable energies and forces can be…

We study the KN interactions in the I(J^{\pi})=0(1/2^-) and 1(1/2^-) channels and associated exotic state \Theta^+ from 2+1 flavor full lattice QCD simulation for relatively heavy quark mass corresponding to m_{\pi}=871 MeV. The s-wave KN…

In this chapter, the current status on baryon-baryon interactions such as nuclear forces in lattice Quantum ChromoDynamics (QCD) is reviewed. In studies of baryon-baryon interactions in lattice QCD, the most reliable method so far is the…

A novel technique for deep learning of image classifiers is presented. The learned CNN models offer better separation of deep features (also known as embedded vectors) measured by Euclidean proximity and also no deterioration of the…