Related papers: Parameter Optimization of Domain-Wall Fermion usin…

We study lattice QCD with two flavors of dynamical domain wall quarks. With renormalization group motivated actions, we find chiral symmetry can be preserved to a high degree at lattice cut off of a^{-1} \sim 2 GeV even for fifth dimension…

We estimate the spatial distribution of heterogeneous physical parameters involved in the formation of magnetic domain patterns of polycrystalline thin films by using convolutional neural networks. We propose a method to obtain a spatial…

In order to enhance our understanding of spectral functions in lattice QCD obtained with the help of the Maximum Entropy Method, we study meson spectral functions for lattice fermions with chiral symmetry. In particular we analyse lattice…

Machine Learning (ML) models are extensively used in various applications due to their significant advantages over traditional learning methods. However, the developed ML models often underperform when deployed in the real world due to the…

We investigate the properties of domain wall fermions on a set of quenched configurations at non-zero temperature. In particular, we compute the low lying eigenvalues of the DWF operator and study their relation with topology, level…

A magnetic field applied to a cross linked ladder compound can generate isolated electronic states bound to the ends of the chain. After exploring the interference phenomena responsible, I discuss a connection to the domain wall approach to…

We present our recent studies of the pseudo-critical temperature, $T_c$, of QCD using domain wall fermions. Domain wall fermions have the advantage that they preserve exact SU(2) chiral symmetry at finite lattice spacing in the limit that…

We study some properties of a dimensional reduction mechanism for fermions in an odd number D+1 of spacetime dimensions. A fermionic field is equipped with a mass term with domain wall like defects along one of the spacelike dimensions,…

We construct a new holographic description of QCD using domain wall fermions. The construction consists of probe D7 branes in a D5 brane geometry describing quarks on a 4+1d defect in a 5+1d gauge theory. We then compactify one dimension of…

Principles of machine learning are applied to models that support skyrmion phases in two dimensions. Successful feature predictions on various phases of the skyrmion model were possible with several layers of convolutional neural network…

We carry out a comparative study among five-dimensional formulations of chirally symmetric fermions about the algorithmic performance, chiral symmetry violation and topological tunneling to find a computationally inexpensive formulation…

Lattice simulations of Quantum Chromodynamics (QCD) enable one to calculate the low-energy properties of the strong interaction among quarks and gluons based on the first principle. The most time-consuming part of the numerical simulations…

The reasons for the feasibility of the Microcanonical Fermionic Average ($MFA$) approach to lattice gauge theory with dynamical fermions are discussed. We then present a new exact algorithm, which is free from systematic errors and…

An example of a supersymmetric model involving two interacting chiral superfields is presented here which allows for solutions describing string-like ``domain ribbon'' defects embedded within a domain wall. It is energetically favorable for…

The strange quark mass has been computed using a lattice action which possesses continuum--like chiral symmetry to good precision, namely the domain wall fermion action. This talk surveys this action and the recent calculation of m_s by the…

Chiral properties of QCD formulated with the domain-wall fermion (DWQCD) are studied using the anomalous quark mass m_{5q} and the spectrum of the 4-dimensional Wilson-Dirac operator. Numerical simulations are made with the standard…

We consider recent progress in algorithms for generating gauge field configurations that include the dynamical effects of light fermions. We survey what has been achieved in recent state-of-the-art computations, and examine the trade-offs…

Deep learning-based methods deliver state-of-the-art performance for solving inverse problems that arise in computational imaging. These methods can be broadly divided into two groups: (1) learn a network to map measurements to the signal…

We introduce a learning method for recovering action parameters in lattice field theories. Our method is based on the minimization of a convex loss function constructed using the Schwinger-Dyson relations. We show that score matching, a…

We report on simulations of quenched QCD using domain wall fermions, where we focus on basic questions about the formalism and its ability to produce expected low energy hadronic physics for light quarks. The work reported here is on…