Improving flavor symmetry in the Kogut-Susskind hadron spectrum

Journal ArticleWe study the effect of modifying the coupling of Kogut-Susskind quarks to the gauge field by replacing the link matrix in the quark action by a ‘‘fat link,'' or sum of link plus three-link paths. Flavor symmetry breaking, determined by the mass difference between the Goldstone and non-Goldstone local pions, is reduced by approximately a factor of 2 by this modification

A note on the depth-from-defocus mechanism of jumping spiders

Jumping spiders are capable of estimating the distance to their prey relying only on the information from one of their main eyes. Recently, it has been shown that jumping spiders perform this estimation based on image defocus cues. In order to gain insight into the mechanisms involved in this blur-to-distance mapping as performed by the spider and to judge whether inspirations can be drawn from spider vision for depth-from-defocus computer vision algorithms, we constructed a three-dimensional (3D) model of the anterior median eye of the Metaphidippus aeneolus, a well studied species of jumping spider. We were able to study images of the environment as the spider would see them and to measure the performances of a well known depth-from-defocus algorithm on this dataset. We found that the algorithm performs best when using images that are averaged over the considerable thickness of the spider's receptor layers, thus pointing towards a possible functional role of the receptor thickness for the spider's depth estimation capabilities

Domain wall fermion calculation of nucleon g_A/g_V

We present a preliminary domain-wall fermion lattice-QCD calculation of isovector vector and axial charges, g_V and g_A, of the nucleon. Since the lattice renormalizations, Z_V and Z_A, of the currents are identical with DWF, the lattice ratio (g_A/g_V)^{lattice} directly yields the continuum value. Indeed Z_V determined from the matrix element of the vector current agrees closely with Z_A from a non-perturbative renormalization study of quark bilinears. We also obtain spin related quantities Delta-q/g_V and delta-q/g_V.Comment: Lattice 2000 (Hadronic Matrix Elements), 4 pages, 5 figure

A Primal-Dual Algorithm for Hybrid Federated Learning

Very few methods for hybrid federated learning, where clients only hold subsets of both features and samples, exist. Yet, this scenario is very important in practical settings. We provide a fast, robust algorithm for hybrid federated learning that hinges on Fenchel Duality. We prove the convergence of the algorithm to the same solution as if the model was trained centrally in a variety of practical regimes. Furthermore, we provide experimental results that demonstrate the performance improvements of the algorithm over a commonly used method in federated learning, FedAvg. We also provide privacy considerations and necessary steps to protect client data