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We investigate many-body spin squeezing dynamics in an XXZ model with interactions that fall off with distance $r$ as $1/r^\alpha$ in $D=2$ and $3$ spatial dimensions. In stark contrast to the Ising model, we find a broad parameter regime…

Quantum Physics · Physics 2020-12-30 Michael A. Perlin , Chunlei Qu , Ana Maria Rey

We review our recent results \cite{bsult} on the derivation of a B-S equation in QCD in a Wilson loop context. We work in a second order formalism, use the Feynman--Schwinger path integral representation for a quark in external field and…

High Energy Physics - Phenomenology · Physics 2007-05-23 N. Brambilla , G. M. Prosperi

In this paper, we study the convergence properties of the Stochastic Gradient Descent (SGD) method for finding a stationary point of a given objective function $J(\cdot)$. The objective function is not required to be convex. Rather, our…

Machine Learning · Statistics 2024-09-24 Rajeeva L. Karandikar , M. Vidyasagar

This paper focuses on the minimization of a sum of a twice continuously differentiable function $f$ and a nonsmooth convex function. An inexact regularized proximal Newton method is proposed by an approximation to the Hessian of $f$…

Optimization and Control · Mathematics 2023-11-09 Ruyu Liu , Shaohua Pan , Yuqia Wu , Xiaoqi Yang

This paper proposes a new graph proximity measure. This measure is a derivative of network reliability. By analyzing its properties and comparing it against other proximity measures through graph examples, we demonstrate that it is more…

Social and Information Networks · Computer Science 2016-12-23 Haifeng Qian , Hui Wan , Mark N. Wegman , Luis A. Lastras , Ruchir Puri

We conduct non-asymptotic analysis on the mean-field variational inference for approximating posterior distributions in complex Bayesian models that may involve latent variables. We show that the mean-field approximation to the posterior…

Statistics Theory · Mathematics 2019-11-06 Wei Han , Yun Yang

Motivated by the computation of the non-parametric maximum likelihood estimator (NPMLE) and the Bayesian posterior in statistics, this paper explores the problem of convex optimization over the space of all probability distributions. We…

Statistics Theory · Mathematics 2023-11-03 Rentian Yao , Linjun Huang , Yun Yang

Sliced-Wasserstein distance (SW) and its variant, Max Sliced-Wasserstein distance (Max-SW), have been used widely in the recent years due to their fast computation and scalability even when the probability measures lie in a very high…

Machine Learning · Statistics 2020-10-06 Khai Nguyen , Nhat Ho , Tung Pham , Hung Bui

We propose a methodology for intercomparing climate models and evaluating their performance against benchmarks based on the use of the Wasserstein distance (WD). This distance provides a rigorous way to measure quantitatively the difference…

Atmospheric and Oceanic Physics · Physics 2020-11-16 Gabriele Vissio , Valerio Lembo , Valerio Lucarini , Michael Ghil

In a variety of applications it is important to extract information from a probability measure $\mu$ on an infinite dimensional space. Examples include the Bayesian approach to inverse problems and possibly conditioned) continuous time…

Probability · Mathematics 2016-06-02 Frank Pinski , Gideon Simpson , Andrew Stuart , Hendrik Weber

We present a new model-independent method to determine the spatial curvature and to mitigate the circularity problem affecting the use of quasars as distance indicators. The cosmic-chronometer measurements are used to construct the…

Cosmology and Nongalactic Astrophysics · Physics 2020-01-29 Jun-Jie Wei , Fulvio Melia

We propose a stochastic optimization method for minimizing loss functions, expressed as an expected value, that adaptively controls the batch size used in the computation of gradient approximations and the step size used to move along such…

Machine Learning · Computer Science 2020-03-04 Achraf Bahamou , Donald Goldfarb

In practical situations, calculating approximations of concepts is the central step for knowledge reduction of dynamic covering decision information system, which has received growing interests of researchers in recent years. In this paper,…

Information Theory · Computer Science 2015-12-10 Guangming Lang

The perimeter and area generating functions of exactly solvable polygon models satisfy q-functional equations, where q is the area variable. The behaviour in the vicinity of the point where the perimeter generating function diverges can…

Statistical Mechanics · Physics 2008-08-28 C. Richard , A. J. Guttmann

We propose and analyze a Stein variational reduced basis method (SVRB) to solve large-scale PDE-constrained Bayesian inverse problems. To address the computational challenge of drawing numerous samples requiring expensive PDE solves from…

Numerical Analysis · Mathematics 2020-02-26 Peng Chen , Omar Ghattas

A new estimator for three-center two-particle Coulomb integrals is presented. Our estimator is exact for some classes of integrals and is much more efficient than the standard Schwartz counterpart due to the proper account of distance…

Chemical Physics · Physics 2015-09-02 David S. Hollman , Henry F. Schaefer , Edward F. Valeev

A method is proposed to compute robust inner-approximations to the backward reachable set for uncertain nonlinear systems. It also produces a robust control law that drives trajectories starting in these sets to the target set. The method…

Systems and Control · Electrical Eng. & Systems 2020-03-13 He Yin , Peter Seiler , Murat Arcak

In recent years, the usefulness of 3D shape estimation is being realized in microscopic or close-range imaging, as the 3D information can further be used in various applications. Due to limited depth of field at such small distances, the…

Computer Vision and Pattern Recognition · Computer Science 2017-01-02 Arnav Bhavsar

In many cases beam coupling impedances or wake fields are calculated with computer simulator such as CST Studio Suite, GdfidL Electromagnetic Field Simulator and so on. But evaluation with the stretched-wire method is still very useful by…

In this work we consider Bayesian inference problems with intractable likelihood functions. We present a method to compute an approximate of the posterior with a limited number of model simulations. The method features an inverse Gaussian…

Computation · Statistics 2021-02-23 Hongqiao Wang , Ziqiao Ao , Tengchao Yu , Jinglai Li