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Homomorphic encryption (HE) is a privacy-preserving technique that enables computation directly over ciphertext. Unfortunately, a key challenge for HE is that implementations can be impractically slow and have limits on computation that can…

Cryptography and Security · Computer Science 2022-03-08 Hsuan Hsiao , Vincent Lee , Brandon Reagen , Armin Alaghi

Spatially embedded networks are important in several disciplines. The prototypical spatial net- work we assume is the Random Geometric Graph of which many properties are known. Here we present new results for the two-point degree…

Statistical Mechanics · Physics 2013-03-21 Alberto Antonioni , Marco Tomassini

We consider numerical solutions for the Allen-Cahn equation with standard double well potential and periodic boundary conditions. Surprisingly it is found that using standard numerical discretizations with high precision computational…

Analysis of PDEs · Mathematics 2021-06-15 Dong Li , Chaoyu Quan , Tao Tang , Wen Yang

In this paper we address three aspects of nonlinear computational homogenization of elastic solids by two-scale finite element methods. First, we present a nonlinear formulation of the finite element heterogeneous multiscale method FE-HMM…

Numerical Analysis · Mathematics 2019-12-24 Bernhard Eidel , Andreas Fischer , Ajinkya Gote

Symmetry is one of the most central concepts in physics, and it is no surprise that it has also been widely adopted as an inductive bias for machine-learning models applied to the physical sciences. This is especially true for models…

Chemical Physics · Physics 2024-12-23 Marcel F. Langer , Sergey N. Pozdnyakov , Michele Ceriotti

Two of the most widely used electronic structure theory methods, namely Hartree-Fock and Kohn-Sham density functional theory, both requires the iterative solution of a set of Schr\"odinger-like equations. The speed of convergence of such…

Chemical Physics · Physics 2024-06-06 S. Hazra , U. Patil , S. Sanvito

When function approximation is used, solving the Bellman optimality equation with stability guarantees has remained a major open problem in reinforcement learning for decades. The fundamental difficulty is that the Bellman operator may…

Machine Learning · Computer Science 2018-06-07 Bo Dai , Albert Shaw , Lihong Li , Lin Xiao , Niao He , Zhen Liu , Jianshu Chen , Le Song

Node2vec is a graph embedding method that learns a vector representation for each node of a weighted graph while seeking to preserve relative proximity and global structure. Numerical experiments suggest Node2vec struggles to recreate the…

Machine Learning · Statistics 2023-09-18 Yasuaki Hiraoka , Yusuke Imoto , Killian Meehan , Théo Lacombe , Toshiaki Yachimura

Given any half-sided modular inclusion of standard subspaces, we show that the entropy function associated with the decreasing one-parameter family of translated standard subspaces is convex for any given (not necessarily smooth) vector in…

Mathematical Physics · Physics 2024-01-11 Fabio Ciolli , Roberto Longo , Alessio Ranallo , Giuseppe Ruzzi

Widely used in hydraulics, the Colebrook equation for flow friction relates implicitly to the input parameters; the Reynolds number, and the relative roughness of inner pipe surface, with the output unknown parameter; the flow friction…

Computational Engineering, Finance, and Science · Computer Science 2018-10-29 Pavel Praks , Dejan Brkic

Hypergraph partitioning is an important problem in machine learning, computer vision and network analytics. A widely used method for hypergraph partitioning relies on minimizing a normalized sum of the costs of partitioning hyperedges…

Machine Learning · Computer Science 2017-11-06 Pan Li , Olgica Milenkovic

In this paper, we study the phenomenon of Hopf or more specifically quantum double symmetry breaking. We devise a criterion for this type of symmetry breaking which is more general than the one existing in the literature, and therefore…

Mesoscale and Nanoscale Physics · Physics 2015-06-25 F. A. Bais , C. J. M. Mathy

Although effective for two dimensional (2D) systems, some approximations may fail in describing the properties of one-dimensional (1D) models, which belong to a different universality class. In this paper, we analyze the adequacy of the…

Strongly Correlated Electrons · Physics 2007-05-23 Adolfo Avella , Ferdinando Mancini , Maria del Mar Sanchez-Lopez

The Sllod equations of motion enable modeling of homogeneous flow at the atomic scale, and are commonly used to predict fluid properties such as viscosity. However, few publicly available codes support such simulations, and those that do…

Soft Condensed Matter · Physics 2026-03-24 Stephen Sanderson , Debra J. Searles

In this paper, a generalized finite element method (GFEM) with optimal local approximation spaces for solving high-frequency heterogeneous Helmholtz problems is systematically studied. The local spaces are built from selected eigenvectors…

Numerical Analysis · Mathematics 2022-09-15 Chupeng Ma , Christian Alber , Robert Scheichl

Present theoretical predictions for the entanglement entropy through topological defects are violated by numerical simulations. In order to resolve this, we introduce a paradigm shift in the preparation of reduced density matrices in the…

High Energy Physics - Theory · Physics 2026-01-07 Christian Northe , Paolo Rossi

We are interested in existence results for second order differential inclusions, involving finite number of unilateral constraints in an abstract framework. These constraints are described by a set-valued operator, more precisely a proximal…

Classical Analysis and ODEs · Mathematics 2010-03-10 Frederic Bernicot , Aline Lefebvre-Lepot

We show that the properties of the lower part of the spectrum of the Helmholtz equation for an heterogeneous system in a finite region in $d$ dimensions, where the solutions to the homogeneous problems are known, can be systematically…

Mathematical Physics · Physics 2015-12-23 Paolo Amore

We analyze the Nystr\"om approximation of a positive definite kernel associated with a probability measure. We first prove an improved error bound for the conventional Nystr\"om approximation with i.i.d. sampling and singular-value…

Numerical Analysis · Mathematics 2023-05-24 Satoshi Hayakawa , Harald Oberhauser , Terry Lyons

A test on the numerical accuracy of the semiclassical approximation as a function of the principal quantum number has been performed for the Pullen--Edmonds model, a two--dimensional, non--integrable, scaling invariant perturbation of the…

High Energy Physics - Theory · Physics 2009-09-25 S. Graffi , V. R. Manfredi , L. Salasnich
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