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Related papers: The Stress Tensor in Quenched Random Systems

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Tensors play a central role in many modern machine learning and signal processing applications. In such applications, the target tensor is usually of low rank, i.e., can be expressed as a sum of a small number of rank one tensors. This…

Machine Learning · Statistics 2015-05-18 Parikshit Shah , Nikhil Rao , Gongguo Tang

Relying on random matrix theory (RMT), this paper studies asymmetric order-$d$ spiked tensor models with Gaussian noise. Using the variational definition of the singular vectors and values of (Lim, 2005), we show that the analysis of the…

Probability · Mathematics 2022-11-22 Mohamed El Amine Seddik , Maxime Guillaud , Romain Couillet

Modeling joint probability distributions over sequences has been studied from many perspectives. The physics community developed matrix product states, a tensor-train decomposition for probabilistic modeling, motivated by the need to…

Machine Learning · Computer Science 2020-10-22 Siddarth Srinivasan , Sandesh Adhikary , Jacob Miller , Guillaume Rabusseau , Byron Boots

The notions of stress and hyperstress are anchored in 3-dimensional continuum mechanics. Within the framework of the 4-dimensional spacetime continuum, stress and hyperstress translate into the energy-momentum and the hypermomentum current,…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Frank Gronwald , Friedrich W. Hehl

We investigate quantum information processing and manipulations in disordered systems of ultracold atoms and trapped ions. First, we demonstrate generation of entanglement and local realization of quantum gates in a quantum spin glass…

In this article, we define the matricization of a tensor and we present some properties of the matricization. After that, we define the determinant of a tensor and we present some properties of the determinant. We define the covariance…

Probability · Mathematics 2021-08-19 Yurii Yurchenko

It is shown that random quantum spin systems with centered disorder satisfy correlation inequalities previously proved (arXiv:cond-mat/0612371) in the classical case. Consequences include monotone approach of pressure and ground state…

Statistical Mechanics · Physics 2015-05-13 Pierluigi Contucci , Joel L. Lebowitz

We calculate correlation functions of the R-current or the stress-energy tensor T_{\mu\nu} with two non-protected operators dual to generic massive string states with rotation in S^5, in the context of the AdS/CFT correspondence. Field…

High Energy Physics - Theory · Physics 2015-06-12 George Georgiou , Bum-Hoon Lee , Chanyong Park

The correlations of the fluctuating stress tensor are calculated in an equilibrium molecular-dynamics simulation of a Lennard--Jones liquid. We define a coarse-grained local stress tensor which can be calculated numerically and which allows…

Soft Condensed Matter · Physics 2012-01-19 Michael Schindler

Derivation of the procedures that can be applied in evaluating two-time correlation function in terms of coherent-state propagator and corresponding Q-function is presented. On the basis that the involved functions are generally exponential…

Quantum Physics · Physics 2009-10-16 Sintayehu Tesfa

We numerically and analytically analyze the startup continuous shear rheology of heavily entangled rigid rod polymer fluids based on our self-consistent, force-level theory of anharmonic tube confinement. The approach is simplified by…

Soft Condensed Matter · Physics 2016-04-15 Kenenth S. Schweizer , Daniel M. Sussman

Tensor decomposition on big data has attracted significant attention recently. Among the most popular methods is a class of algorithms that leverages compression in order to reduce the size of the tensor and potentially parallelize…

Machine Learning · Computer Science 2018-11-20 Georgios Tsitsikas , Evangelos E. Papalexakis

This paper establishes sharp concentration inequalities for simple random tensors. Our theory unveils a phenomenon that arises only for asymmetric tensors of order $p \ge 3:$ when the effective ranks of the covariances of the component…

Probability · Mathematics 2026-03-23 Jiaheng Chen , Daniel Sanz-Alonso

The complexity of quantum many-body systems is manifested in the vast diversity of their correlations, making it challenging to distinguish the generic from the atypical features. This can be addressed by analyzing correlations through…

Quantum Physics · Physics 2023-09-04 Daniel Haag , Flavio Baccari , Georgios Styliaris

Using particle-based numerical simulations performed under pressure-imposed conditions, we investigate the transient dilation dynamics of a shear thickening suspension brought to shear jamming. We show that the stress levels, instead of…

Soft Condensed Matter · Physics 2024-08-28 Shivakumar Athani , Bloen Metzger , Yoël Forterre , Romain Mari

This thesis poses a selection of recent research of the author in a common context. It starts with a selected review on research concerning the role entanglement might play at quantum phase transitions and introduces measures for…

Quantum Physics · Physics 2012-02-08 A. Osterloh

A correspondence between fluctuations of conformally invariant quantum fields and that of classical fields finally reducing to perfect fluid matter content is shown to exist. Previously a similar correspondence between the stress tensors…

General Relativity and Quantum Cosmology · Physics 2019-08-21 Seema Satin

One of the challenging problems in the condensed matter physics is to understand the quantum many-body systems, especially, their physical mechanisms behind. Since there are only a few complete analytical solutions of these systems, several…

Statistical Mechanics · Physics 2020-03-27 Jozef Genzor , Tomotoshi Nishino , Andrej Gendiar

Tensor networks are used to efficiently approximate states of strongly-correlated quantum many-body systems. More generally, tensor network approximations may allow to reduce the costs for operating on an order-$N$ tensor from exponential…

Strongly Correlated Electrons · Physics 2022-05-31 Hao Chen , Thomas Barthel

In this paper, we study the power iteration algorithm for the spiked tensor model, as introduced in [44]. We give necessary and sufficient conditions for the convergence of the power iteration algorithm. When the power iteration algorithm…

Statistics Theory · Mathematics 2020-12-29 Jiaoyang Huang , Daniel Z. Huang , Qing Yang , Guang Cheng
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