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Related papers: Zero Modes in a $c = 2$ Matrix Model

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Following earlier work on the same topic, we consider once more scalar field theories on the world sheet parametrized by the light cone coordinates. For most of the way, we use the same approach as in the previous work, but there is an…

High Energy Physics - Theory · Physics 2015-06-15 Korkut Bardakci

Large Language Models (LLMs) face significant challenges in edge deployment due to their massive parameter scale. Vector Quantization (VQ), a clustering-based quantization method, serves as a prevalent solution to this issue for its…

Machine Learning · Computer Science 2025-06-27 Yuxuan Yue , Zukang Xu , Zhihang Yuan , Dawei Yang , Jianlong Wu , Liqiang Nie

We study the problem of quantum quench across a critical point in a strongly coupled field theory using AdS/CFT techniques. The model involves a probe neutral scalar field with mass-squared $m^2$ in the range $-9/4 < m^2 < -3/2$ in a…

High Energy Physics - Theory · Physics 2015-05-30 Pallab Basu , Sumit R. Das

We derive Concentration of Measure (CoM) inequalities for randomized Toeplitz matrices. These inequalities show that the norm of a high-dimensional signal mapped by a Toeplitz matrix to a low-dimensional space concentrates around its mean…

Information Theory · Computer Science 2016-11-17 Borhan M. Sanandaji , Tyrone L. Vincent , Michael B. Wakin

Lorentz-invariant non-commutative QED (NCQED) is constructed such that it should be a part of Lorentz-invariant non-commutative standard model (NCSM), a subject to be treated in later publications. Our NCSM is based on Connes' observation…

High Energy Physics - Theory · Physics 2009-11-07 Katsusada Morita

We use the quantum group approach for the investigation of correlation functions of integrable vertex models and spin chains. For the inhomogeneous reduced density matrix in case of an arbitrary simple Lie algebra we find functional…

Mathematical Physics · Physics 2021-02-26 A. Klümper , Kh. S. Nirov , A. V. Razumov

A Chern-Simons matrix model was proposed by Dorey, Tong, and Turner to describe non-Abelian fractional quantum Hall effect. In this paper we study the Hilbert space of the Chern-Simons matrix model from a geometric quantization point of…

Mathematical Physics · Physics 2024-09-20 Sen Hu , Si Li , Dongheng Ye , Yehao Zhou

We provide a detailed comparison of the different approaches available for the quantization of a totally constrained system with a constraint algebra generating the non-compact $SL(2,\mathbb{R})$ group. In particular, we consider three…

General Relativity and Quantum Cosmology · Physics 2014-07-23 Rodolfo Gambini , Javier Olmedo

This review paper provides an introduction of Markov chains and their convergence rates which is an important and interesting mathematical topic which also has important applications for very widely used Markov chain Monte Carlo (MCMC)…

Probability · Mathematics 2021-09-03 Yu Hang Jiang , Tong Liu , Zhiya Lou , Jeffrey S. Rosenthal , Shanshan Shangguan , Fei Wang , Zixuan Wu

We formulate QCD in (d+1) dimensions using Dirac's front form with periodic boundary conditions, that is, within Discretized Light-Cone Quantization. The formalism is worked out in detail for SU(2) pure glue theory in (2+1) dimensions which…

High Energy Physics - Theory · Physics 2009-10-28 H. C. Pauli , A. C. Kalloniatis , S. S. Pinsky

Motivated by the renormalization group (RG) approach to $c=0$ matrix model of Bre\'zin and Zinn-Justin, we develop a RG scheme for $c=1$ matrix model on a circle and analyze how the two coupling constants in double scaling limit with…

High Energy Physics - Theory · Physics 2007-05-23 Satabhisa Dasgupta , Tathagata Dasgupta

Recently, in the context of Relativistic Quantum Information Theory (RQI) of massive spin-1/2 particles, it has been suggested that it is impossible to perform a momentum-independent spin measurement, showing the inadequacy of the spin…

Mathematical Physics · Physics 2022-01-12 Heon Lee

Matrix models and their connections to String Theory and noncommutative geometry are discussed. Various types of matrix models are reviewed. Most of interest are IKKT and BFSS models. They are introduced as 0+0 and 1+0 dimensional reduction…

High Energy Physics - Theory · Physics 2009-09-29 Corneliu Sochichiu

Existing post-training quantization methods for large language models (LLMs) offer remarkable success. However, the increasingly marginal performance gains suggest that existing quantization strategies are insufficient to support the…

Machine Learning · Computer Science 2025-10-28 Jiaqi Zhao , Miao Zhang , Deng Xiang , Ming Li , Weili Guan , Liqiang Nie

This paper is devoted to an in-depth study of the limiting measure of Lee--Yang zeroes for the Ising Model on the Cayley Tree. We build on previous works of M\"uller-Hartmann-Zittartz (1974 and 1977), Barata--Marchetti (1997), and…

Mathematical Physics · Physics 2019-03-27 Ivan Chio , Caleb He , Anthony L. Ji , Roland K. W. Roeder

A new approach is developed for evaluating the convergence rate for nonlinear Markov chains (MC) based on the recently developed spectral radius technique of markovian coupling for linear MC and the idea of small nonlinear perturbations of…

Probability · Mathematics 2025-03-27 Alexander Shchegolev , Alexander Veretennikov

We study a simple quantum circuit model which, without need for fine tuning, is very close to sitting at the transition between ergodic and many-body localized (MBL) phases. We probe the properties of the model on large finite-size systems,…

Disordered Systems and Neural Networks · Physics 2019-12-23 Nicolas Macé

We carry out a systematic study of the exact block entanglement in XXZ spin-chain at Delta=-1/2. We present, the first analytic expressions for reduced density matrices of n spins in a chain of length L (for n<=6 and arbitrary but odd L) of…

Statistical Mechanics · Physics 2009-11-13 Bernard Nienhuis , Massimo Campostrini , Pasquale Calabrese

The vacuum problem of light-cone quantum field theory is reanalysed from a functional-integral point of view.

High Energy Physics - Theory · Physics 2007-05-23 Thomas Heinzl

Deploying neural networks on the edge has become increasingly important as deep learning is being applied in an increasing amount of applications. At the edge computing hardware typically has limited resources disallowing to run neural…

Machine Learning · Computer Science 2025-09-15 Quinten Van Baelen , Peter Karsmakers