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Related papers: Supersymmetry in Random Matrix Theory

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A generalized Hubbard-Stratonovitch transformation relating an integral over random unitary N times N matrices to an integral over Efetov's unitary sigma model manifold, is introduced. This transformation adapts the supersymmetry method to…

chao-dyn · Physics 2009-10-28 Martin R. Zirnbauer

We generalize the supersymmetry method in Random Matrix Theory to arbitrary rotation invariant ensembles. Our exact approach further extends a previous contribution in which we constructed a supersymmetric representation for the class of…

Mathematical Physics · Physics 2009-11-11 Thomas Guhr

Recently, two different approaches were put forward to extend the supersymmetry method in random matrix theory from Gaussian ensembles to general rotation invariant ensembles. These approaches are the generalized Hubbard-Stratonovich…

Mathematical Physics · Physics 2009-06-17 Mario Kieburg , Hans-Jürgen Sommers , Thomas Guhr

It is described how one comes to the Wigner-Dyson random matrix theory (RMT) starting from a model of a disordered metal. The lectures start with a historical introduction where basic ideas of the RMT and theory of disordered metals are…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 K. B. Efetov

Recently, the supersymmetry method was extended from Gaussian ensembles to arbitrary unitarily invariant matrix ensembles by generalizing the Hubbard-Stratonovich transformation. Here, we complete this extension by including arbitrary…

Mathematical Physics · Physics 2009-06-17 Mario Kieburg , Johan Grönqvist , Thomas Guhr

Random matrix theory (RMT) provides a successful model for quantum systems, whose classical counterpart has a chaotic dynamics. It is based on two assumptions: (1) matrix-element independence, and (2) base invariance. Last decade witnessed…

Chaotic Dynamics · Physics 2011-09-27 A. Y. Abul-Magd

The leading correction to the smoothed connected energy density-density correlation function is obtained for the large energy difference, within the context of the Gaussian Random Matrix Theory. In order to achieve this result, the…

Condensed Matter · Physics 2015-06-25 Vladan Lucic

In this talk we go over several new developments regarding the techniques for a large class of non-hermitian matrix models with unitary randomness (complex random numbers). In particular, we discuss: (a) - A diagrammatic approach based on a…

High Energy Physics - Phenomenology · Physics 2008-02-03 Romuald A. Janik , Maciej A. Nowak , Gabor Papp , Ismail Zahed

We investigate simple examples of supersymmetry algebras with real and Grassmann parameters. Special attention is payed to the finite supertransformations and their probability interpretation. Furthermore we look for combinations of bosons…

Quantum Physics · Physics 2023-05-09 Nevena Ilieva , Heide Narnhofer , Walter Thirring

In this work we present an introduction to Supersymmetry in the context of 1-dimensional Quantum Mechanics. For that purpose we develop the concept of hamiltonians factorization using the simple harmonic oscillator as an example, we…

Mathematical Physics · Physics 2011-11-07 Fabricio Marques

The Drinfeld-Sokolov construction of integrable hierarchies, as well as its generalizations, may be extended to the case of loop superalgebras. A sufficient condition on the algebraic data for the resulting hierarchy to be invariant under…

solv-int · Physics 2009-10-31 F. delduc , L. Gallot

Starting from Gaussian random matrix models we derive a new supermatrix field theory model. In contrast to the conventional non-linear sigma models, the new model is applicable for any range of correlations of the elements of the random…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 J. E. Bunder , K. B. Efetov , V. E. Kravtsov , O. M. Yevtushenko , M. R. Zirnbauer

I provide a pedagogical introduction to supersymmetry. The level of discussion is aimed at readers who are familiar with the Standard Model and quantum field theory, but who have had little or no prior exposure to supersymmetry. Topics…

High Energy Physics - Phenomenology · Physics 2016-11-03 Stephen P. Martin

We give a constructive proof for the superbosonization formula for invariant random matrix ensembles, which is the supersymmetry analog of the theory of Wishart matrices. Formulas are given for unitary, orthogonal and symplectic symmetry,…

Statistical Mechanics · Physics 2007-11-15 Hans-Jürgen Sommers

Random matrix models based on an integral over supermatrices are proposed as a natural extension of bosonic matrix models. The subtle nature of superspace integration allows these models to have very different properties from the analogous…

High Energy Physics - Theory · Physics 2015-06-26 Scott A. Yost

We solve a supersymmetric matrix model with a general potential. While matrix models usually describe surfaces, supersymmetry enforces a cancellation of bosonic and fermionic loops and only diagrams corresponding to so-called branched…

Condensed Matter · Physics 2009-10-28 J. Ambjorn , Y. Makeenko , K. Zarembo

Superbosonization is a new variant of the method of commuting and anti-commuting variables as used in studying random matrix models of disordered and chaotic quantum systems. We here give a concise mathematical exposition of the key…

Mathematical Physics · Physics 2008-08-23 P. Littelmann , H. -J. Sommers , M. R. Zirnbauer

The concept of supersymmetry in a quantum mechanical system is extended, permitting the recognition of many more supersymmetric systems, including very familiar ones such as the free particle. Its spectrum is shown to be supersymmetric,…

Quantum Physics · Physics 2009-11-10 A. R. P. Rau

We review the development of random-matrix theory (RMT) during the last decade. We emphasize both the theoretical aspects, and the application of the theory to a number of fields. These comprise chaotic and disordered systems, the…

Condensed Matter · Physics 2016-08-31 Thomas Guhr , Axel Mueller-Groeling , Hans A. Weidenmueller

Modern deep learning models are highly overparameterized, resulting in large sets of parameter configurations that yield the same outputs. A significant portion of this redundancy is explained by symmetries in the parameter…

Machine Learning · Computer Science 2025-12-12 Bo Zhao , Robin Walters , Rose Yu
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