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The conformal anomaly and the Virasoro algebra are fundamental aspects of 2D conformal field theory and conformally covariant models in planar random geometry. In this article, we explicitly derive the Virasoro algebra from an…

Mathematical Physics · Physics 2025-05-06 Sid Maibach , Eveliina Peltola

In this paper, we extend the recent analysis of the new large $D$ limit of matrix models to the cases where the action contains arbitrary multi-trace interaction terms as well as to arbitrary correlation functions. We discuss both the cases…

High Energy Physics - Theory · Physics 2018-05-23 Tatsuo Azeyanagi , Frank Ferrari , Paolo Gregori , Laetitia Leduc , Guillaume Valette

Similarly to the complex matrix model, the rainbow tensor models are superintegrable in the sense that arbitrary Gaussian correlators are explicitly expressed through the Clebsh-Gordan coefficients. We introduce associated (Ooguri-Vafa…

High Energy Physics - Theory · Physics 2020-01-27 H. Itoyama , A. Mironov , A. Morozov

We study the estimation error of constrained M-estimators, and derive explicit upper bounds on the expected estimation error determined by the Gaussian width of the constraint set. Both of the cases where the true parameter is on the…

Statistics Theory · Mathematics 2015-06-29 Yen-Huan Li , Ya-Ping Hsieh , Nissim Zerbib , Volkan Cevher

The paper presents the bosonic and fermionic supersymmetric extensions of the structural equations describing conformally parametrized surfaces immersed in a Grasmann superspace, based on the authors' earlier results. A detailed analysis of…

Mathematical Physics · Physics 2015-06-18 Sébastien Bertrand , Alfred M. Grundland , Alexander J. Hariton

We prove that the Kupershmidt deformation of a bi-Hamiltonian system is itself bi-Hamiltonian. Moreover, Magri hierarchies of the initial system give rise to Magri hierarchies of Kupershmidt deformations as well. Since Kupershmidt…

Exactly Solvable and Integrable Systems · Physics 2010-01-04 Paul Kersten , Iosif Krasil'shchik , Alexander Verbovetsky , Raffaele Vitolo

We derive high-dimensional Gaussian comparison results for the standard $V$-fold cross-validated risk estimates. Our results combine a recent stability-based argument for the low-dimensional central limit theorem of cross-validation with…

Statistics Theory · Mathematics 2023-11-15 Nicholas Kissel , Jing Lei

It is common in functional data analysis to look at a set of related functions: a set of learning curves, a set of brain signals, a set of spatial maps, etc. One way to express relatedness is through an additive model, whereby each…

Computation · Statistics 2014-02-21 Simon Barthelme

We study generalized Hermite polynomials with rectangular matrix arguments arising in multivariate statistical analysis and the theory of zonal polynomials. We show that these are well-suited for expressing the Wiener-Ito chaos expansion of…

Probability · Mathematics 2021-09-29 Massimo Notarnicola

Non-Hermitian generalized eigenvalue problems (GEPs) play a significant role in many practical applications, such as mechanical engineering. Based on the generalized Schur decomposition, we propose a variational quantum algorithm for…

We obtain the explicit rate of convergence $N^{-1/2 + \epsilon}$ for the gaps of generalized Wigner matrices in the bulk of the spectrum, for distributions of matrix entries possibly atomic and supported on enough points. The proof proceeds…

Probability · Mathematics 2025-09-24 Albert Zhang

We first study the quantum product on the big phase space defined by gravitational Gromov-Witten invariants. We then use this product to give an interpretation for various topological recursion relations and also use it to study the…

Algebraic Geometry · Mathematics 2007-05-23 Xiaobo Liu

We consider the problem of finding a dense submatrix of a matrix with i.i.d. Gaussian entries, where density is measured by average value. This problem arose from practical applications in biology and social sciences…

Probability · Mathematics 2025-07-28 Shankar Bhamidi , David Gamarnik , Shuyang Gong

We numerically analyze the spectral statistics of the multiparametric Gaussian ensembles of complex matrices with zero mean and variances with different decay routes away from the diagonals. As the latter mimics different degree of…

Disordered Systems and Neural Networks · Physics 2024-03-05 Mohd. Gayas Ansari , Pragya Shukla

We consider the classification problem of a high-dimensional mixture of two Gaussians with general covariance matrices. Using the replica method from statistical physics, we investigate the asymptotic behavior of a general class of…

Machine Learning · Statistics 2024-10-29 Hanwen Huang , Peng Zeng

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 study a matrix that arises from a singular form of the Woodbury matrix identity. We present generalized inverse and pseudo-determinant identities for this matrix, which have direct applications for Gaussian process regression,…

Statistics Theory · Mathematics 2023-04-26 Siavash Ameli , Shawn C. Shadden

We study the conditions under which a generic supergravity model involving chiral and vector multiplets can admit vacua with spontaneously broken supersymmetry and realistic cosmological constant. We find that the existence of such viable…

High Energy Physics - Theory · Physics 2008-11-26 Marta Gomez-Reino , Claudio A. Scrucca

A hermitian matrix can be parametrized by a set consisting of its determinant and the eigenvalues of its submatrices. We established a group of equations which connect these variables with the mixing parameters of diagonalization. These…

High Energy Physics - Phenomenology · Physics 2024-10-03 S. H. Chiu , T. K. Kuo

Gaussian processes (GPs) are commonly used as models for functions, time series, and spatial fields, but they are computationally infeasible for large datasets. Focusing on the typical setting of modeling data as a GP plus an additive noise…

Methodology · Statistics 2020-12-22 Matthias Katzfuss , Joseph Guinness