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Related papers: Learning BPS Spectra and the Gap Conjecture

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Probabilistic shaping (PS) is a promising technique to approach the Shannon limit using typical constellation geometries. However, the impact of PS on the chain of signal processing algorithms of a coherent receiver still needs further…

Signal Processing · Electrical Eng. & Systems 2018-09-14 Darli A. A. Mello , Fabio A. Barbosa , Jacklyn D. Reis

We study the infrared behavior of the entire class of Y(p,q) quiver gauge theories. The dimer technology is exploited to discuss the duality cascades and support the general belief about a runaway behavior for the whole family. We argue…

High Energy Physics - Theory · Physics 2009-11-11 Andrea Brini , Davide Forcella

Feature extraction - the ability to identify relevant properties of data - is a key factor underlying the success of deep learning. Yet, it has proved difficult to elucidate its nature within existing predictive theories, to the extent that…

Disordered Systems and Neural Networks · Physics 2025-08-29 Andrea Corti , Rosalba Pacelli , Pietro Rotondo , Marco Gherardi

We deduce several curious q-series expansions by applying inverse relations to certain identities for basic hypergeometric series. After rewriting some of these expansions in terms of q-integrals, we obtain, in the limit q -> 1, some…

Classical Analysis and ODEs · Mathematics 2019-02-22 George Gasper , Michael Schlosser

((1+1)-dimensional ${\cal N}=1$ super-symmetric field theory and (3+1)-dimensional ${\cal N}=2$ super-symmetric gauge theory are discussed in a, more or less, unified way, designed to identify the quantum BPS states in both systems.…

High Energy Physics - Theory · Physics 2016-02-29 Juan Mateos Guilarte

The discrepant posterior phenomenon (DPP) is a counter-intuitive phenomenon that can frequently occur in a Bayesian analysis of multivariate parameters. It refers to the phenomenon that a parameter estimate based on a posterior is more…

Statistics Theory · Mathematics 2022-01-14 Yang Chen , Ruobin Gong , Min-ge Xie

Standard exceptional points (EPs) are non-Hermitian degeneracies that occur in open systems. At an EP, the Taylor series expansion becomes singular and fails to converge -- a feature that was exploited for several applications. Here, we…

Applied Physics · Physics 2021-03-25 M. Sakhdari , M. Hajizadegan , Q. Zhong , D. N. Christodoulides , R. El-Ganainy , P. -Y. Chen

We collect in this note some observations on the role of symmetries in Bayesian inference problems, that can be useful or detrimental depending on the way they act on the signal and on the observations. We emphasize in particular the need…

Disordered Systems and Neural Networks · Physics 2025-02-13 Guilhem Semerjian

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative…

Populations and Evolution · Quantitative Biology 2014-06-18 Steven A. Frank

The partition functions of three-dimensional N=2 supersymmetric gauge theories on different manifolds can be expressed as q-hypergeometric integrals. By comparing the partition functions of three-dimensional mirror dual theories, one finds…

Mathematical Physics · Physics 2019-05-01 Deniz N. Bozkurt , Ilmar Gahramanov

Statistical analysis of a graph often starts with embedding, the process of representing its nodes as points in space. How to choose the embedding dimension is a nuanced decision in practice, but in theory a notion of true dimension is…

Machine Learning · Statistics 2021-01-06 Patrick Rubin-Delanchy

It is possible to understand whether a given BPS spectrum is generated by a relevant deformation of a 4D N=2 SCFT or of an asymptotically free theory from the periodicity properties of the corresponding quantum monodromy. With the aim of…

High Energy Physics - Theory · Physics 2017-03-17 Michele Cirafici , Michele Del Zotto

Bayesian Networks (BNs) are useful tools giving a natural and compact representation of joint probability distributions. In many applications one needs to learn a Bayesian Network (BN) from data. In this context, it is important to…

Machine Learning · Computer Science 2012-07-02 Or Zuk , Shiri Margel , Eytan Domany

We consider the problems of hypothesis testing and model comparison under a flexible Bayesian linear regression model whose formulation is closely connected with the linear mixed effect model and the parametric models for SNP set analysis…

Methodology · Statistics 2015-02-24 Xiaoquan Wen

We systematically study supersymmetric embeddings of D-brane probes of different dimensionality in the AdS_5xY^{p,q} background of type IIB string theory. The main technique employed is the kappa symmetry of the probe's worldvolume theory.…

High Energy Physics - Theory · Physics 2009-11-11 Felipe Canoura , Jose D. Edelstein , Leopoldo A. Pando Zayas , Alfonso V. Ramallo , Diana Vaman

This paper considers the problem of learning the parameters in Bayesian networks of discrete variables with known structure and hidden variables. Previous approaches in these settings typically use expectation maximization; when the network…

Machine Learning · Computer Science 2013-09-27 Yonatan Halpern , David Sontag

We study the discrete flows generated by the symmetry group of the BPS quivers for Calabi-Yau geometries describing five dimensional superconformal quantum field theories on a circle. These flows naturally describe the BPS particle spectrum…

High Energy Physics - Theory · Physics 2021-08-04 Giulio Bonelli , Fabrizio Del Monte , Alessandro Tanzini

We determine the general scalar potential consistent with (p,q) supersymmetry in two-dimensional non-linear sigma models with torsion, generalizing previous results for special cases. We thereby find many new supersymmetric sigma models…

High Energy Physics - Theory · Physics 2010-04-06 G. Papadopoulos , P. K. Townsend

We advocate a set of approximations for studying the finite temperature behavior of strongly-coupled theories in 0+1 dimensions. The approximation consists of expanding about a Gaussian action, with the width of the Gaussian determined by a…

High Energy Physics - Theory · Physics 2008-11-26 Daniel Kabat , Gilad Lifschytz

Supersymmetric gauge theories have played a central role in applications of quantum field theory to mathematics. Topologically twisted supersymmetric gauge theories often admit a rigorous mathematical description: for example, the Donaldson…

Quantum Algebra · Mathematics 2017-11-22 Kevin Costello , Claudia Scheimbauer
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