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We define the notion of a Lie superalgebra over a field $k$ of characteristic $2$ which unifies the two pre-existing ones - $\mathbb{Z}/2$-graded Lie algebras with a squaring map and Lie algebras in the Verlinde category ${\rm Ver}_4^+(k)$,…

Representation Theory · Mathematics 2025-07-24 Pavel Etingof , Serina Hu

In a recent paper DeWolfe et al. have shown how to use the self-intersection number of junctions to constrain the BPS spectrum of N=2, D=4 theories with ADE flavor symmetry arising on a single D3-brane probe in a 7-brane background.…

High Energy Physics - Theory · Physics 2009-10-31 Amer Iqbal

We introduce an approach for solving PDEs over manifolds using physics informed neural networks whose architecture aligns with spectral methods. The networks are trained to take in as input samples of an initial condition, a time stamp and…

Machine Learning · Computer Science 2023-09-06 Yuval Zelig , Shai Dekel

This paper proposes an equivariant neural network that takes data in any semi-simple Lie algebra as input. The corresponding group acts on the Lie algebra as adjoint operations, making our proposed network adjoint-equivariant. Our framework…

Machine Learning · Computer Science 2024-06-10 Tzu-Yuan Lin , Minghan Zhu , Maani Ghaffari

We construct representation theory of Lie algebras with filtrations. In this framework a classification of irreducible representations is obtained and spectra of some reducible representations are found.

Representation Theory · Mathematics 2012-03-01 A. N. Panov

Dense networks with weighted connections often exhibit a community like structure, where although most nodes are connected to each other, different patterns of edge weights may emerge depending on each node's community membership. We…

Machine Learning · Statistics 2021-05-27 Benjamin Leinwand , Vladas Pipiras

We examine applications of polynomial Lie algebras $sl_{pd}(2)$ to solve physical tasks in $G_{inv}$-invariant models of coupled subsystems in quantum physics. A general operator formalism is given to solve spectral problems using…

Quantum Physics · Physics 2007-05-23 V. P. Karassiov

We consider correlation functions in 6d $(2,0)$ theories of two $\frac{1}{2}$-BPS operators inserted away from a $\frac{1}{2}$-BPS surface defect. In the large central charge limit the leading connected contribution corresponds to sums of…

High Energy Physics - Theory · Physics 2023-10-31 Junding Chen , Aleix Gimenez-Grau , Xinan Zhou

We propose a new way to build networks of defects. The idea takes advantage of the deformation procedure recently employed to describe defect structures, which we use to construct networks, spread from small rudimentary networks that appear…

High Energy Physics - Theory · Physics 2008-11-26 V. I. Afonso , D. Bazeia , M. A. Gonzalez Leon , L. Losano , J. Mateos Guilarte

The algebraic structure and the spectral properties of a special class of multi-component NLS equations, related to the symmetric spaces of {\bf BD.I}-type are analyzed. The focus of the study is on the spectral theory of the relevant Lax…

Exactly Solvable and Integrable Systems · Physics 2010-06-03 Vladimir S. Gerdjikov , Georgi G. Grahovski

We study the BPS spectrum of four dimensional N=2 SU(2) theory with massive fundamental matters using the D3-brane probe. Since the BPS states are realized by string webs subject to the BPS conditions, we determine explicitly the…

High Energy Physics - Theory · Physics 2009-10-31 Yukiko Ohtake

Network theory and inverse modeling are two standard tools of applied physics, whose combination is needed when studying the dynamical organization of spatially distributed systems from indirect measurements. However, the associated…

Data Analysis, Statistics and Probability · Physics 2015-01-30 Vincent Wens

We present a new, systematic approach for analyzing network topologies. We first introduce the dK-series of probability distributions specifying all degree correlations within d-sized subgraphs of a given graph G. Increasing values of d…

Networking and Internet Architecture · Computer Science 2008-04-16 Priya Mahadevan , Dmitri Krioukov , Kevin Fall , Amin Vahdat

Anomaly detection aims to distinguish observations that are rare and different from the majority. While most existing algorithms assume that instances are i.i.d., in many practical scenarios, links describing instance-to-instance…

Machine Learning · Computer Science 2019-10-10 Yuening Li , Xiao Huang , Jundong Li , Mengnan Du , Na Zou

This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D) surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model…

Neural and Evolutionary Computing · Computer Science 2009-12-14 Vincy Joseph , Shalini Bhatia

In this note we consider the set of line operators in theories of class $S$. We show that this set carries the action of a natural discrete dynamical system associated with the BPS spectrum. We discuss several applications of this…

High Energy Physics - Theory · Physics 2021-07-27 Michele Cirafici

We generalize the non-abelianization of Gaiotto-Moore-Neitzke from the case of $SL(n)$ and $GL(n)$ to arbitrary reductive algebraic groups. This gives a map between a moduli space of certain $N$-shifted weakly $W$-equivariant $T$-local…

Algebraic Geometry · Mathematics 2021-03-24 Matei Ionita , Benedict Morrissey

We study surface defects in 4d $\mathcal{N}=1$ $SU(N)$ superconformal gauge theories of class $\mathcal{S}_k$ obtained from the 6d (1,0) theories of type $A_{N-1}$, which are worldvolume theories on $N$ M5-branes at…

High Energy Physics - Theory · Physics 2021-01-01 Yuto Ito , Yutaka Yoshida

We propose a generalization of S-folds to 4d $\mathcal{N}=2$ theories. This construction is motivated by the classification of rank one 4d $\mathcal{N}=2$ super-conformal field theories (SCFTs), which we reproduce from D3-branes probing a…

High Energy Physics - Theory · Physics 2020-08-07 Fabio Apruzzi , Simone Giacomelli , Sakura Schafer-Nameki

We explore artificial neural networks as a tool for the reconstruction of spectral functions from imaginary time Green's functions, a classic ill-conditioned inverse problem. Our ansatz is based on a supervised learning framework in which…