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We consider adaptive estimation and statistical inference for high-dimensional graph-based linear models. In our model, the coordinates of regression coefficients correspond to an underlying undirected graph. Furthermore, the given graph…

Statistics Theory · Mathematics 2020-01-30 Duzhe Wang , Po-Ling Loh

We introduce an approach to expand gauge-invariant Wilson operators on lattice. This approach is based on non-abelian Stokes theorem and overcomes some shortage of some former methods. It is also suitable for expanding any Wilson operators…

High Energy Physics - Lattice · Physics 2014-11-17 Da Qing Liu , Ji Min Wu

We propose a new approach to the combinatorial interpretations of linearization coefficient problem of orthogonal polynomials. We first establish a difference system and then solve it combinatorially and analytically using the method of…

Classical Analysis and ODEs · Mathematics 2012-11-20 Mourad E. H. Ismail , Anisse Kasraoui , Jiang Zeng

We discuss the possibility of non-minimal gauge invariance of transverse-momentum-dependent parton densities (TMDs) that allows direct access to the spin degrees of freedom of fermion fields entering the operator definition of (quark) TMDs.…

High Energy Physics - Phenomenology · Physics 2011-12-13 I. O. Cherednikov , A. I. Karanikas , N. G. Stefanis

Parametric models in vector spaces are shown to possess an associated linear map. This linear operator leads directly to reproducing kernel Hilbert spaces and affine- / linear- representations in terms of tensor products. From the…

Numerical Analysis · Mathematics 2018-06-19 Hermann G. Matthies , Roger Ohayon

In this text we develop the formalism of products and powers of linear codes under componentwise multiplication. As an expanded version of the author's talk at AGCT-14, focus is put mostly on basic properties and descriptive statements that…

Information Theory · Computer Science 2014-10-15 Hugues Randriambololona

We study the convergence of distributions on finite paths of weighted digraphs, namely the family of Boltzmann distributions and the sequence of uniform distributions. Targeting applications to the convergence of distributions on paths, we…

Probability · Mathematics 2024-10-04 Samy Abbes

We show that it is possible to improve the chiral behaviour and the approach to the continuum limit of correlation functions in lattice QCD with Wilson fermions by taking arithmetic averages of correlators computed in theories regularized…

High Energy Physics - Lattice · Physics 2009-11-10 R. Frezzotti , G. C. Rossi

We show that weighted path orders are special instances of a variant of semantic path orders. Exploiting this fact, we introduce a generalization of weighted path orders that goes beyond the realm of simple termination. Experimental data…

Logic in Computer Science · Computer Science 2023-07-27 Teppei Saito , Nao Hirokawa

We extend the use of piecewise orthogonal collocation to computing periodic solutions of renewal equations, which are particularly important in modeling population dynamics. We prove convergence through a rigorous error analysis. Finally,…

Numerical Analysis · Mathematics 2023-12-08 Alessia Ando' , Dimitri Breda

We review the state-of-the-art knowledge of IR singularities in multileg QCD amplitudes, identifying the key reasons for the remarkable simplicity of the soft anomalous dimension. We then present a novel strategy to compute this quantity…

High Energy Physics - Phenomenology · Physics 2026-04-22 Einan Gardi , Zehao Zhu

In a gauge theory at nonzero temperature the eigenvalues of the Wilson line form a set of gauge invariant observables. By constructing the corresponding partition function for the phases of these eigenvalues, we prove that the trivial…

High Energy Physics - Phenomenology · Physics 2009-10-22 A. Gocksch , R. D. Pisarski

We employ the Transformer to learn patterns in two-dimensional lattice Yang-Mills theory. Specifically, we represent both Wilson loops and their expectation values as tokenized sequences. Taking the shape of Wilson loops as input, the model…

High Energy Physics - Theory · Physics 2025-10-29 Zeyu Li , Guorui Zhu , Wenjie He , Bo Feng , Jiaqi Chen , Ming-xing Luo , Gang Yang

This paper proposes a method for solving multivariate regression and classification problems using piecewise linear predictors over a polyhedral partition of the feature space. The resulting algorithm that we call PARC (Piecewise Affine…

Machine Learning · Computer Science 2021-03-11 Alberto Bemporad

Circuit analysis of any certain model behavior is a central task in mechanistic interpretability. We introduce our circuit discovery pipeline with Sparse Autoencoders (SAEs) and a variant called Transcoders. With these two modules inserted…

Machine Learning · Computer Science 2024-07-23 Xuyang Ge , Fukang Zhu , Wentao Shu , Junxuan Wang , Zhengfu He , Xipeng Qiu

As an improvement of the QCD sum rule method to study modifications of light vector mesons in nuclear matter and/or at finite temperature, we calculate the Wilson coefficients of all independent gluonic non-scalar operators up to dimension…

High Energy Physics - Phenomenology · Physics 2017-07-04 HyungJoo Kim , Philipp Gubler , Su Houng Lee

Large language models can change answers under harmless edits that matter in practice: RAG outputs flip when passages are reordered, fine-tuning erodes invariances learned at pretraining, debate or chain-of-thought prompts take…

Machine Learning · Computer Science 2025-10-13 Edward Y. Chang , Ethan Y. Chang

In this paper we study Wilson loops in various representations for finite and large values of the color gauge group for supersymmetric ${\cal N}=4$ gauge theories. We also compute correlators of Wilson loops in different representations and…

High Energy Physics - Theory · Physics 2018-11-14 Ekaterina Sysoeva

We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish…

Statistics Theory · Mathematics 2011-12-13 Li Wang , Xiang Liu , Hua Liang , Raymond J. Carroll

Partially linear additive models generalize linear ones since they model the relation between a response variable and covariates by assuming that some covariates have a linear relation with the response but each of the others enter through…

Methodology · Statistics 2023-08-08 Graciela Boente , Alejandra Mercedes Martinez