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The predictive power of perturbative QCD (pQCD) depends on two important issues: (1) how to eliminate the renormalization scheme-and-scale ambiguities at fixed order, and (2) how to reliably estimate the contributions of unknown…

High Energy Physics - Phenomenology · Physics 2019-03-27 Bo-Lun Du , Xing-Gang Wu , Jian-Ming Shen , Stanley J. Brodsky

Most ML datasets today contain biases. When we train models on these datasets, they often not only learn these biases but can worsen them -- a phenomenon known as bias amplification. Several co-occurrence-based metrics have been proposed to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Bhanu Tokas , Rahul Nair , Hannah Kerner

In this work we consider the possibility of representing the perturbative series for renormalization group invariant quantities in QCD in the form of their decomposition in powers of the conformal anomaly $\beta(\alpha_s)/\alpha_s$ in the…

High Energy Physics - Phenomenology · Physics 2022-11-21 A. L. Kataev , V. S. Molokoedov

We present two variants of an approach for evaluation of observables in analytic QCD models. The approach is motivated by the skeleton expansion in a certain class of schemes. We then evaluate the Adler function at low energies in one…

High Energy Physics - Phenomenology · Physics 2009-11-11 Gorazd Cvetic , Cristian Valenzuela

We introduce a new method for estimating the parameter of the bivariate Clayton copulas within the framework of Algorithmic Inference. The method consists of a variant of the standard boot-strapping procedure for inferring random…

Machine Learning · Statistics 2019-10-08 Bruno Apolloni

We consider the problem of asymptotic reconstruction of the state and parameter values in systems of ordinary differential equations. A solution to this problem is proposed for a class of systems of which the unknowns are allowed to be…

Optimization and Control · Mathematics 2015-03-13 Ivan Y. Tyukin , Erik Steur , Henk Nijmeijer , Cees van Leeuwen

Quadratic and Linear Discriminant Analysis (QDA/LDA) are the most often applied classification rules under normality. In QDA, a separate covariance matrix is estimated for each group. If there are more variables than observations in the…

Methodology · Statistics 2016-12-26 Stéphanie Aerts , Ines Wilms

This paper gives an overview of recently developed model for the QCD analytic invariant charge. Its underlying idea is to bring the analyticity condition, which follows from the general principles of local Quantum Field Theory, in…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. V. Nesterenko

The Altarelli-Parisi-Lipatov equations for the parton distribution functions are rederived using the dynamical renormalization group approach to quantum kinetics. This method systematically treats the ln Q^2 corrections that arises in…

High Energy Physics - Phenomenology · Physics 2014-11-17 D. Boyanovsky , H. J. de Vega , D. -S. Lee , S. -Y. Wang , H. -L. Yu

Perturbative renormalization group theory is developed as a unified tool for global asymptotic analysis. With numerous examples, we illustrate its application to ordinary differential equation problems involving multiple scales, boundary…

High Energy Physics - Theory · Physics 2008-11-26 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

An outline is given of an extended perturbative solution of Euclidean QCD which systematically accounts for a class of nonperturbative effects, while allowing renormalization by the perturbative counterterms. Proper vertices Gamma are…

High Energy Physics - Theory · Physics 2014-11-18 M. Stingl

SDE-based methods such as denoising diffusion probabilistic models (DDPMs) have shown remarkable success in real-world sample generation tasks. Prior analyses of DDPMs have been focused on the exponential Euler discretization, showing…

Machine Learning · Computer Science 2025-11-10 Matthew S. Zhang , Stephen Huan , Jerry Huang , Nicholas M. Boffi , Sitan Chen , Sinho Chewi

The `renormalon' or `dispersive' method for estimating non-perturbative corrections to QCD observables is reviewed. The corrections are power-suppressed, i.e. of the form $A/Q^p$ where $Q$ is the hard process momentum scale. The renormalon…

High Energy Physics - Phenomenology · Physics 2009-10-30 B. R. Webber

We tackle the problem of building adaptive estimation procedures for ill-posed inverse problems. For general regularization methods depending on tuning parameters, we construct a penalized method that selects the optimal smoothing sequence…

Statistics Theory · Mathematics 2008-07-31 Jean-Michel Loubes , Carenne Ludeña

Renormalization scheme uncertainties in the next-next-to-leading order QCD predictions are discussed. To obtain an estimate of these uncertainties it is proposed to compare predictions in all schemes that do not have unnaturally large…

High Energy Physics - Phenomenology · Physics 2009-10-28 Piotr A. Raczka

Based on the renormalization group summation method of McKeon ${\it et\; al.}$, it is shown that the renormalization group equation, while related to the radiatively mass scale $\mu$, would perform a summation over QCD perturbative terms.…

High Energy Physics - Phenomenology · Physics 2020-02-19 M. Akrami , A. Mirjalili

Two different models exhibiting self-organized criticality are analyzed by means of the dynamic renormalization group. Although the two models differ by their behavior under a parity transformation of the order parameter, it is shown that…

Condensed Matter · Physics 2009-10-22 Albert Diaz-Guilera

We present the estimates of the order $O(\alpha^{4}_{s})$ QCD corrections to $R(s)$, $R_{\tau}$ and to the deep-inelastic scattering sum rules, namely to the non-polarized and polarized Bjorken sum rules and to the Gross-Llewellyn Smith sum…

High Energy Physics - Phenomenology · Physics 2008-02-03 A. L. Kataev , V. V. Starshenko

With the availability of extraordinarily huge data sets, solving the problems of distributed statistical methodology and computing for such data sets has become increasingly crucial in the big data area. In this paper, we focus on the…

Machine Learning · Statistics 2023-10-24 Yue Chao , Lei Huang , Xuejun Ma

Derived from the regular perturbation treatment of the nonlinear Schrodinger equation, a machine learning-based scheme to mitigate the intra-channel optical fiber nonlinearity is proposed. Referred to as the perturbation theory-aided (PA)…

Signal Processing · Electrical Eng. & Systems 2022-04-06 Xiang Lin , Shenghang Luo , Sunish Kumar Orappanpara Soman , Octavia A. Dobre , Lutz Lampe , Deyuan Chang , Chuandong Li