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The discrepancy on the muon anomalous magnetic moment values obtained via a direct measurement and via a data-driven theory determination that uses the experimentally measured hadronic cross section, is among the long standing and most…

High Energy Physics - Experiment · Physics 2026-01-21 Zhiqing Zhang

The observation and description of collective excitations in solids is a fundamental issue when seeking to understand the physics of a many-body system. Analysis of these excitations is usually carried out by measuring the dynamical…

Repeated measurements are common in many fields, where random variables are observed repeatedly across different subjects. Such data have an underlying hierarchical structure, and it is of interest to learn covariance/correlation at…

Methodology · Statistics 2023-06-13 Sunpeng Duan , Guo Yu , Juntao Duan , Yuedong Wang

This paper proposes a flexible framework for inferring large-scale time-varying and time-lagged correlation networks from multivariate or high-dimensional non-stationary time series with piecewise smooth trends. Built on a novel and unified…

Methodology · Statistics 2023-02-13 Lujia Bai , Weichi Wu

We present a lattice determination of the leading-order hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment, $a_{\mu}^{\rm HVP}$, in the so-called short and intermediate time-distance windows, $a_{\mu}^{\rm…

The deviation of the measured value of the muon anomalous magnetic moment from the standard model prediction can be completely explained by mixing of the muon with extra vectorlike leptons, L and E, near the electroweak scale. This mixing…

High Energy Physics - Phenomenology · Physics 2013-08-09 Radovan Dermisek , Aditi Raval

In recent years, the anomalous magnetic moment of the muon has triggered a lot of activity in the lattice QCD community because a persistent tension of about $3.5~\sigma$ is observed between the phenomenological estimate and the Brookhaven…

High Energy Physics - Lattice · Physics 2021-04-21 Antoine Gérardin

We evaluate the leading-order hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon with two light flavors in minimal hard-wall and soft-wall holographic QCD models, as well as in simple generalizations…

High Energy Physics - Phenomenology · Physics 2022-06-08 Josef Leutgeb , Anton Rebhan , Michael Stadlbauer

A method is discussed that allows combining sets of differential or inclusive measurements. It is assumed that at least one measurement was obtained with simultaneously fitting a set of nuisance parameters, representing sources of…

Data Analysis, Statistics and Probability · Physics 2018-01-09 Jan Kieseler

The Standard Model prediction of the muon $g-2$ increasingly depends on lattice QCD computations of the hadronic vacuum polarization (HVP), where the isospin-breaking (IB) effects remain a significant source of uncertainty. To complement…

High Energy Physics - Phenomenology · Physics 2026-05-07 Volodymyr Biloshytskyi , Dominik Erb , Harvey B. Meyer , Julian Parrino , Vladimir Pascalutsa

We have performed a new evaluation of the hadronic contribution to $a_{\mu}=(g-2)/2$ of the muon with explicit correlations of systematic errors among the experimental data on $\sigma( e^+e^- \to hadrons )$. Our result for the lowest order…

High Energy Physics - Phenomenology · Physics 2014-11-17 D. H. Brown , W. A. Worstell

Our recent series of measurements at Brookhaven National Laboratory determined the muon anomalous magnetic moment \amu to a precision of 0.5 ppm. The final result--representing the average of five running periods using both positive and…

High Energy Physics - Experiment · Physics 2009-11-11 David W. Hertzog

We present a general framework for uncertainty quantification that is a mosaic of interconnected models. We define global first and second order structural and correlative sensitivity analyses for random counting measures acting on risk…

Probability · Mathematics 2021-01-05 Caleb Deen Bastian , Herschel Rabitz

Lattice QCD (LQCD) studies for the hadron vacuum polarization (HVP) and its contribution to the muon anomalous magnetic moment (muon g-2) are reviewed. There currently exists more than 3-sigma deviations in the muon g-2 between the BNL…

High Energy Physics - Lattice · Physics 2019-06-05 Kohtaroh Miura

Estimating a covariance matrix is central to high-dimensional data analysis. Empirical analyses of high-dimensional biomedical data, including genomics, proteomics, microbiome, and neuroimaging, among others, consistently reveal strong…

Methodology · Statistics 2024-12-05 Yifan Yang , Chixiang Chen , Shuo Chen

Conformal prediction provides a distribution-free framework for uncertainty quantification. This study explores the application of conformal prediction in scenarios where covariates are missing, which introduces significant challenges for…

Methodology · Statistics 2025-09-09 Jingsen Kong , YIming Liu , Guangren Yang

We present new lattice results of the ETM Collaboration, obtained from extensive simulations of lattice QCD with dynamical up, down, strange and charm quarks at physical mass values, different volumes and lattice spacings, concerning the SM…

The MUonE experiment aims at providing a new independent evaluation of the leading hadronic contribution to the muon anomalous magnetic moment. The proposed method is based on the measurement of the running of the QED coupling in the…

High Energy Physics - Phenomenology · Physics 2024-02-01 A. Gurgone

In this PhD thesis, we propose a novel framework for uncertainty quantification in machine learning, which is based on proper scores. Uncertainty quantification is an important cornerstone for trustworthy and reliable machine learning…

Machine Learning · Computer Science 2025-08-26 Sebastian G. Gruber

Estimation of the covariance matrix of asset returns is crucial to portfolio construction. As suggested by economic theories, the correlation structure among assets differs between emerging markets and developed countries. It is therefore…

Methodology · Statistics 2021-09-28 Xin Chen , Dan Yang , Yan Xu , Yin Xia , Dong Wang , Haipeng Shen
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