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Multivariate analyses play an important role in high energy physics. Such analyses often involve performing an unbinned maximum likelihood fit of a probability density function (p.d.f.) to the data. This paper explores a variety of unbinned…

High Energy Physics - Experiment · Physics 2011-07-13 Mike Williams

We present a study of the valence transversity PDF obtained through a constrained fit. The effects of the constraints on the uncertainties of the PDF are explored. We show that the resulting isovector tensor charge is largely undetermined…

High Energy Physics - Phenomenology · Physics 2021-08-05 A. Courtoy

The molecular rearrangements of most fluids under flow and deformation do not directly follow the macroscopic strain field. In this work, we describe a phenomenological method for characterizing such non-affine deformation via the…

Soft Condensed Matter · Physics 2018-01-17 Guan-Rong Huang , Bin Wu , Yangyang Wang , Wei-Ren Chen

The drag and diffusion coefficients of a hot hadronic medium have been evaluated by using hidden charm mesons as probes. The matrix elements for the evaluation of these coefficients are calculated using an effective theory as well as from…

Nuclear Theory · Physics 2016-03-22 Sukanya Mitra , Sabyasachi Ghosh , Santosh K. Das , Sourav Sarkar , Jan-e Alam

Besides the classical distinction of correlation and dependence, many dependence measures bear further pitfalls in their application and interpretation. The aim of this paper is to raise and recall awareness of some of these limitations by…

Methodology · Statistics 2020-04-17 Björn Böttcher

We consider the distributed detection problem of a temporally correlated random radio source signal using a wireless sensor network capable of measuring the energy of the received signals. It is well-known that optimal tests in the…

Signal Processing · Electrical Eng. & Systems 2023-12-20 Juan Augusto Maya , Leonardo Rey Vega , Andrea M. Tonello

Modeling users for the purpose of identifying their preferences and then personalizing services on the basis of these models is a complex task, primarily due to the need to take into consideration various explicit and implicit signals,…

Information Retrieval · Computer Science 2017-07-06 Amit Tiroshi , Tsvi Kuflik , Shlomo Berkovsky , Mohamed Ali Kaafar

The availability of metadata for scientific documents is pivotal in propelling scientific knowledge forward and for adhering to the FAIR principles (i.e. Findability, Accessibility, Interoperability, and Reusability) of research findings.…

Information Retrieval · Computer Science 2025-01-10 Zeyd Boukhers , Cong Yang

The drag and diffusion coefficients of a hot hadronic medium consisting of pions, kaons and eta using open beauty mesons as a probe have been evaluated. The interaction of the probe with the hadronic matter has been treated in the framework…

High Energy Physics - Phenomenology · Physics 2012-04-30 Santosh K Das , Sabyasachi Ghosh , Sourav Sarkar , Jan-e Alam

We propose a new way of thinking about one parameter persistence. We believe topological persistence is fundamentally not about decomposition theorems but a central role is played by a choice of metrics. Choosing a pseudometric between…

Algebraic Topology · Mathematics 2020-02-07 Wojciech Chachólski , Henri Riihimäki

In the era of "big data", it is becoming more of a challenge to not only build state-of-the-art predictive models, but also gain an understanding of what's really going on in the data. For example, it is often of interest to know which, if…

Machine Learning · Statistics 2018-05-15 Brandon M. Greenwell , Bradley C. Boehmke , Andrew J. McCarthy

Interpreting data with mathematical models is an important aspect of real-world industrial and applied mathematical modeling. Often we are interested to understand the extent to which a particular set of data informs and constrains model…

Methodology · Statistics 2025-03-06 Matthew J Simpson , Ruth E Baker

Parameter estimation is one of the most important tasks in statistics, and is key to helping people understand the distribution behind a sample of observations. Traditionally parameter estimation is done either by closed-form solutions…

Machine Learning · Computer Science 2024-03-04 Xiaoxin Yin , David S. Yin

We present an analysis strategy for probing physics beyond the Standard Model via modifications to the parton distribution functions (PDFs) in a muon beam, which measurably alter the kinematics of all hard processes at a future muon…

High Energy Physics - Phenomenology · Physics 2026-02-20 Pouya Asadi , Austin Batz , Samuel Homiller , Tien-Tien Yu

Dynamic factor models are often estimated by point-estimation methods, disregarding parameter uncertainty. We propose a method accounting for parameter uncertainty by means of posterior approximation, using variational inference. Our…

Methodology · Statistics 2022-10-14 Erik Spånberg

We show that the parton distribution functions (PDF) described by the statistical model have very interesting physical properties which help to understand the structure of partons. The role of the quark helicity components is emphasized as…

High Energy Physics - Phenomenology · Physics 2015-09-28 Claude Bourrely

The finite energy sum rule extraction of the strong coupling {\alpha}_s from hadronic {\tau} decay data provides one of its most precise experimental determinations. As precision improves, small non-perturbative effects become increasingly…

High Energy Physics - Lattice · Physics 2011-11-23 Diogo Boito , Oscar Catà , Maarten Golterman , Matthias Jamin , Kim Maltman , James Osborne , Santiago Peris

We propose a coefficient that measures the dependence among large values for spatial processes of maxima. Its main properties are: a) $k$ locations can be taken into account; b) it takes values in $[0,1]$ and higher values indicate stronger…

Statistics Theory · Mathematics 2015-06-22 Helena Ferreira , Luisa Pereira

Physics models typically contain adjustable parameters to reproduce measured data. While some parameters correspond directly to measured features in the data, others are unobservable. These unobservables can, in some cases, cause…

Nuclear Theory · Physics 2024-03-11 C. H. Kim , K. Y. Chae , M. S. Smith , D. W. Bardayan , C. R. Brune , R. J. deBoer , D. Lu , D. Odell

A major bottleneck in nanoparticle measurements is the lack of comparability. Comparability of measurement results is obtained by metrological traceability, which is obtained by calibration. In the present work the calibration of…

Applications · Statistics 2018-12-24 J. Pétry , B. De Boeck , N. Sebaihi , M. Coenegrachts , T. Caebergs , M. Dobre
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