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An important limitation in current fits of parton distribution functions (PDFs) is that PDF uncertainties do not include any source of theoretical uncertainty. Here we present a general method for incorporating theoretical uncertainties…

高能物理 - 唯象学 · 物理学 2018-10-05 R. L. Pearson , C. Voisey

In this talk, we present the results from our recent global reanalysis of nuclear parton distribution functions (nPDFs), where the DGLAP-evolving nPDFs are constrained by nuclear hard process data from deep inelastic $l+A$ scattering (DIS)…

高能物理 - 唯象学 · 物理学 2008-11-26 K. J. Eskola , V. J. Kolhinen , H. Paukkunen , C. A. Salgado

The precise knowledge of parton distribution functions (PDFs) is indispensable to the accurate calculation of hadron-initiated QCD hard scattering observables. Much of our information on PDFs is extracted by comparing deep inelastic…

高能物理 - 唯象学 · 物理学 2013-10-03 David Westmark

We determine the strong coupling alpha_s from a next-to-leading order analysis of processes used for the NNPDF2.1 parton determination, which includes data from neutral and charged current deep-inelastic scattering, Drell-Yan and inclusive…

A study is presented of the impact of simulated inclusive Electron Ion Collider Deep Inelastic Scattering data on the determination of the proton and nuclear parton distribution functions (PDFs) at next-to-next-to-leading and…

Hessian PDF reweighting, or "profiling", has become a widely used way to study the impact of a new data set on parton distribution functions (PDFs) with Hessian error sets. The available implementations of this method have resorted to a…

高能物理 - 唯象学 · 物理学 2019-09-27 Kari J. Eskola , Petja Paakkinen , Hannu Paukkunen

A simultaneous fit of parton distribution functions (PDFs) and electroweak parameters to HERA data on deep inelastic scattering is presented. The input data are the neutral current and charged current inclusive cross sections which were…

高能物理 - 实验 · 物理学 2016-05-16 ZEUS Collaboration , H. Abramowicz , I. Abt , L. Adamczyk , M. Adamus , S. Antonelli , V. Aushev , O. Behnke , U. Behrens , A. Bertolin , S. Bhadra , I. Bloch , E. G. Boos , I. Brock , N. H. Brook , R. Brugnera , A. Bruni , P. J. Bussey , A. Caldwell , M. Capua , C. D. Catterall , J. Chwastowski , J. Ciborowski , R. Ciesielski , A. M. Cooper-Sarkar , M. Corradi , R. K. Dementiev , R. C. E. Devenish , S. Dusini , B. Foster , G. Gach , E. Gallo , A. Garfagnini , A. Geiser , A. Gizhko , L. K. Gladilin , Yu. A. Golubkov , G. Grzelak , M. Guzik , C. Gwenlan , W. Hain , O. Hlushchenko , D. Hochman , R. Hori , Z. A. Ibrahim , Y. Iga , M. Ishitsuka , F. Januschek , N. Z. Jomhari , I. Kadenko , S. Kananov , U. Karshon , P. Kaur , D. Kisielewska , R. Klanner , U. Klein , I. A. Korzhavina , A. Kotanski , U. Koetz , N. Kovalchuk , H. Kowalski , B. Krupa , O. Kuprash , M. Kuze , B. B. Levchenko , A. Levy , S. Limentani , M. Lisovyi , E. Lobodzinska , B. Loehr , E. Lohrmann , A. Longhin , D. Lontkovskyi , O. Yu. Lukina , I. Makarenko , J. Malka , A. Mastroberardino , F. Mohamad Idris , N. Mohammad Nasir , V. Myronenko , K. Nagano , T. Nobe , R. J. Nowak , Yu. Onishchuk , E. Paul , W. Perlanski , N. S. Pokrovskiy , A. Polini , M. Przybycien , P. Roloff , M. Ruspa , D. H. Saxon , M. Schioppa , U. Schneekloth , T. Schoerner-Sadenius , L. M. Shcheglova , R. Shevchenko , O. Shkola , Yu. Shyrma , I. Singh , I. O. Skillicorn , W. Slominski , A. Solano , L. Stanco , N. Stefaniuk , A. Stern , P. Stopa , J. Sztuk-Dambietz , E. Tassi , K. Tokushuku , J. Tomaszewska , T. Tsurugai , M. Turcato , O. Turkot , T. Tymieniecka , A. Verbytskyi , W. A. T. Wan Abdullah , K. Wichmann , M. Wing , S. Yamada , Y. Yamazaki , N. Zakharchuk , A. F. Zarnecki , L. Zawiejski , O. Zenaiev , B. O. Zhautykov , D. S. Zotkin

Factor models have been widely used in economics and finance. However, the heavy-tailed nature of macroeconomic and financial data is often neglected in the existing literature. To address this issue and achieve robustness, we propose an…

统计方法学 · 统计学 2023-03-30 Yong He , Lingxiao Li , Dong Liu , Wen-Xin Zhou

We have presented the results of our next-to-next-to-leading order (NNLO) QCD analysis of nuclear parton distribution functions (nuclear PDFs) [Phys. Rev. D 93 (2016) 014026, arXiv:1601.00939 [hep-ph]] using all available neutral current…

高能物理 - 唯象学 · 物理学 2020-12-17 S. Atashbar Tehrani

A recent study by Wang {\it et al.}(arXiv:2309.01417) proposed a novel connection between the nature of the parton distribution function (PDF) and the characteristics of its moments. In this study, we apply these findings to analyze the…

高能物理 - 唯象学 · 物理学 2024-07-16 Xiaobin Wang , Zexin Wu , Minghui Ding , Lei Chang

This article presents the results of a quantitative study of the small-x data at HERA, using the CCFM equation. The first step consists of choosing the version of the CCFM equation to be used, corresponding to selecting a particular subset…

高能物理 - 唯象学 · 物理学 2014-11-17 G. Bottazzi , G. Marchesini , G. P. Salam , M. Scorletti

We present a method developed by the NNPDF Collaboration that allows the inclusion of new experimental data into an existing set of parton distribution functions without the need for a complete refit. A Monte Carlo ensemble of PDFs may be…

高能物理 - 唯象学 · 物理学 2015-06-03 Francesco Cerutti , Nathan Hartland

The trade-off between general-purpose foundation vision models and their specialized counterparts is critical for efficient feature coding design and is not yet fully understood. We investigate this trade-off by comparing the feature…

计算机视觉与模式识别 · 计算机科学 2025-10-21 Masoud Khairi Atani , Alon Harell , Hyomin Choi , Runyu Yang , Fabien Racape , Ivan V. Bajic

Beyond leading-order, perturbative QCD requires a choice of factorisation scheme to define the parton distribution functions (PDFs) and hard-process cross-section. The modified minimal-subtraction ($\overline{\mathrm{MS}}$) scheme has long…

高能物理 - 唯象学 · 物理学 2025-05-12 Stéphane Delorme , Aleksander Kusina , Andrzej Siódmok , James Whitehead

In this work we show that the classification performance of high-dimensional structural MRI data with only a small set of training examples is improved by the usage of dimension reduction methods. We assessed two different dimension…

机器学习 · 计算机科学 2015-05-27 Andreas Grünauer , Markus Vincze

We present NNPDFpol2.0, a new set of collinear helicity parton distribution functions (PDFs) of the proton based on legacy measurements of structure functions in inclusive neutral-current longitudinally polarised deep-inelastic scattering…

A new analysis of the modification of the hadronization process in the nuclear medium for pions is presented. The effective description is condensed in a set of medium modified fragmentation functions (nFFs) obtained at next-to-leading…

高能物理 - 唯象学 · 物理学 2021-01-05 Pía Zurita

The computation of the parton distribution functions (PDF) or distribution amplitudes (DA) of hadrons from first principles lattice QCD constitutes a central open problem. In this study, we present and evaluate the efficiency of a selection…

高能物理 - 格点 · 物理学 2019-05-01 Joseph Karpie , Kostas Orginos , Alexander Rothkopf , Savvas Zafeiropoulos

We present a new methodology that is able to yield a simultaneous determination of the Parton Distribution Functions (PDFs) of the proton alongside any set of parameters that determine the theory predictions; whether within the Standard…

高能物理 - 唯象学 · 物理学 2022-05-12 Shayan Iranipour , Maria Ubiali

The choice of data that enters a global QCD analysis can have a substantial impact on the resulting parton distributions and their predictions for collider observables. One of the main reasons for this has to do with the possible presence…

高能物理 - 唯象学 · 物理学 2014-09-11 Juan Rojo