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相关论文: Accessing Compton Form Factors at the Electron Ion…

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We assess the impact of future measurements of deeply virtual Compton scattering (DVCS) off protons using the planned detector at the Electron-Ion Collider in China (EicC), proposed as an upgrade to the High Intensity heavy-ion Accelerator…

高能物理 - 唯象学 · 物理学 2026-05-26 Yuan-Yuan Huang , Xu Cao , Taifu Feng , Krešimir Kumerički , Yu Lu

The extraction of Compton Form Factors (CFFs) in a global analysis of almost all Deeply Virtual Compton Scattering (DVCS) proton data is presented. The extracted quantities are DVCS sub-amplitudes and the most basic observables which are…

高能物理 - 唯象学 · 物理学 2019-07-25 H. Moutarde , P. Sznajder , J. Wagner

This study presents the impact of future measurements of deeply virtual Compton scattering (DVCS) with the ePIC detector at the electron-ion collider (EIC), currently under construction at Brookhaven National Laboratory. The considered…

The study of hadronic structure has been carried out for many years. Generalized parton distribution functions (GPDs) give broad information on the internal structure of hadrons. Combining GPDs and high-energy scattering experiments, we…

高能物理 - 唯象学 · 物理学 2023-06-06 Gang Xie , Wei Kou , Qiang Fu , Zhenyu Ye , Xurong Chen

The impact of potential future measurements of beam charge asymmetries on the current knowledge of Compton form factors is evaluated. Elaborating on the results of a global neural network fit to deeply virtual Compton scattering data, a…

高能物理 - 唯象学 · 物理学 2021-09-01 H. Dutrieux , V. Bertone , H. Moutarde , P. Sznajder

We investigate the exercise of locally extracting the real and imaginary parts of the four twist-2 Compton form factors (CFFs) $\{\mathcal{H},\mathcal{E},\widetilde{\mathcal{H}},\widetilde{\mathcal{E}}\}$ which arise in the deeply virtual…

高能物理 - 唯象学 · 物理学 2022-08-24 Kyle Shiells , Yuxun Guo , Xiangdong Ji

We develop a new methodology for extracting Compton form factors (CFFs) in from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized inverse problem solver, a variational autoencoder inverse…

高能物理 - 唯象学 · 物理学 2024-08-13 Manal Almaeen , Tareq Alghamdi , Brandon Kriesten , Douglas Adams , Yaohang Li , Huey-Wen Lin , Simonetta Liuti

We present the results of a fitter code which aims at extracting Compton Form Factors (CFFs) from DVCS (Deep Virtual Compton Scattering) experimental data, in a largely model-independent way. CFFs are linked to GPDs (Generalized parton…

高能物理 - 唯象学 · 物理学 2010-11-19 Michel Guidal

We have generated a parametrization of the Compton form factor (CFF) H based on data from deeply virtual Compton scattering (DVCS) using neural networks. This approach offers an essentially model-independent fitting procedure, which…

高能物理 - 唯象学 · 物理学 2015-05-28 Kresimir Kumericki , Dieter Mueller , Andreas Schafer

Deeply virtual exclusive scattering processes (DVES) serve as precise probes of nucleon quark and gluon distributions in coordinate space. These distributions are derived from generalized parton distributions (GPDs) via Fourier transform…

We present a quantitative assessment of the impact a future Electron-Ion Collider would have in the determination of parton distribution functions in the proton and parton-to-hadron fragmentation functions through semi-inclusive…

高能物理 - 唯象学 · 物理学 2019-05-15 Elke C. Aschenauer , Ignacio Borsa , Rodolfo Sassot , Charlotte Van Hulse

We analyze the hard scattering amplitude of gravitational form factors (GFFs) of hadrons within QCD factorization at large momentum transfers, focusing on their conformal field theory (CFT) description. These form factors are key to…

高能物理 - 唯象学 · 物理学 2024-10-03 Claudio Corianò , Stefano Lionetti , Dario Melle , Riccardo Tommasi

We report high-precision measurements of the Deeply Virtual Compton Scattering (DVCS) cross section at high values of the Bjorken variable $x_B$. DVCS is sensitive to the Generalized Parton Distributions of the nucleon, which provide a…

高能物理 - 唯象学 · 物理学 2022-07-13 F. Georges , M. N. H. Rashad , A. Stefanko , M. Dlamini , B. Karki , S. F. Ali , P-J. Lin , H-S Ko , N. Israel , D. Adikaram , Z. Ahmed , H. Albataineh , B. Aljawrneh , K. Allada , S. Allison , S. Alsalmi , D. Androic , K. Aniol , J. Annand , H. Atac , T. Averett , C. Ayerbe Gayoso , X. Bai , J. Bane , S. Barcus , K. Bartlett , V. Bellini , R. Beminiwattha , J. Bericic , D. Biswas , E. Brash , D. Bulumulla , J. Campbell , A. Camsonne , M. Carmignotto , J. Castellano , C. Chen , J-P. Chen , T. Chetry , M. E. Christy , E. Cisbani , B. Clary , E. Cohen , N. Compton , J. C. Cornejo , S. Covrig Dusa , B. Crowe , S. Danagoulian , T. Danley , F. De Persio , W. Deconinck , M. Defurne , C. Desnault , D. Di , M. Duer , B. Duran , R. Ent , C. Fanelli , G. Franklin , E. Fuchey , C. Gal , D. Gaskell , T. Gautam , O. Glamazdin , K. Gnanvo , V. M. Gray , C. Gu , T. Hague , G. Hamad , D. Hamilton , K. Hamilton , O. Hansen , F. Hauenstein , W. Henry , D. W. Higinbotham , T. Holmstrom , T. Horn , Y. Huang , G. M. Huber , C. Hyde , H. Ibrahim , C-M. Jen , K. Jin , M. Jones , A. Kabir , C. Keppel , V. Khachatryan , P. M. King , S. Li , W. B. Li , J. Liu , H. Liu , A. Liyanage , J. Magee , S. Malace , J. Mammei , P. Markowitz , E. McClellan , M. Mazouz , F. Meddi , D. Meekins , K. Mesik , R. Michaels , A. Mkrtchyan , R. Montgomery , C. Muñoz Camacho , L. S. Myers , P. Nadel-Turonski , S. J. Nazeer , V. Nelyubin , D. Nguyen , N. Nuruzzaman , M. Nycz , O. F. Obretch , L. Ou , C. Palatchi , B. Pandey , S. Park , K. Park , C. Peng , R. Pomatsalyuk , E. Pooser , A. J. R. Puckett , V. Punjabi , B. Quinn , S. Rahman , P. E. Reimer , J. Roche , I. Sapkota , A. Sarty , B. Sawatzky , N. H. Saylor , B. Schmookler , M. H. Shabestari , A. Shahinyan , S. Sirca , G. R. Smith , S. Sooriyaarachchilage , N. Sparveris , R. Spies , T. Su , A. Subedi , V. Sulkosky , A. Sun , L. Thorne , Y. Tian , N. Ton , F. Tortorici , R. Trotta , G. M. Urciuoli , E. Voutier , B. Waidyawansa , Y. Wang , B. Wojtsekhowski , S. Wood , X. Yan , L. Ye , Z. Ye , C. Yero , J. Zhang , Y. Zhao , P. Zhu

We extract Compton form factors (CFFs) from deeply virtual Compton scattering measurements at the Thomas Jefferson National Accelerator Facility (JLab) using quantum-inspired deep neural networks (QDNNs). The analysis implements the twist-2…

机器学习 · 计算机科学 2026-04-30 Brandon B. Le , Dustin Keller

Several observables for the deeply virtual Compton scattering process have been simulated in the kinematic regime of a proposed Electron-Ion Collider to explore the possible impact of such measurements for the phenomenological access of…

高能物理 - 唯象学 · 物理学 2015-06-15 Elke-Caroline Aschenauer , Salvatore Fazio , Kresimir Kumericki , Dieter Mueller

We present a quantitative assessment of the anticipated impact of future Electron-Ion Collider (EIC) measurements on the extraction of parton-to-pion fragmentation functions (FFs). Our analysis combines simulated semi-inclusive…

高能物理 - 唯象学 · 物理学 2025-10-09 Maryam Soleymaninia , Hamzeh Khanpour , Majid Azizi , Hadi Hashamipour

A likelihood analysis of the observables in deeply virtual exclusive photoproduction off a proton target, $ep \rightarrow e' p' \gamma'$, is presented. Two processes contribute to the reaction: deeply virtual Compton scattering, where the…

Transverse momentum-dependent parton distribution functions (TMDs) provide three-dimensional imaging of the nucleon in the momentum space. With its fundamental importance in understanding the spin structure of the nucleon, the precise…

高能物理 - 唯象学 · 物理学 2024-03-11 Chunhua Zeng , Tianbo Liu , Peng Sun , Yuxiang Zhao

We utilize the DVCS asymmetry measurements of the HERMES collaboration for access to Compton form factors in the deeply virtual regime and to generalized parton distributions. In particular, the (almost) complete measurement of DVCS…

高能物理 - 唯象学 · 物理学 2015-06-12 Kresimir Kumericki , Dieter Mueller , Morgan Murray

Generalized Parton Distributions (GPDs) are multidimensional structure functions of hadrons, encoding mechanical and spin properties through the correlation of the momentum and transverse position of partons. While channels like Deeply…

高能物理 - 唯象学 · 物理学 2025-09-16 J. S. Alvarado , M. Hoballah , E. Voutier
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