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Exploring baryon resonances with transition generalized parton distributions: status and perspectives

2025· article· en· W4399062319 on OpenAlexafffund
S. Diehl, K. Joo, K. Semenov-Tian-Shansky, Christian Weiss, V. M. Braun, W. C. Chang, P. Chatagnon, Martha Constantinou, Yuxun Guo, Parada T. P. Hutauruk, H. S. Jo, Andrey Kim, Junyoung Kim, P. Kroll, S. Kumano, Chang‐Hwan Lee, Simonetta Liuti, R. McNulty, Hyeon-Dong Son, P. Sznajder, A. Usman, C. V. Hulse, Marc Vanderhaeghen, M. Winn

Bibliographic record

VenueThe European Physical Journal A · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsUniversity of Regina
FundersJapan Society for the Promotion of ScienceOffice of ScienceFoundation for the Advancement of Theoretical Physics and MathematicsDeutsche ForschungsgemeinschaftStrongNational Research FoundationNuclear PhysicsNatural Sciences and Engineering Research Council of CanadaMinistry of Science and ICT, South KoreaU.S. Department of EnergyEuropean CommissionBundesministerium für Bildung und ForschungComunidad de MadridNational Research Foundation of KoreaNational Science Foundation
KeywordsPartonBaryonPhysicsParticle physicsTransition (genetics)Baryon numberStatistical physicsNuclear physicsQuantum chromodynamicsChemistry

Abstract

fetched live from OpenAlex

Abstract QCD gives rise to a rich spectrum of excited baryon states. Understanding their internal structure is important for many areas of nuclear physics, such as nuclear forces, dense matter, and neutrino-nucleus interactions. Generalized parton distributions (GPDs) are an established tool for characterizing the QCD structure of the ground-state nucleon. They are used to create 3D tomographic images of the quark/gluon structure and quantify the mechanical properties such as the distribution of mass, angular momentum, and forces in the system. Transition GPDs extend these concepts to $$N \rightarrow N^*$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>N</mml:mi> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>N</mml:mi> <mml:mo>∗</mml:mo> </mml:msup> </mml:mrow> </mml:math> transitions and can be used to characterize the 3D structure and mechanical properties of baryon resonances. They can be probed in high-momentum-transfer exclusive electroproduction processes with resonance transitions $$e + N \rightarrow e' + M + N^*$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>e</mml:mi> <mml:mo>+</mml:mo> <mml:mi>N</mml:mi> <mml:mo>→</mml:mo> <mml:msup> <mml:mi>e</mml:mi> <mml:mo>′</mml:mo> </mml:msup> <mml:mo>+</mml:mo> <mml:mi>M</mml:mi> <mml:mo>+</mml:mo> <mml:msup> <mml:mi>N</mml:mi> <mml:mo>∗</mml:mo> </mml:msup> </mml:mrow> </mml:math> , such as deeply-virtual Compton scattering ( $$M = \gamma $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>M</mml:mi> <mml:mo>=</mml:mo> <mml:mi>γ</mml:mi> </mml:mrow> </mml:math> ) or meson production ( $$M = \pi , K$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>M</mml:mi> <mml:mo>=</mml:mo> <mml:mi>π</mml:mi> <mml:mo>,</mml:mo> <mml:mi>K</mml:mi> </mml:mrow> </mml:math> , etc.), and in related photon/hadron-induced processes. This White Paper describes a research program aiming to explore baryon resonance structure with transition GPDs. This includes the properties and interpretation of the transition GPDs, theoretical methods for structures and processes, first experimental results from JLab 12 GeV, future measurements with existing and planned facilities (JLab detector and energy upgrades, COMPASS/AMBER, EIC, EicC, J-PARC, LHC ultraperipheral collisions), and the theoretical and experimental developments needed to realize this program.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.261
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2025
Admission routes2
Has abstractyes

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