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Record W2769864047 · doi:10.2172/1408895

Deep Exclusive Pseudoscalar Meson Production at Jefferson Lab Hall C

2017· report· en· W2769864047 on OpenAlexaff
S. Basnet

Bibliographic record

Venuenot available
Typereport
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPhysicsParticle physicsQuantum chromodynamicsHadronNuclear physicsMesonPerturbative QCDMomentum transferDegrees of freedom (physics and chemistry)QuarkScatteringQuantum mechanics

Abstract

fetched live from OpenAlex

Measurements of exclusive meson production are a useful tool in the study of hadronic structure. In particular, one can discern the relevant degrees of freedom at different distance scales through these studies. In the transition region between low momentum transfer (where a description of hadronic degrees of freedom in terms of effective hadronic Lagrangians is valid) and high momentum transfer (where the degrees of freedom are quarks and gluons), the predictive power of Quantum Chromodynamics (QCD), the theory of the strong interaction, is limited due to the absence of a complete solution. Thus, one has to rely upon experimental data from the non-perturbative intermediate-energy regime to thoroughly understand the onset of perturbative QCD (pQCD) as the momentum transfer is increased. This work involves two deep exclusive meson electroproduction experiments at Jefferson Lab (JLab). The p(e,e'pi+)n reaction is studied at fixed Q^2 and W of 2.5 GeV2 and 2.0 GeV, respectively, while varying the four momentum transfer to the nucleon -t from 0.2 to 2.1 GeV2 . As -t is increased, the hadronic interaction scale is reduced independently of the observation scale of the virtual photon, providing valuable information about the hard- scattering process in general. The data was taken at JLab Hall C in 2003, as a part of the experiment E01-004, Fpi-2, using the High Momentum Spectrometer (HMS) and Short Orbit Spectrometer (SOS), and in this work, the results of the differential cross section analysis are presented and compared to prior data, as well as two theoretical models. Using these results over a wide -t range, the transition from hard to soft QCD is also studied. In addition, the p(e,e'K+)Lambda(Sigma0) reactions are also studied. Despite their importance in elucidating the reaction mechanism underlying strangeness production, we still do not have complete understanding of these reactions above the resonance region. The experiment, E12- 09-011, intends to perform, for the first time, a full Rosenbluth (L/T/LT/TT) separation of p(e,e'K+)Lambda(Sigma0) cross sections above the resonance region using the newly upgraded standard equipment, Super High Momentum Spectrometer (SHMS) at JLab Hall C. The separated data will allow us to better understand the Kaon production reaction mechanism and the hard-soft QCD transition in exclusive processes. The kinematic settings being studied in the experiment ranges from Q^2 of 0.4 to 5.5 GeV2, W of 2.3 to 3.1 GeV, and -t of 0.06 to 0.53 GeV2. Here, the results from some pre-experimental studies with regards to estimations of singles rates as well as real and accidental coincidence rates are presented, using two different models. The implications of these projections on the runplan for the experiment are also discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.027
GPT teacher head0.330
Teacher spread0.302 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2017
Admission routes1
Has abstractyes

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