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Record W3096128731

A Measurement of the Proton's Weak Charge Using an Integration Cerenkov Detector System

2011· dissertation· en· W3096128731 on OpenAlexfundno aff
Peiqing Wang

Bibliographic record

VenueMspace (University of Manitoba) · 2011
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyNational Science Foundation
KeywordsDetectorPhysicsCharge (physics)ProtonNuclear physicsParticle physicsOptics
DOInot available

Abstract

fetched live from OpenAlex

The Q-weak experiment at Thomas Jefferson National Accelerator Facility (USA) will make a precision determination of the proton weak charge with approximately 4% combined statistical and systematic uncertainties via a measurement of the parity violating asymmetry in elastic electron-proton scattering at very low momentum transfer and forward angle. This will allow an extraction of the weak mixing angle at Q^2=0.026 (GeV/c)^2 to approximately 0.3%. The weak mixing angle is a fundamental parameter in the Standard Model of electroweak interactions. At the proposed accuracy, a measured deviation of this parameter from the predicted value would indicate new physics beyond what is currently described in the Standard Model. Without deviation from the predicted value, this measurement would place stringent limits on possible extensions to the Standard Model and constitute the most precise measurement of the proton's weak charge to date. The key experimental apparatus include a liquid hydrogen target, a toroidal magnetic spectrometer and a set of eight Cerenkov detectors. The Cerenkov detectors form the main detector system for the Q-weak experiment and are used to measure the parity violating asymmetry during the primary Q-weak production runs. The Cerenkov detectors form the main subject of this thesis. Following a brief introduction to the experiment, the design, development, construction, installation, and testing of this detector system will be discussed in detail. This is followed by a detailed discussion of detector diagnostic data analysis and the corresponding detector performance. The experiment has been successfully constructed and commissioned, and is currently taking data. The thesis will conclude with a discussion of the preliminary analysis of a small portion of the liquid hydrogen data.

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)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.238
Teacher spread0.197 · 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
GenreOther

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

Citations11
Published2011
Admission routes1
Has abstractyes

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