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Record W4387560257 · doi:10.48550/arxiv.2310.05669

Transverse Emittance Reduction in Muon Beams by Ionization Cooling

2023· preprint· en· W4387560257 on OpenAlexaff
MICE Collaboration, M. Bogomilov, R. Tsenov, G. Vankova-Kirilova, Y. P. Song, Jingyu Tang, Z. H. Li, R. Bertoni, M. Bonesini, F. Chignoli, R. Mazza, A. de Bari, D. Orestano, L. Tortora, Y. Kuno, H. Sakamoto, Akira Sato, S. Ishimoto, М. Chung, C. K. Sung, F. Filthaut, M. Fedorov, D. Joković, D. Maletić, Mihailo Savić, N. Jovančević, Jovana Nikolov, M. Vretenar, S. Ramberger, R. Asfandiyarov, A. Blondel, F. Drielsma, Y. Karadzhov, S. B. Boyd, J. R. Greis, T. Lord, C. Pidcott, Ian Taylor, G. Charnley, N. Collomb, Keith Dumbell, Alan Gallagher, A. Grant, S. Griffiths, T. Hartnett, B. Martlew, A. Moss, A. Muir, I. Mullacrane, A. Oates, P. Owens, G. Stokes, P. A. Warburton, Christopher J. White, D. Adams, V. Bayliss, J. Boehm, T. Bradshaw, C. Brown, M. Courthold, J. Govans, M. Hills, J.-B. Lagrange, C. Macwaters, A. Nichols, R. Preece, S. Ricciardi, Chris Rogers, Timothy Stanley, J. Tarrant, M. A. H. Tucker, S. Watson, A. Wilson, R. Bayes, J. C. Nugent, G. T. Chatzitheodoridis, Alexander Dick, K. Ronald, C. G. Whyte, A. R. Young, R. Gamet, P. Cooke, V. Blackmore, D. Colling, A. Dobbs, P.J. Dornan, P. Franchini, C. Hunt, Paul Jurj, A. Kurup, K. Long, J. Martyniak, S. Middleton, J. Pasternak, M. A. Uchida, J.H. Cobb, Campbell Booth, P. Hodgson, J. Langlands, Edward B. Overton, V. Pec, Peter J. Smith, S. Wilbur, M. Ellis, R. B. S. Gardener, P. Kyberd, JJ Nebrensky, A. DeMello, S.A. Gourlay, Andrew Lambert, D. Li, Tianhuan Luo, S. Prestemon, Steve Virostek, M. Palmer, Holger Witte, D. Adey, A. Bross, D. Bowring, A. Liu, David Neuffer, M. Popovic, P. Rubinov, Ben Freemire, P. Hanlet, Daniel M. Kaplan, T. Mohayai, D. Rajaram, P. Snopok, Y. Torun, L. Cremaldi, David Sanders, L. Coney, G. Hanson, C. Heidt

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldEngineering
TopicMuon and positron interactions and applications
Canadian institutionsLaurentian University
FundersHigh Energy PhysicsJapan Society for the Promotion of ScienceMinistarstvo Prosvete, Nauke i Tehnološkog RazvojaChinese Academy of SciencesNational Research FoundationScience and Technology Facilities CouncilIstituto Nazionale di Fisica NucleareInstitute of High Energy PhysicsU.S. Department of EnergyEuropean CommissionNational Research Foundation of KoreaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsMuonPhysicsThermal emittanceNuclear physicsMuon colliderBeam (structure)Phase spaceProtonTransverse planeIonizationNeutrino FactoryNeutrinoAtomic physicsIonParticle acceleratorNeutrino oscillationOptics

Abstract

fetched live from OpenAlex

Accelerated muon beams have been considered for next-generation studies of high-energy lepton-antilepton collisions and neutrino oscillations. However, high-brightness muon beams have not yet been produced. The main challenge for muon acceleration and storage stems from the large phase-space volume occupied by the beam, derived from the muon production mechanism through the decay of pions from proton collisions. Ionization cooling is the technique proposed to decrease the muon beam phase-space volume. Here we demonstrate a clear signal of ionization cooling through the observation of transverse emittance reduction in beams that traverse lithium hydride or liquid hydrogen absorbers in the Muon Ionization Cooling Experiment (MICE). The measurement is well reproduced by the simulation of the experiment and the theoretical model. The results shown here represent a substantial advance towards the realization of muon-based facilities that could operate at the energy and intensity frontiers.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.903

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 head0.046
GPT teacher head0.184
Teacher spread0.139 · 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 designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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