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Towards a muon collider

2023· article· en· W4361238982 on OpenAlexaff
C. Accettura, Dean C. Adams, Rohit Agarwal, C. Ahdida, C. Aimè, David Amorim, Paolo Andreetto, Robert Appleby, A. Apresyan, A. Apyan, Sergey Arsenyev, Pouya Asadi, Aleksandr Azatov, J. J. Back, Lorenzo Balconi, L. Bandiera, Hutchcroft, D. E., N. Bartosik, E. Barzi, Fabian Batsch, M. Bauce, J. Scott Berg, A. Bersani, A. Bertarelli, A. Bertolin, Fulvio Boattini, Alex Bogacz, M. Bonesini, B. Bordini, Salvatore Bottaro, L. Bottura, A. Braghieri, Marco Breschi, Xavier Buffat, L. Buonincontri, Philip Burrows, Dario Buttazzo, B. Caiffi, M. Calviani, S. Calzaferri, Daniele Calzolari, Rodolfo Capdevilla, Fausto Casaburo, Luca Castelli, G. Cavoto, Francesco Giovanni Celiberto, L. Celona, A. Cerri, Gianmario Cesarini, Cari Cesarotti, Grigorios Chachamis, Antoine Chancé, Mauro Chiesa, A. Colaleo, F. Collamati, G. Collazuol, Nathaniel Craig, C. Curatolo, David Curtin, G. Da Molin, Magnus Dam, Heiko Damerau, Sridhara Dasu, Jorge de Blas, Stefania De Curtis, E. De Matteis, Stefania de Rosa, D. Denisov, Christopher Densham, Radovan Dermíšek, Luca Di Luzio, E. Di Meco, B. Di Micco, Keith R. Dienes, E. Diociaiuti, T. Dorigo, A. Dudarev, F. Errico, M. Fabbrichesi, S. Farinon, Jose Antonio Ferreira Somoza, F. Filthaut, D. Fiorina, Elena Fol, Matthew Forslund, Roberto Franceschini, Rui Franqueira Ximenes, Emidio Gabrielli, Francesco Garosi, L. Giambastiani, A. Gianelle, Dario Augusto Giove, Carlo Giraldin, Alfredo Glioti, M. Greco, Admir Greljo, Ramona Groeber, Christophe Grojean, Junhua Gu, Chengcheng Han, J. M. Hauptman, Keith Hermanek, M. Herndon, T. R. Holmes, Samuel Homiller, Guoyuan Huang, Sudip Jana, S. Jindariani, David Kelliher, Wolfgang Kilian, Antti Kolehmainen, P. Koppenburg, Nils Kreher, G. Krintiras, K. Krizka, Gordan Krnjaic, Benjamin T Kuchma, Nilanjana Kumar, Anton Lechner, Roberto Li Voti, R. Lipton, Shivani Lomte, K. Long, Jose Lorenzo Gomez, R. Losito, Ian Low, Qianshu Lu, D. Lucchesi, S. Machida, Fabio Maltoni, M. Mandurrino, B. Mansoulié, Luca Mantani, C. Marchand, S. Mariotto, S. Martin–Haugh, David Marzocca, Paola Mastrapasqua, G. S. Mauro, A. Mazzolari, Navin McGinnis, Patrick Meade, B. Mele, F. Meloni, C. Merlassino, E. Métral, Natalia Milas, N. Mokhov, Alessandro Montella, Tim Mulder, Federico Nardi, David Neuffer, Y. Onel, D. Orestano, D. Paesani, S. Pagan Griso, M. Palmer, Paolo Panci, Giuliano Panico, Rocco Paparella, Paride Paradisi, A. Passeri, A. Pellecchia, F. Piccinini, A. Portone, K. Potamianos, Marco Prioli, L. Quettier, E. Radicioni, R. Radogna, Riccardo Rattazzi, Diego Redigolo, Laura Reina, E. D. Resseguie, Jürgen Reuter, Pier Luigi Ribani, L. Ristori, Tania Robens, Werner Rodejohann, M. Romagnoni, K. Ronald, L. Rossi, Richard Ruíz, Farinaldo S. Queiroz, Filippo Sala, Jakub Šalko, P. Salvini, Ennio Salvioni, José Santiago, I. Sarra, Francisco Javier Saura Esteban, J. Schieck, Daniel Schulte, M. Selvaggi, Carmine Senatore, A. Şenol, V. Sharma, Vladimir Shiltsev, Zito, G, R. Simoniello, Kyriacos Skoufaris, M. Sorbi, S. Di Stefano, Anna Stamerra, S. Stapnes, G. H. Stark, M. Statera, Daniel Stolarski, Diktys Stratakis, Shufang Su, Olcyr Sumensari, X. Sun, Raman Sundrum, M. Swiatlowski, Alexei Sytov, Tim M. P. Tait, Jingyu Tang, Andrea Tesi, P. Testoni, Brooks Thomas, E. A. Thompson, Riccardo Torre, Sokratis Trifinopoulos, R. U. Valente, Alessandro Valenti, Ursula van Rienen, Arjan Verweij, Ludovico Vittorio, Liantao Wang, H. A. Weber, Richard Wu, Yongcheng Wu, Andrea Wulzer, A. Yamamoto, K. Yonehara, Angela Zaza, Xiaoran Zhao, A.V. Zlobin, D. Zuliani, José Zurita

Bibliographic record

VenueThe European Physical Journal C · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsCarleton UniversityTRIUMFUniversity of Toronto
FundersHigh Energy PhysicsBasic Energy SciencesAgencia Estatal de InvestigaciónFundação para a Ciência e a TecnologiaResearch Executive AgencyScience and Technology Facilities CouncilOffice of SciencePolska Akademia NaukGeneralitat ValencianaEnergy Frontier Research CentersCERNDeutsche ForschungsgemeinschaftNarodowe Centrum NaukiEuropean Regional Development FundU.S. Department of EnergyEuropean CommissionSun Yat-sen UniversityUniversity of OxfordComunidad de MadridSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungJunta de AndalucíaNational Science Foundation
KeywordsMuon colliderMuonParticle physicsColliderPhysicsNuclear physicsParticle accelerator

Abstract

fetched live from OpenAlex

Abstract A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score0.998

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)0.0000.003

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 head0.025
GPT teacher head0.266
Teacher spread0.241 · 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.

Study designOther design
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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