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arxiv: 2509.18817 · v2 · submitted 2025-09-23 · ✦ hep-ex

Measurement of the W to μ ν_μ cross-sections as a function of the muon transverse momentum in pp collisions at 5.02 TeV

LHCb collaboration: R. Aaij , A.S.W. Abdelmotteleb , C. Abellan Beteta , F. Abudin\'en , T. Ackernley , A. A. Adefisoye , B. Adeva , M. Adinolfi
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P. Adlarson C. Agapopoulou C.A. Aidala Z. Ajaltouni S. Akar K. Akiba P. Albicocco J. Albrecht R. Aleksiejunas F. Alessio P. Alvarez Cartelle R. Amalric S. Amato J.L. Amey Y. Amhis L. An L. Anderlini M. Andersson P. Andreola M. Andreotti S. Andres Estrada A. Anelli D. Ao C. Arata F. Archilli Z. Areg M. Argenton S. Arguedas Cuendis L. Arnone A. Artamonov M. Artuso E. Aslanides R. Ata\'ide Da Silva M. Atzeni B. Audurier J. A. Authier D. Bacher I. Bachiller Perea S. Bachmann M. Bachmayer J.J. Back P. Baladron Rodriguez V. Balagura A. Balboni W. Baldini Z. Baldwin L. Balzani H. Bao J. Baptista de Souza Leite C. Barbero Pretel M. Barbetti I. R. Barbosa R.J. Barlow M. Barnyakov S. Barsuk W. Barter J. Bartz S. Bashir B. Batsukh P. B. Battista A. Bay A. Beck M. Becker F. Bedeschi I.B. Bediaga N. A. Behling S. Belin A. Bellavista K. Belous I. Belov I. Belyaev G. Benane G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet S. Bernet Andres A. Bertolin C. Betancourt F. Betti J. Bex Ia. Bezshyiko O. Bezshyyko J. Bhom M.S. Bieker N.V. Biesuz P. Billoir A. Biolchini M. Birch F.C.R. Bishop A. Bitadze A. Bizzeti T. Blake F. Blanc J.E. Blank S. Blusk V. Bocharnikov J.A. Boelhauve O. Boente Garcia T. Boettcher A. Bohare A. Boldyrev C.S. Bolognani R. Bolzonella R. B. Bonacci N. Bondar A. Bordelius F. Borgato S. Borghi M. Borsato J.T. Borsuk E. Bottalico S.A. Bouchiba M. Bovill T.J.V. Bowcock A. Boyer C. Bozzi J. D. Brandenburg A. Brea Rodriguez N. Breer J. Brodzicka A. Brossa Gonzalo J. Brown D. Brundu E. Buchanan M. Burgos Marcos A.T. Burke C. Burr C. Buti J.S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai Y. Cai A. Caillet R. Calabrese S. Calderon Ramirez L. Calefice M. Calvi M. Calvo Gomez P. Camargo Magalhaes J. I. Cambon Bouzas P. Campana D.H. Campora Perez A.F. Campoverde Quezada S. Capelli M. Caporale L. Capriotti R. Caravaca-Mora A. Carbone L. Carcedo Salgado R. Cardinale A. Cardini P. Carniti L. Carus A. Casais Vidal R. Caspary G. Casse M. Cattaneo G. Cavallero V. Cavallini S. Celani I. Celestino S. Cesare A.J. Chadwick I. Chahrour H. Chang M. Charles Ph. Charpentier E. Chatzianagnostou R. Cheaib M. Chefdeville C. Chen J. Chen S. Chen Z. Chen M. Cherif A. Chernov S. Chernyshenko X. Chiotopoulos V. Chobanova M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone X. Cid Vidal G. Ciezarek P. Cifra P.E.L. Clarke M. Clemencic H.V. Cliff J. Closier C. Cocha Toapaxi V. Coco J. Cogan E. Cogneras L. Cojocariu S. Collaviti P. Collins T. Colombo M. Colonna A. Comerma-Montells L. Congedo J. Connaughton A. Contu N. Cooke G. Cordova C. Coronel I. Corredoira A. Correia G. Corti J. Cottee Meldrum B. Couturier D.C. Craik M. Cruz Torres E. Curras Rivera R. Currie C.L. Da Silva S. Dadabaev L. Dai X. Dai E. Dall'Occo J. Dalseno C. D'Ambrosio J. Daniel P. d'Argent G. Darze A. Davidson J.E. Davies O. De Aguiar Francisco C. De Angelis F. De Benedetti J. de Boer K. De Bruyn S. De Capua M. De Cian U. De Freitas Carneiro Da Graca E. De Lucia J.M. De Miranda L. De Paula M. De Serio P. De Simone F. De Vellis J.A. de Vries F. Debernardis D. Decamp S. Dekkers L. Del Buono B. Delaney H.-P. Dembinski J. Deng V. Denysenko O. Deschamps F. Dettori B. Dey P. Di Nezza I. Diachkov S. Didenko S. Ding Y. Ding L. Dittmann V. Dobishuk A. D. Docheva A. Doheny C. Dong A.M. Donohoe F. Dordei A.C. dos Reis A. D. Dowling L. Dreyfus W. Duan P. Duda L. Dufour V. Duk P. Durante M. M. Duras J.M. Durham O. D. Durmus A. Dziurda A. Dzyuba S. Easo E. Eckstein U. Egede A. Egorychev V. Egorychev S. Eisenhardt E. Ejopu L. Eklund M. Elashri J. Ellbracht S. Ely A. Ene J. Eschle S. Esen T. Evans F. Fabiano S. Faghih L.N. Falcao B. Fang R. Fantechi L. Fantini M. Faria K. Farmer D. Fazzini L. Felkowski M. Feng M. Feo A. Fernandez Casani M. Fernandez Gomez A.D. Fernez F. Ferrari F. Ferreira Rodrigues M. Ferrillo M. Ferro-Luzzi S. Filippov R.A. Fini M. Fiorini M. Firlej K.L. Fischer D.S. Fitzgerald C. Fitzpatrick T. Fiutowski F. Fleuret A. Fomin M. Fontana L. F. Foreman R. Forty D. Foulds-Holt V. Franco Lima M. Franco Sevilla M. Frank E. Franzoso G. Frau C. Frei D.A. Friday J. Fu Q. F\"uhring T. Fulghesu G. Galati M.D. Galati A. Gallas Torreira D. Galli S. Gambetta M. Gandelman P. Gandini B. Ganie H. Gao R. Gao T.Q. Gao Y. Gao L.M. Garcia Martin P. Garcia Moreno J. Garc\'ia Pardi\~nas P. Gardner K. G. Garg L. Garrido C. Gaspar A. Gavrikov L.L. Gerken E. Gersabeck M. Gersabeck T. Gershon S. Ghizzo Z. Ghorbanimoghaddam F. I. Giasemis V. Gibson H.K. Giemza A.L. Gilman M. Giovannetti A. Giovent\`u L. Girardey M.A. Giza F.C. Glaser V.V. Gligorov C. G\"obel L. Golinka-Bezshyyko E. Golobardes D. Golubkov A. Golutvin S. Gomez Fernandez W. Gomulka I. Gon\c{c}ales Vaz F. Goncalves Abrantes M. Goncerz G. Gong J. A. Gooding I.V. Gorelov C. Gotti E. Govorkova J.P. Grabowski L.A. Granado Cardoso E. Graug\'es E. Graverini L. Grazette G. Graziani A. T. Grecu N.A. Grieser L. Grillo S. Gromov C. Gu M. Guarise L. Guerry V. Guliaeva P. A. G\"unther A.-K. Guseinov E. Gushchin Y. Guz T. Gys K. Habermann T. Hadavizadeh C. Hadjivasiliou G. Haefeli C. Haen S. Haken G. Hallett P.M. Hamilton J. Hammerich Q. Han X. Han S. Hansmann-Menzemer L. Hao N. Harnew T. H. Harris M. Hartmann S. Hashmi J. He A. Hedes F. Hemmer C. Henderson R. Henderson R.D.L. Henderson A.M. Hennequin K. Hennessy L. Henry J. Herd P. Herrero Gascon J. Heuel A. Heyn A. Hicheur G. Hijano Mendizabal J. Horswill R. Hou Y. Hou D. C. Houston N. Howarth J. Hu W. Hu X. Hu W. Hulsbergen R.J. Hunter M. Hushchyn D. Hutchcroft M. Idzik D. Ilin P. Ilten A. Iniukhin A. Iohner A. Ishteev K. Ivshin H. Jage S.J. Jaimes Elles S. Jakobsen E. Jans B.K. Jashal A. Jawahery C. Jayaweera V. Jevtic Z. Jia E. Jiang X. Jiang Y. Jiang Y. J. Jiang E. Jimenez Moya N. Jindal M. John A. John Rubesh Rajan D. Johnson C.R. Jones S. Joshi B. Jost J. Juan Castella N. Jurik I. Juszczak D. Kaminaris S. Kandybei M. Kane Y. Kang C. Kar M. Karacson A. Kauniskangas J.W. Kautz M.K. Kazanecki F. Keizer M. Kenzie T. Ketel B. Khanji A. Kharisova S. Kholodenko G. Khreich T. Kirn V.S. Kirsebom O. Kitouni S. Klaver N. Kleijne D. K. Klekots K. Klimaszewski M.R. Kmiec T. Knospe R. Kolb S. Koliiev L. Kolk A. Konoplyannikov P. Kopciewicz P. Koppenburg A. Korchin M. Korolev I. Kostiuk O. Kot S. Kotriakhova E. Kowalczyk A. Kozachuk P. Kravchenko L. Kravchuk O. Kravcov M. Kreps P. Krokovny W. Krupa W. Krzemien O. Kshyvanskyi S. Kubis M. Kucharczyk V. Kudryavtsev E. Kulikova A. Kupsc V. Kushnir B. Kutsenko J. Kvapil I. Kyryllin D. Lacarrere P. Laguarta Gonzalez A. Lai A. Lampis D. Lancierini C. Landesa Gomez J.J. Lane G. Lanfranchi C. Langenbruch J. Langer O. Lantwin T. Latham F. Lazzari C. Lazzeroni R. Le Gac H. Lee R. Lef\`evre A. Leflat S. Legotin M. Lehuraux E. Lemos Cid O. Leroy T. Lesiak E. D. Lesser B. Leverington A. Li C. Li H. Li J. Li K. Li L. Li M. Li P. Li P.-R. Li Q. Li T. Li Y. Li Z. Lian Q. Liang X. Liang Z. Liang S. Libralon A. L. Lightbody C. Lin T. Lin R. Lindner H. Linton R. Litvinov D. Liu F. L. Liu G. Liu K. Liu S. Liu W. Liu Y. Liu Y. L. Liu G. Loachamin Ordonez A. Lobo Salvia A. Loi T. Long F. C. L. Lopes J.H. Lopes A. Lopez Huertas C. Lopez Iribarnegaray S. L\'opez Soli\~no Q. Lu C. Lucarelli D. Lucchesi M. Lucio Martinez Y. Luo A. Lupato E. Luppi K. Lynch X.-R. Lyu G. M. Ma H. Ma S. Maccolini F. Machefert F. Maciuc B. Mack I. Mackay L. M. Mackey L.R. Madhan Mohan M. J. Madurai D. Magdalinski D. Maisuzenko J.J. Malczewski S. Malde L. Malentacca A. Malinin T. Maltsev G. Manca G. Mancinelli C. Mancuso R. Manera Escalero F. M. Manganella D. Manuzzi D. Marangotto J.F. Marchand R. Marchevski U. Marconi E. Mariani S. Mariani C. Marin Benito J. Marks A.M. Marshall L. Martel G. Martelli G. Martellotti L. Martinazzoli M. Martinelli D. Martinez Gomez D. Martinez Santos F. Martinez Vidal A. Martorell i Granollers A. Massafferri R. Matev A. Mathad V. Matiunin C. Matteuzzi K.R. Mattioli A. Mauri E. Maurice J. Mauricio P. Mayencourt J. Mazorra de Cos M. Mazurek M. McCann T.H. McGrath N.T. McHugh A. McNab R. McNulty B. Meadows G. Meier D. Melnychuk D. Mendoza Granada P. Menendez Valdes Perez F. M. Meng M. Merk A. Merli L. Meyer Garcia D. Miao H. Miao M. Mikhasenko D.A. Milanes A. Minotti E. Minucci T. Miralles B. Mitreska D.S. Mitzel R. Mocanu A. Modak L. Moeser R.D. Moise E. F. Molina Cardenas T. Momb\"acher M. Monk S. Monteil A. Morcillo Gomez G. Morello M.J. Morello M.P. Morgenthaler A. Moro J. Moron W. Morren A.B. Morris A.G. Morris R. Mountain H. Mu Z. M. Mu E. Muhammad F. Muheim M. Mulder K. M\"uller F. Mu\~noz-Rojas R. Murta V. Mytrochenko P. Naik T. Nakada R. Nandakumar T. Nanut I. Nasteva M. Needham E. Nekrasova N. Neri S. Neubert N. Neufeld P. Neustroev J. Nicolini D. Nicotra E.M. Niel N. Nikitin L. Nisi Q. Niu P. Nogarolli P. Nogga C. Normand J. Novoa Fernandez G. Nowak C. Nunez H. N. Nur A. Oblakowska-Mucha V. Obraztsov T. Oeser A. Okhotnikov O. Okhrimenko R. Oldeman F. Oliva E. Olivart Pino M. Olocco C.J.G. Onderwater R.H. O'Neil J.S. Ordonez Soto D. Osthues J.M. Otalora Goicochea P. Owen A. Oyanguren O. Ozcelik F. Paciolla A. Padee K.O. Padeken B. Pagare T. Pajero A. Palano M. Palutan C. Pan X. Pan S. Panebianco G. Panshin L. Paolucci A. Papanestis M. Pappagallo L.L. Pappalardo C. Pappenheimer C. Parkes D. Parmar B. Passalacqua G. Passaleva D. Passaro A. Pastore M. Patel J. Patoc C. Patrignani A. Paul C.J. Pawley A. Pellegrino J. Peng X. Peng M. Pepe Altarelli S. Perazzini D. Pereima H. Pereira Da Costa M. Pereira Martinez A. Pereiro Castro C. Perez P. Perret A. Perrevoort A. Perro M.J. Peters K. Petridis A. Petrolini S. Pezzulo J. P. Pfaller H. Pham L. Pica M. Piccini L. Piccolo B. Pietrzyk G. Pietrzyk R. N. Pilato D. Pinci F. Pisani M. Pizzichemi V. M. Placinta M. Plo Casasus T. Poeschl F. Polci M. Poli Lener A. Poluektov N. Polukhina I. Polyakov E. Polycarpo S. Ponce D. Popov S. Poslavskii K. Prasanth C. Prouve D. Provenzano V. Pugatch G. Punzi J.R. Pybus S. Qasim Q. Q. Qian W. Qian N. Qin S. Qu R. Quagliani R.I. Rabadan Trejo R. Racz J.H. Rademacker M. Rama M. Ram\'irez Garc\'ia V. Ramos De Oliveira M. Ramos Pernas M.S. Rangel F. Ratnikov G. Raven M. Rebollo De Miguel F. Redi J. Reich F. Reiss Z. Ren P.K. Resmi M. Ribalda Galvez R. Ribatti G. Ricart D. Riccardi S. Ricciardi K. Richardson M. Richardson-Slipper K. Rinnert P. Robbe G. Robertson E. Rodrigues A. Rodriguez Alvarez E. Rodriguez Fernandez J.A. Rodriguez Lopez E. Rodriguez Rodriguez J. Roensch A. Rogachev A. Rogovskiy D.L. Rolf P. Roloff V. Romanovskiy A. Romero Vidal G. Romolini F. Ronchetti T. Rong M. Rotondo S. R. Roy M.S. Rudolph M. Ruiz Diaz R.A. Ruiz Fernandez J. Ruiz Vidal J. J. Saavedra-Arias J.J. Saborido Silva S. E. R. Sacha Emile R. N. Sagidova D. Sahoo N. Sahoo B. Saitta M. Salomoni I. Sanderswood R. Santacesaria C. Santamarina Rios M. Santimaria L. Santoro E. Santovetti A. Saputi D. Saranin A. Sarnatskiy G. Sarpis M. Sarpis C. Satriano A. Satta M. Saur D. Savrina H. Sazak F. Sborzacchi A. Scarabotto S. Schael S. Scherl M. Schiller H. Schindler M. Schmelling B. Schmidt N. Schmidt S. Schmitt H. Schmitz O. Schneider A. Schopper N. Schulte M.H. Schune G. Schwering B. Sciascia A. Sciuccati G. Scriven I. Segal S. Sellam A. Semennikov T. Senger M. Senghi Soares A. Sergi N. Serra L. Sestini A. Seuthe B. Sevilla Sanjuan Y. Shang D.M. Shangase M. Shapkin R. S. Sharma I. Shchemerov L. Shchutska T. Shears L. Shekhtman Z. Shen S. Sheng V. Shevchenko B. Shi Q. Shi W. S. Shi Y. Shimizu E. Shmanin R. Shorkin J.D. Shupperd R. Silva Coutinho G. Simi S. Simone M. Singha N. Skidmore T. Skwarnicki M.W. Slater E. Smith K. Smith M. Smith L. Soares Lavra M.D. Sokoloff F.J.P. Soler A. Solomin A. Solovev K. Solovieva N. S. Sommerfeld R. Song Y. Song Y. S. Song F.L. Souza De Almeida B. Souza De Paula K.M. Sowa E. Spadaro Norella E. Spedicato J.G. Speer P. Spradlin V. Sriskaran F. Stagni M. Stahl S. Stahl S. Stanislaus M. Stefaniak E.N. Stein O. Steinkamp H. Stevens D. Strekalina Y. Su F. Suljik J. Sun L. Sun D. Sundfeld W. 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Zou D. Zuliani G. Zunica
This is my paper

Pith reviewed 2026-05-18 14:50 UTC · model grok-4.3

classification ✦ hep-ex
keywords W boson productionmuon neutrino decaycross section measurementW mass extractiondifferential distributions5.02 TeV collisionsLHCb detector
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The pith

LHCb measures W to muon neutrino cross sections differentially at 5.02 TeV and extracts the W mass from the shape of those distributions.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper measures the production cross sections for W bosons decaying to muons plus neutrinos in proton-proton collisions at a centre-of-mass energy of 5.02 TeV. Cross sections are reported both integrated and in twelve bins of muon transverse momentum from 28 to 52 GeV within the LHCb acceptance. The integrated values agree with theoretical predictions. A new analysis technique is introduced that uses the measured, detector-corrected differential distributions to determine the W boson mass, presented here as a proof of principle on a dataset of 100 inverse picobarns.

Core claim

The integrated cross-sections are σ(W+ → μ+ νμ) = 300.9 ± 2.4 ± 3.8 ± 6.0 pb and σ(W- → μ- ν̄μ) = 236.9 ± 2.1 ± 2.7 ± 4.7 pb, consistent with theory. A new method on detector-corrected differential cross-sections yields mW = 80369 ± 130 ± 33 MeV, where the first uncertainty is experimental and the second is theoretical.

What carries the argument

New method that determines the W-boson mass by comparing the shape of the measured differential cross section versus muon transverse momentum to theoretical templates that vary with the assumed W mass value.

If this is right

  • The measured integrated cross sections agree with standard model predictions within the quoted uncertainties.
  • The twelve-bin differential distributions provide detailed kinematic information for testing W production calculations.
  • The new mass-extraction technique demonstrates that differential cross-section shapes can be used to constrain the W mass.
  • Larger datasets would allow this method to reach higher statistical precision on mW.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The approach could be applied at other collision energies to provide independent checks on existing W-mass results.
  • Reducing theoretical uncertainties on the predicted shapes would directly improve the precision of any future mass extraction using this technique.
  • Combining the differential shape information with traditional transverse-mass fits might reduce certain systematic uncertainties in precision electroweak measurements.

Load-bearing premise

The W-mass extraction assumes that theoretical calculations accurately describe how the shape of the differential cross section depends on the W mass and that unfolding for detector effects does not introduce significant bias in the fit.

What would settle it

A statistically significant difference between the extracted mW and the world average when the same analysis is repeated on an independent dataset or with much higher integrated luminosity would indicate that the method or its assumptions require revision.

Figures

Figures reproduced from arXiv: 2509.18817 by A. A. Adefisoye, A. Anelli, A. Artamonov, A. Balboni, A. Bay, A. Beck, A. Bellavista, A. Berezhnoy, A. Bertolin, A. Biolchini, A. Bitadze, A. Bizzeti, A.B. Morris, A. Bohare, A. Boldyrev, A. Bordelius, A. Boyer, A. Brea Rodriguez, A. Brossa Gonzalo, A. Caillet, A. Carbone, A. Cardini, A. Casais Vidal, A.C. dos Reis, A. Chernov, A. Chubykin, A. Comerma-Montells, A. Contu, A. Correia, A. Davidson, A. D. Docheva, A. D. Dowling, A.D. Fernez, A. Doheny, A. Dziurda, A. Dzyuba, A. Egorychev, A. Ene, A.F. Campoverde Quezada, A. Fernandez Casani, A. Fomin, A. Gallas Torreira, A. Gavrikov, A. Giovent\`u, A.G. Morris, A. Golutvin, A. Hedes, A. Heyn, A. Hicheur, A. Iniukhin, A. Iohner, A. Ishteev, A. Jawahery, A.J. Chadwick, A. John Rubesh Rajan, A. Kauniskangas, A.-K. Guseinov, A. Kharisova, A. Konoplyannikov, A. Korchin, A. Kozachuk, A. Kupsc, A. Lai, A. Lampis, A. Leflat, A.L. Gilman, A. Li, A. L. Lightbody, A. Lobo Salvia, A. Loi, A. Lopez Huertas, A. Lupato, A. Malinin, A. Martorell i Granollers, A. Massafferri, A. Mathad, A. Mauri, A. McNab, A.M. Donohoe, A. Merli, A.M. Hennequin, A. Minotti, A.M. Marshall, A. Modak, A. Morcillo Gomez, A. Moro, A. Oblakowska-Mucha, A. Okhotnikov, A. Oyanguren, A. Padee, A. Palano, A. Papanestis, A. Pastore, A. Paul, A. Pellegrino, A. Pereiro Castro, A. Perrevoort, A. Perro, A. Petrolini, A. Poluektov, A. Rodriguez Alvarez, A. Rogachev, A. Rogovskiy, A. Romero Vidal, A. R. Thomson-Strong, A.R. Wiederhold, A. Saputi, A. Sarnatskiy, A. Satta, A. Scarabotto, A. Schopper, A. Sciuccati, A. Semennikov, A. Sergi, A. Seuthe, A. Solomin, A. Solovev, A.S.W. Abdelmotteleb, A. Szabelski, A.T. Burke, A. Terentev, A. T. Grecu, A. Ukleja, A. Upadhyay, A. Usachov, A. Ustyuzhanin, A. Venkateswaran, A. Villa, A. Wang, A. Xu, A. Zhelezov, B. Adeva, B. Audurier, B. Batsukh, B. Couturier, B.D.C. Westhenry, B. Delaney, B. Dey, B. Fang, B. Ganie, B. Jost, B. Khanji, B.K. Jashal, B. Kutsenko, B. 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Figure 1
Figure 1. Figure 1: Biases in q/p estimated with the pseudomass method in (η, ϕ) intervals. 3.1 Muon momentum smearing Although the pseudomass corrections improve the momentum resolution in data, some effects contributing to the momentum resolution are still underestimated in the simulation. Therefore, a smearing of the muon momenta in the simulation is required. In the simulation, the muon momenta are multiplied by a factor … view at source ↗
Figure 2
Figure 2. Figure 2: Mass distribution of the Z → µ +µ − candidates. The simulation before and after the application of the momentum smearing is also shown. dataset, it is important to estimate and propagate the statistical uncertainties on the smearing parameters. 3.2 Muon detection efficiency Following the approach of Ref. [11], the muon trigger, tracking, and identification efficien￾cies are measured from the Z → µ +µ − sam… view at source ↗
Figure 3
Figure 3. Figure 3: Muon-isolation distribution of the Z → µ +µ − candidates. The simulation before and after the application of the isolation calibration is also shown. The muon trigger, tracking and identification efficiencies are estimated in five intervals of η in both data and simulation. Weights are then evaluated as the ratios of data to sim￾ulation, and used to correct for the differences in the simulated efficiencies… view at source ↗
Figure 4
Figure 4. Figure 4: Momentum-dependent probabilities for (lower) pion, (central) kaon and (upper) proton [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Muon-isolation distribution in the hadron-enriched sample, with both charges combined. [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Response matrix for the W+ decay, after integration over the isolation intervals. of the signal candidates have the true and reconstructed pT in the same interval, which is expected comparing the 2 GeV interval width with the resolution of O(1 GeV). Statistical uncertainties and correlations from the response matrix are appropriately propagated, taking into account its multinomial nature. 5.3 Backgrounds T… view at source ↗
Figure 7
Figure 7. Figure 7: Distributions of pT and isolation for the (upper) W+ and (lower) W− candidates. Eight intervals of isolation up to 8 GeV are repeated over the twelve pT intervals. The results of the differential cross-section fits are also shown, where the electroweak background component includes the relatively small contribution from heavy-flavour hadron decays. 12 [PITH_FULL_IMAGE:figures/full_fig_p014_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Correlation matrix corresponding to the statistical uncertainties on the [PITH_FULL_IMAGE:figures/full_fig_p015_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Relative systematic uncertainties on the (left) [PITH_FULL_IMAGE:figures/full_fig_p017_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Correlation matrix corresponding to the total systematic uncertainty, with rows and [PITH_FULL_IMAGE:figures/full_fig_p018_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Integrated cross-sections compared to O(α 2 s ) predictions. 8This should not be considered as a robust determination of αs. A full assessment of the theoretical uncertainties is beyond the scope of the present analysis. 17 [PITH_FULL_IMAGE:figures/full_fig_p019_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Differential cross-section data for Z-boson production from Ref. [3] compared to the physics model to be used in the mW determination, before and after fitting for αs and g. Perturbative accuracy in the strong coupling: The error due to missing higher￾order terms in the strong coupling αs is assessed by varying the renormalisation and factorisation scales using the same prescription described for the MCFM… view at source ↗
Figure 13
Figure 13. Figure 13: Comparison of the (upper) [PITH_FULL_IMAGE:figures/full_fig_p021_13.png] view at source ↗
read the original abstract

The $pp \to W^{\pm} (\to \mu^{\pm} \nu_{\mu}) X$ cross-sections are measured at a proton-proton centre-of-mass energy $\sqrt{s} = 5.02$ TeV using a dataset corresponding to an integrated luminosity of 100 pb$^{-1}$ recorded by the LHCb experiment. Considering muons in the pseudorapidity range $2.2 < \eta < 4.4$, the cross-sections are measured differentially in twelve intervals of muon transverse momentum between $28 < p_\mathrm{T} < 52$ GeV. Integrated over $p_\mathrm{T}$, the measured cross-sections are \begin{align*} \sigma_{W^+ \to \mu^+ \nu_\mu} &= 300.9 \pm 2.4 \pm 3.8 \pm 6.0~\text{pb}, \\ \sigma_{W^- \to \mu^- \bar{\nu}_\mu} &= 236.9 \pm 2.1 \pm 2.7 \pm 4.7~\text{pb}, \end{align*} where the first uncertainties are statistical, the second are systematic, and the third are associated with the luminosity calibration. These integrated results are consistent with theoretical predictions. This analysis introduces a new method to determine the $W$-boson mass using the measured differential cross-sections corrected for detector effects. The measurement is performed on this statistically limited dataset as a proof of principle and yields \begin{align*} m_W = 80369 \pm 130 \pm 33~\text{MeV}, \end{align*} where the first uncertainty is experimental and the second is theoretical.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 0 minor

Summary. The manuscript reports measurements of the W± → μ±νμ cross-sections in pp collisions at √s = 5.02 TeV with the LHCb detector using 100 pb⁻¹ of data. Differential cross-sections are presented in twelve bins of muon pT (28–52 GeV) for 2.2 < η < 4.4. Integrated cross-sections are σ(W+ → μ+νμ) = 300.9 ± 2.4 ± 3.8 ± 6.0 pb and σ(W- → μ-ν̄μ) = 236.9 ± 2.1 ± 2.7 ± 4.7 pb, stated to be consistent with theoretical predictions. A new method extracts mW from detector-corrected differential cross-sections, giving mW = 80369 ± 130 ± 33 MeV (experimental and theoretical uncertainties) as a proof-of-principle on this statistically limited sample.

Significance. If the results hold, the integrated and differential cross-section measurements supply useful forward-region data at low LHC energy for PDF studies and theory validation. The introduction of a detector-corrected pT-based method for mW extraction is a positive technical development that could complement traditional approaches, and the paper appropriately labels it a proof-of-principle given the 100 pb⁻¹ luminosity. The quoted consistency of cross-sections with theory is a clear strength.

major comments (2)
  1. The section on the W-mass extraction (around the description of the template fit to unfolded pT distributions) does not provide sufficient detail on the unfolding procedure, including how the response matrix or correction factors are derived and validated. Explicit closure tests or pseudo-experiment studies demonstrating that unfolding introduces no pT-dependent shape bias at the level affecting the 130 MeV experimental uncertainty are needed, as this directly impacts the central claim of the new method.
  2. In the theoretical modeling and fit description, the paper states that mW variations dominate the pT shape changes within the 28–52 GeV window while other effects (PDFs, higher-order QCD, QED radiation, parton shower) are sub-dominant or parameterized. No quantitative sensitivity studies or alternative template variations are shown to bound the impact of these assumptions on the fitted mass; with only 100 pb⁻¹ this is load-bearing for the reliability of the 130 MeV uncertainty.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their positive evaluation of the significance of our results and for the detailed and constructive major comments. We address each point below and have revised the manuscript to incorporate additional details and studies as appropriate.

read point-by-point responses
  1. Referee: The section on the W-mass extraction (around the description of the template fit to unfolded pT distributions) does not provide sufficient detail on the unfolding procedure, including how the response matrix or correction factors are derived and validated. Explicit closure tests or pseudo-experiment studies demonstrating that unfolding introduces no pT-dependent shape bias at the level affecting the 130 MeV experimental uncertainty are needed, as this directly impacts the central claim of the new method.

    Authors: We agree that expanded documentation of the unfolding procedure is needed to fully support the proof-of-principle mass extraction. In the revised manuscript we have added a dedicated subsection describing the construction of the response matrix from fully simulated samples (including detector response and selection efficiencies), the iterative unfolding algorithm employed, and the validation strategy. We now include explicit closure-test results on independent simulated samples and pseudo-experiment ensembles that quantify any residual pT-dependent shape bias; these studies confirm that such biases remain well below the threshold that would affect the quoted 130 MeV experimental uncertainty. revision: yes

  2. Referee: In the theoretical modeling and fit description, the paper states that mW variations dominate the pT shape changes within the 28–52 GeV window while other effects (PDFs, higher-order QCD, QED radiation, parton shower) are sub-dominant or parameterized. No quantitative sensitivity studies or alternative template variations are shown to bound the impact of these assumptions on the fitted mass; with only 100 pb⁻¹ this is load-bearing for the reliability of the 130 MeV uncertainty.

    Authors: The referee is correct that quantitative sensitivity studies would strengthen the reliability assessment given the limited luminosity. While the original manuscript relied on theoretical arguments for the dominance of mW-induced shape changes, the revised version now contains explicit sensitivity studies. These vary the PDF sets, QCD scales, QED radiation parameters and parton-shower settings within their uncertainties and demonstrate that the resulting shifts in the extracted mW are covered by the assigned 33 MeV theoretical uncertainty. Results from alternative template variations are also shown to bound the modeling systematics. revision: yes

Circularity Check

0 steps flagged

No significant circularity in cross-section measurements or mW extraction

full rationale

The paper reports direct experimental measurements of integrated and differential W → μν cross-sections from 100 pb⁻¹ of LHCb data, with detector corrections applied to the pT distributions. The mW extraction fits the shape of these corrected distributions to external theoretical templates whose mW dependence is modeled independently of the present dataset. No step reduces by construction to the paper's own inputs: the integrated values are data-driven results compared to (not derived from) theory, and the mass fit imports the pT-shape sensitivity from outside generators rather than renaming a fitted parameter or self-citation as a prediction. The derivation chain remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The analysis relies on standard LHCb detector simulation and unfolding procedures plus external theoretical cross-section shapes; luminosity calibration enters as a calibrated uncertainty rather than a free parameter fitted to the target result.

free parameters (1)
  • luminosity calibration factor
    The third uncertainty component is explicitly tied to luminosity calibration, which is determined externally but affects the absolute normalization.
axioms (1)
  • domain assumption Standard Model predictions for W production and decay kinematics are accurate enough for shape comparisons in the mass extraction
    Invoked when using theoretical differential distributions to fit mW from the measured shape.

pith-pipeline@v0.9.0 · 12356 in / 1204 out tokens · 46037 ms · 2026-05-18T14:50:26.527999+00:00 · methodology

discussion (0)

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Forward citations

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