| Title: |
Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment |
| Authors: |
Acero, MA; Acharya, B; Adamson, P; Aliaga, L; Anfimov, N; Antoshkin, A; Arrieta-Diaz, E; Asquith, L; Aurisano, A; Back, A; Backhouse, C; Baird, M; Balashov, N; Baldi, P; Bambah, BA; Bashar, S; Bat, A; Bays, K; Bernstein, R; Bhatnagar, V; Bhattarai, D; Bhuyan, B; Bian, J; Booth, AC; Bowles, R; Brahma, B; Bromberg, C; Buchanan, N; Butkevich, A; Calvez, S; Carroll, TJ; Catano-Mur, E; Chatla, A; Chirco, R; Choudhary, BC; Choudhary, S; Christensen, A; Coan, TE; Colo, M; Cremonesi, L; Davies, GS; Derwent, PF; Ding, P; Djurcic, Z; Dolce, M; Doyle, D; Dueñas Tonguino, D; Dukes, EC; Dye, A; Ehrlich, R; Elkins, M; Ewart, E; Feldman, GJ; Filip, P; Franc, J; Frank, MJ; Gallagher, HR; Gandrajula, R; Gao, F; Giri, A; Gomes, RA; Goodman, MC; Grichine, V; Groh, M; Group, R; Guo, B; Habig, A; Hakl, F; Hall, A; Hartnell, J; Hatcher, R; Hausner, H; He, M; Heller, K; Hewes, V; Himmel, A; Jargowsky, B; Jarosz, J; Jediny, F; Johnson, C; Judah, M; Kakorin, I; Kaplan, DM; Kalitkina, A; Kleykamp, J; Klimov, O; Koerner, LW; Kolupaeva, L; Kotelnikov, S; Kralik, R; Kullenberg, C; Kubu, M; Kumar, A; Kuruppu, CD; Kus, V; Lackey, T; Lang, K; Lasorak, P; Lesmeister, J; Lin, S; Lister, A; Liu, J; Lokajicek, M; Lopez, JMC; Mahji, R; Magill, S; Manrique Plata, M; Mann, WA; Manoharan, MT; Marshak, ML; Martinez-Casales, M; Matveev, V; Mayes, B; Mehta, B; Messier, MD; Meyer, H; Miao, T; Mikola, V; Miller, WH; Mishra, S; Mishra, SR; Mislivec, A; Mohanta, R; Moren, A; Morozova, A; Mu, W; Mualem, L; Muether, M; Mulder, K; Naples, D; Nath, A; Nayak, N; Nelleri, S; Nelson, JK; Nichol, R; Niner, E; Norman, A; Norrick, A; Nosek, T; Oh, H; Olshevskiy, A; Olson, T; Ott, J; Pal, A; Paley, J; Panda, L; Patterson, RB; Pawloski, G; Pershey, D; Petrova, O; Petti, R; Phan, DD; Plunkett, RK; Pobedimov, A; Porter, JCC; Rafique, A; Prais, LR; Raj, V; Rajaoalisoa, M; Ramson, B; Rebel, B; Rojas, P; Roy, P; Ryabov, V; Samoylov, MC; Sanchez, O; Sánchez Falero, S; Shanahan, P; Sharma, P; Shukla, S; Sheshukov, A; Singh, I; Singh, P; Singh, V; Smith, E; Smolik, J; Snopok, P; Solomey, N; Sousa, A; Soustruznik, K; Strait, M; Suter, L; Sutton, A; Swain, S; Sweeney, C; Sztuc, A; Tapia Oregui, B; Tas, P; Temizel, BN; Thakore, T; Thayyullathil, RB; Thomas, J; Tiras, E; Tripathi, J; Trokan-Tenorio, J; Torun, Y; Urheim, J; Vahle, P; Vallari, Z; Vasel, J; Vrba, T; Wallbank, M; Warburton, TK; Wetstein, M; Whittington, D; Wickremasinghe, DA; Wieber, T; Wolcott, J; Wrobel, M; Wu, W; Xiao, Y; Yaeggy, B; Yallappa Dombara, A; Yankelevich, A; Yonehara, K; Yu, S; Yu, Y; Zadorozhnyy, S; Zalesak, J; Zhang, Y; Zwaska, R; The NOvA collaboration, . |
| Source: |
Journal of Instrumentation , 20 , Article T02001. (2025) |
| Publisher Information: |
IOP Publishing Ltd |
| Publication Year: |
2025 |
| Collection: |
University College London: UCL Discovery |
| Subject Terms: |
Science & Technology; Technology; Instruments & Instrumentation; Analysis and statistical methods; Computing (architecture farms; GRID for recording storage; archiving; and distribution of data); SYSTEMATIC UNCERTAINTIES |
| Description: |
Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confidence intervals on model parameters, but it only applies under certain conditions. These conditions, such as nested hypotheses and unbounded parameters, are often violated in neutrino oscillation measurements and other experimental scenarios. Monte Carlo methods can address these issues, albeit at increased computational cost. In the presence of nuisance parameters, however, the best way to implement a Monte Carlo method is ambiguous. This paper documents the method selected by the NOvA experiment, the profile construction. It presents the toy studies that informed the choice of method, details of its implementation, and tests performed to validate it. It also includes some practical considerations which may be of use to others choosing to use the profile construction. |
| Document Type: |
article in journal/newspaper |
| File Description: |
text |
| Language: |
English |
| Relation: |
https://discovery.ucl.ac.uk/id/eprint/10220794/1/Monte%20Carlo%20method%20for%20constructing%20confidence%20intervals%20AAM.pdf; https://discovery.ucl.ac.uk/id/eprint/10220794/ |
| Availability: |
https://discovery.ucl.ac.uk/id/eprint/10220794/1/Monte%20Carlo%20method%20for%20constructing%20confidence%20intervals%20AAM.pdf; https://discovery.ucl.ac.uk/id/eprint/10220794/ |
| Rights: |
open |
| Accession Number: |
edsbas.BA352C15 |
| Database: |
BASE |