Globalisation: The physics landscape today

Journal of Physics: Conference Series IOP Publishing 2877:1 (2024) 012019

Abstract:

This paper discusses how physics has become globalised in the context of the Oxford Department of Physics and its permanent academic staff over the period from 1987 to 2017. Modern émigrés move to new institutions for scientific opportunities and a physicist will typically work in several over the course of their career.

Prospects for γ-ray observations of the Perseus galaxy cluster with the Cherenkov Telescope Array

Journal of Cosmology and Astroparticle Physics IOP Publishing 2024:10 (2024) 004

Authors:

K Abe, S Abe, F Acero, A Acharyya, R Adam, A Aguasca-Cabot, I Agudo, A Aguirre-Santaella, J Alfaro, R Alfaro, N Alvarez-Crespo, R Alves Batista, J-P Amans, E Amato, EO Angüner, LA Antonelli, C Aramo, M Araya, C Arcaro, L Arrabito, K Asano, Y Ascasíbar, J Aschersleben, H Ashkar

Abstract:

Galaxy clusters are expected to be both dark matter (DM) reservoirs and storage rooms for the cosmic-ray protons (CRp) that accumulate along the cluster's formation history. Accordingly, they are excellent targets to search for signals of DM annihilation and decay at γ-ray energies and are predicted to be sources of large-scale γ-ray emission due to hadronic interactions in the intracluster medium (ICM). In this paper, we estimate the sensitivity of the Cherenkov Telescope Array (CTA) to detect diffuse γ-ray emission from the Perseus galaxy cluster. We first perform a detailed spatial and spectral modelling of the expected signal for both the DM and the CRp components. For each case, we compute the expected CTA sensitivity accounting for the CTA instrument response functions. The CTA observing strategy of the Perseus cluster is also discussed. In the absence of a diffuse signal (non-detection), CTA should constrain the CRp to thermal energy ratio X 500 within the characteristic radius R 500 down to about X 500 < 3 × 10-3, for a spatial CRp distribution that follows the thermal gas and a CRp spectral index αCRp = 2.3. Under the optimistic assumption of a pure hadronic origin of the Perseus radio mini-halo and depending on the assumed magnetic field profile, CTA should measure αCRp down to about ΔαCRp ≃ 0.1 and the CRp spatial distribution with 10% precision, respectively. Regarding DM, CTA should improve the current ground-based γ-ray DM limits from clusters observations on the velocity-averaged annihilation cross-section by a factor of up to ∼ 5, depending on the modelling of DM halo substructure. In the case of decay of DM particles, CTA will explore a new region of the parameter space, reaching models with τ χ > 1027 s for DM masses above 1 TeV. These constraints will provide unprecedented sensitivity to the physics of both CRp acceleration and transport at cluster scale and to TeV DM particle models, especially in the decay scenario.

Search for a light sterile neutrino with 7.5 years of IceCube DeepCore data

Physical Review D American Physical Society (APS) 110:7 (2024) 072007

Authors:

R Abbasi, M Ackermann, J Adams, SK Agarwalla, JA Aguilar, M Ahlers, JM Alameddine, NM Amin, K Andeen, C Argüelles, Y Ashida, S Athanasiadou, L Ausborm, SN Axani, X Bai, A Balagopal V., M Baricevic, SW Barwick, S Bash, V Basu, R Bay, JJ Beatty, J Becker Tjus, J Beise, C Bellenghi, C Benning, S BenZvi, D Berley, E Bernardini, DZ Besson, E Blaufuss, L Bloom, S Blot, F Bontempo, JY Book Motzkin, C Boscolo Meneguolo, S Böser, O Botner, J Böttcher, E Bourbeau, J Braun, B Brinson, J Brostean-Kaiser, L Brusa, RT Burley, D Butterfield, MA Campana, I Caracas, K Carloni, J Carpio, S Chattopadhyay, N Chau, Z Chen, D Chirkin, S Choi, BA Clark, A Coleman, GH Collin, A Connolly, JM Conrad, R Corley, DF Cowen, P Dave, C De Clercq, JJ DeLaunay, D Delgado, S Deng, A Desai, P Desiati, KD de Vries, G de Wasseige, T DeYoung, A Diaz, JC Díaz-Vélez, P Dierichs, M Dittmer, A Domi, L Draper, H Dujmovic, D Durnford, K Dutta, MA DuVernois, T Ehrhardt, L Eidenschink, A Eimer, P Eller, E Ellinger, S El Mentawi, D Elsässer, R Engel, H Erpenbeck, J Evans, PA Evenson, KL Fan, K Fang, K Farrag, AR Fazely, A Fedynitch, N Feigl, S Fiedlschuster, C Finley, L Fischer, D Fox, A Franckowiak, S Fukami, P Fürst, J Gallagher, E Ganster, A Garcia, M Garcia, G Garg, E Genton, L Gerhardt, A Ghadimi, C Girard-Carillo, C Glaser, T Glüsenkamp, JG Gonzalez, S Goswami, A Granados, D Grant, SJ Gray, O Gries, S Griffin, S Griswold, KM Groth, D Guevel, C Günther, P Gutjahr, C Ha, C Haack, A Hallgren, L Halve, F Halzen, H Hamdaoui, M Ha Minh, M Handt, K Hanson, J Hardin, AA Harnisch, P Hatch, A Haungs, J Häußler, K Helbing, J Hellrung, J Hermannsgabner, L Heuermann, N Heyer, S Hickford, A Hidvegi, J Hignight, C Hill, GC Hill, KD Hoffman, S Hori, K Hoshina, M Hostert, W Hou, T Huber, K Hultqvist, M Hünnefeld, R Hussain, K Hymon, A Ishihara, W Iwakiri, M Jacquart, S Jain, O Janik, M Jansson, GS Japaridze, M Jeong, M Jin, BJP Jones, N Kamp, D Kang, W Kang, X Kang, A Kappes, D Kappesser, L Kardum, T Karg, M Karl, A Karle, A Katil, U Katz, M Kauer, JL Kelley, M Khanal, A Khatee Zathul, A Kheirandish, J Kiryluk, SR Klein, A Kochocki, R Koirala, H Kolanoski, T Kontrimas, L Köpke, C Kopper, DJ Koskinen, P Koundal, M Kovacevich, M Kowalski, T Kozynets, J Krishnamoorthi, K Kruiswijk, E Krupczak, A Kumar, E Kun, N Kurahashi, N Lad, C Lagunas Gualda, M Lamoureux, MJ Larson, S Latseva, F Lauber, JP Lazar, JW Lee, K Leonard DeHolton, A Leszczyńska, J Liao, M Lincetto, YT Liu, M Liubarska, C Love, L Lu, F Lucarelli, W Luszczak, Y Lyu, W Y., J Madsen, E Magnus, KBM Mahn, Y Makino, E Manao, S Mancina, W Marie Sainte, IC Mariş, S Marka, Z Marka, M Marsee, I Martinez-Soler, R Maruyama, F Mayhew, F McNally, JV Mead, K Meagher, S Mechbal, A Medina, M Meier, Y Merckx, L Merten, J Micallef, J Mitchell, T Montaruli, RW Moore, Y Morii, R Morse, M Moulai, T Mukherjee, R Naab, R Nagai, M Nakos, U Naumann, J Necker, A Negi, L Neste, M Neumann, H Niederhausen, MU Nisa, K Noda, A Noell, A Novikov, A Obertacke Pollmann, V O’Dell, B Oeyen, A Olivas, R Orsoe, J Osborn, E O’Sullivan, V Palusova, H Pandya, N Park, GK Parker, EN Paudel, L Paul, C Pérez de los Heros, T Pernice, J Peterson, A Pizzuto, M Plum, A Pontén, Y Popovych, M Prado Rodriguez, B Pries, R Procter-Murphy, GT Przybylski, C Raab, J Rack-Helleis, M Ravn, K Rawlins, Z Rechav, A Rehman, P Reichherzer, E Resconi, S Reusch, W Rhode, B Riedel, A Rifaie, EJ Roberts, S Robertson, S Rodan, G Roellinghoff, M Rongen, A Rosted, C Rott, T Ruhe, L Ruohan, D Ryckbosch, I Safa, J Saffer, D Salazar-Gallegos, P Sampathkumar, A Sandrock, M Santander, S Sarkar, S Sarkar, J Savelberg, P Savina, P Schaile, M Schaufel, H Schieler, S Schindler, L Schlickmann, B Schlüter, F Schlüter, N Schmeisser, T Schmidt, J Schneider, FG Schröder, L Schumacher, S Sclafani, D Seckel, M Seikh, M Seo, S Seunarine, P Sevle Myhr, R Shah, S Shefali, N Shimizu, M Silva, B Skrzypek, B Smithers, R Snihur, J Soedingrekso, A Søgaard, D Soldin, P Soldin, G Sommani, C Spannfellner, GM Spiczak, C Spiering, M Stamatikos, T Stanev, T Stezelberger, T Stürwald, T Stuttard, GW Sullivan, I Taboada, S Ter-Antonyan, A Terliuk, M Thiesmeyer, WG Thompson, J Thwaites, S Tilav, K Tollefson, C Tönnis, S Toscano, D Tosi, A Trettin, R Turcotte, JP Twagirayezu, MA Unland Elorrieta, AK Upadhyay, K Upshaw, A Vaidyanathan, N Valtonen-Mattila, J Vandenbroucke, N van Eijndhoven, D Vannerom, J van Santen, J Vara, F Varsi, J Veitch-Michaelis, M Venugopal, M Vereecken, S Vergara Carrasco, S Verpoest, D Veske, A Vijai, C Walck, A Wang, C Weaver, P Weigel, A Weindl, J Weldert, AY Wen, C Wendt, J Werthebach, M Weyrauch, N Whitehorn, CH Wiebusch, DR Williams, L Witthaus, A Wolf, M Wolf, G Wrede, XW Xu, JP Yanez, E Yildizci, S Yoshida, R Young, S Yu, T Yuan, Z Zhang, P Zhelnin, P Zilberman, M Zimmerman

2D Convolutional Neural Network for Event Reconstruction in IceCube DeepCore

Proceedings of Science 444 (2024)

Authors:

R Abbasi, M Ackermann, J Adams, SK Agarwalla, JA Aguilar, M Ahlers, JM Alameddine, NM Amin, K Andeen, G Anton, C Argüelles, Y Ashida, S Athanasiadou, SN Axani, X Bai, AV Balagopal, M Baricevic, SW Barwick, V Basu, R Bay, JJ Beatty, J Becker Tjus, J Beise, C Bellenghi, C Benning, S BenZvi, D Berley, E Bernardini, DZ Besson, E Blaufuss, S Blot, F Bontempo, JY Book, C Boscolo Meneguolo, S Böser, O Botner, J Böttcher, E Bourbeau, J Braun, B Brinson, J Brostean-Kaiser, RT Burley, RS Busse, D Butterfield, MA Campana, K Carloni, EG Carnie-Bronca, S Chattopadhyay, N Chau, C Chen, Z Chen, D Chirkin, S Choi, BA Clark, L Classen, A Coleman, GH Collin, A Connolly, JM Conrad, P Coppin, P Correa, DF Cowen, P Dave, C De Clercq, JJ DeLaunay, D Delgado, S Deng, K Deoskar, A Desai, P Desiati, KD de Vries, G de Wasseige, T DeYoung, A Diaz, JC Díaz-Vélez, M Dittmer, A Domi, H Dujmovic, MA DuVernois, T Ehrhardt, P Eller, E Ellinger, S El Mentawi, D Elsässer, R Engel, H Erpenbeck, J Evans, PA Evenson, KL Fan, K Fang, K Farrag, AR Fazely, A Fedynitch, N Feigl, S Fiedlschuster, C Finley, L Fischer, D Fox, A Franckowiak, A Fritz

Abstract:

IceCube DeepCore is an extension of the IceCube Neutrino Observatory designed to measure GeV scale atmospheric neutrino interactions for the purpose of neutrino oscillation studies. Distinguishing muon neutrinos from other flavors and reconstructing inelasticity are especially difficult tasks at GeV scale energies in IceCube DeepCore due to sparse instrumentation. Convolutional neural networks (CNNs) have been found to have better success at neutrino event reconstruction than conventional likelihood-based methods. In this contribution, we present a new CNN model that exploits time and depth translational symmetry in IceCube DeepCore data and present the model’s performance, specifically for flavor identification and inelasticity reconstruction.

A time variability test for neutrino sources identified by IceCube

Proceedings of Science 444 (2024)

Authors:

R Abbasi, M Ackermann, J Adams, SK Agarwalla, JA Aguilar, M Ahlers, JM Alameddine, NM Amin, K Andeen, G Anton, C Argüelles, Y Ashida, S Athanasiadou, SN Axani, X Bai, AV Balagopal, M Baricevic, SW Barwick, V Basu, R Bay, JJ Beatty, J Becker Tjus, J Beise, C Bellenghi, C Benning, S BenZvi, D Berley, E Bernardini, DZ Besson, E Blaufuss, S Blot, F Bontempo, JY Book, C Boscolo Meneguolo, S Böser, O Botner, J Böttcher, E Bourbeau, J Braun, B Brinson, J Brostean-Kaiser, RT Burley, RS Busse, D Butterfield, MA Campana, K Carloni, EG Carnie-Bronca, S Chattopadhyay, N Chau, C Chen, Z Chen, D Chirkin, S Choi, BA Clark, L Classen, A Coleman, GH Collin, A Connolly, JM Conrad, P Coppin, P Correa, DF Cowen, P Dave, C De Clercq, JJ DeLaunay, D Delgado, S Deng, K Deoskar, A Desai, P Desiati, KD de Vries, G de Wasseige, T DeYoung, A Diaz, JC Díaz-Vélez, M Dittmer, A Domi, H Dujmovic, MA DuVernois, T Ehrhardt, P Eller, E Ellinger, S El Mentawi, D Elsässer, R Engel, H Erpenbeck, J Evans, PA Evenson, KL Fan, K Fang, K Farrag, AR Fazely, A Fedynitch, N Feigl, S Fiedlschuster, C Finley, L Fischer, D Fox, A Franckowiak, A Fritz

Abstract:

IceCube has reported evidence for neutrino emission from the Seyfert-II galaxy NGC 1068 and the blazar TXS 0506+056. The former was identified in a time-integrated search, and the latter using time-dependent and multi-messenger methods. A natural question is: are sources identified in time-integrated searches consistent with a steady neutrino source? We present a non-parametric method, TAUNTON, to answer this question. Motivated by the Cramér-von Mises test, TAUNTON is an unbinned single-hypothesis method to identify deviations in neutrino data from the steady hypothesis. An advantage of TAUNTON is that it is sensitive to arbitrary deviations from the steady hypothesis. Here we present results of TAUNTON applied to a 8.7 year data-set of muon neutrino track events; the same data used to identify NGC 1068 at 4.2σ. We use TAUNTON on 51 objects, a subset (with >4 signal neutrinos) of the 110 objects studied in the NGC 1068 publication. We set a threshold of 3σ pre-trial to identify sources inconsistent with the steady hypothesis. TAUNTON reports a p-value of 0.9 for NGC 1068, consistent with the steady hypothesis. Using the time integrated fit, data for TXS 0506+056 is consistent with the steady hypothesis at 1.7σ. Time variability is not identified for TXS 0506+056 because there are few neutrino events.