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Constraining the Prompt Atmospheric Neutrino Flux Combining IceCube's Cascade and Track Samples

R. Abbasi, M. Ackermann, J. Adams, S. K. Agarwalla, J. A. Aguilar, M. Ahlers, J. M. Alameddine, S. Ali, N. M. Amin, K. Andeen, C. Argüelles, Y. Ashida, S. Athanasiadou, S. N. Axani, R. Babu, X. Bai, J. Baines-Holmes, A. Balagopal V., S. W. Barwick, S. Bash, V. Basu, R. Bay, J. J. Beatty, J. Becker Tjus, P. Behrens, J. Beise, C. Bellenghi, S. Benkel, S. BenZvi, D. Berley, E. Bernardini, D. Z. Besson, E. Blaufuss, L. Bloom, S. Blot, I. Bodo, F. Bontempo, J. Y. Book Motzkin, C. Boscolo Meneguolo, S. Böser, O. Botner, J. Böttcher, J. Braun, B. Brinson, Z. Brisson-Tsavoussis, R. T. Burley, D. Butterfield, M. A. Campana, K. Carloni, J. Carpio, S. Chattopadhyay, N. Chau, Z. Chen, D. Chirkin, S. Choi, B. A. Clark, P. Coleman, G. H. Collin, D. A. Coloma Borja, A. Connolly, J. M. Conrad, D. F. Cowen, C. De Clercq, J. J. DeLaunay, D. Delgado, T. Delmeulle, S. Deng, P. Desiati, K. D. de Vries, G. de Wasseige, T. DeYoung, J. C. Díaz-Vélez, S. DiKerby, T. Ding, M. Dittmer, A. Domi, L. Draper, L. Dueser, D. Durnford, K. Dutta, M. A. DuVernois, T. Ehrhardt, L. Eidenschink, A. Eimer, C. Eldridge, P. Eller, E. Ellinger, D. Elsässer, R. Engel, H. Erpenbeck, W. Esmail, S. Eulig, J. Evans, P. A. Evenson, K. L. Fan, K. Fang, K. Farrag, A. R. Fazely, A. Fedynitch, N. Feigl, 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. Glaser, T. Glüsenkamp, J. G. Gonzalez, S. Goswami, A. Granados, D. Grant, S. J. Gray, S. Griffin, S. Griswold, K. M. Groth, D. Guevel, C. Günther, P. Gutjahr, C. Ha, C. Haack, A. Hallgren, L. Halve, F. Halzen, L. Hamacher, M. Ha Minh, M. Handt, K. Hanson, J. Hardin, A. A. Harnisch, P. Hatch, A. Haungs, J. Häußler, K. Helbing, J. Hellrung, B. Henke, L. Hennig, F. Henningsen, L. Heuermann, R. Hewett, N. Heyer, S. Hickford, A. Hidvegi, C. Hill, G. C. Hill, R. Hmaid, K. D. Hoffman, D. Hooper, S. Hori, K. Hoshina, M. Hostert, W. Hou, M. Hrywniak, T. Huber, K. Hultqvist, K. Hymon, A. Ishihara, W. Iwakiri, M. Jacquart, S. Jain, O. Janik, M. Jansson, M. Jeong, M. Jin, N. Kamp, D. Kang, W. Kang, A. Kappes, L. Kardum, T. Karg, M. Karl, A. Karle, A. Katil, M. Kauer, J. L. Kelley, M. Khanal, A. Khatee Zathul, A. Kheirandish, H. Kimku, J. Kiryluk, C. Klein, S. R. Klein, Y. Kobayashi, A. Kochocki, R. Koirala, H. Kolanoski, T. Kontrimas, L. Köpke, C. Kopper, D. J. Koskinen, P. Koundal, M. Kowalski, T. Kozynets, A. Kravka, N. Krieger, J. Krishnamoorthi, T. Krishnan, K. Kruiswijk, E. Krupczak, A. Kumar, E. Kun, N. Kurahashi, N. Lad, C. Lagunas Gualda, L. Lallement Arnaud, M. J. Larson, F. Lauber, J. P. Lazar, K. Leonard DeHolton, A. Leszczyńska, C. Li, J. Liao, C. Lin, Q. R. Liu, Y. T. Liu, M. Liubarska, C. Love, L. Lu, F. Lucarelli, W. Luszczak, Y. Lyu, M. Macdonald, J. Madsen, E. Magnus, Y. Makino, E. Manao, S. Mancina, A. Mand, I. C. Mari{ş}, S. Marka, Z. Marka, L. Marten, I. Martinez-Soler, R. Maruyama, J. Mauro, F. Mayhew, F. McNally, K. Meagher, S. Mechbal, A. Medina, M. Meier, Y. Merckx, L. Merten, J. Mitchell, L. Molchany, S. Mondal, T. Montaruli, R. W. Moore, Y. Morii, A. Mosbrugger, M. Moulai, D. Mousadi, E. Moyaux, T. Mukherjee, R. Naab, M. Nakos, U. Naumann, J. Necker, L. Neste, M. Neumann, H. Niederhausen, M. U. Nisa, K. Noda, A. Noell, A. Novikov, A. Obertacke, V. O'Dell, A. Olivas, R. Orsoe, J. Osborn, E. O'Sullivan, V. Palusova, H. Pandya, A. Parenti, N. Park, V. Parrish, E. N. Paudel, L. Paul, C. Pérez de los Heros, T. Pernice, T. C. Petersen, J. Peterson, M. Plum, A. Pontén, V. Poojyam, Y. Popovych, M. Prado Rodriguez, B. Pries, R. Procter-Murphy, G. T. Przybylski, L. Pyras, C. Raab, J. Rack-Helleis, N. Rad, M. Ravn, K. Rawlins, Z. Rechav, A. Rehman, I. Reistroffer, E. Resconi, S. Reusch, C. D. Rho, W. Rhode, L. Ricca, B. Riedel, A. Rifaie, E. J. Roberts, M. Rongen, A. Rosted, C. Rott, T. Ruhe, L. Ruohan, D. Ryckbosch, J. Saffer, D. Salazar-Gallegos, P. Sampathkumar, A. Sandrock, G. Sanger-Johnson, M. Santander, S. Sarkar, M. Scarnera, P. Schaile, M. Schaufel, H. Schieler, S. Schindler, L. Schlickmann, B. Schlüter, F. Schlüter, N. Schmeisser, T. Schmidt, F. G. Schröder, L. Schumacher, S. Schwirn, S. Sclafani, D. Seckel, L. Seen, M. Seikh, S. Seunarine, P. A. Sevle Myhr, R. Shah, S. Shah, S. Shefali, N. Shimizu, B. Skrzypek, R. Snihur, J. Soedingrekso, D. Soldin, P. Soldin, G. Sommani, C. Spannfellner, G. M. Spiczak, C. Spiering, J. Stachurska, M. Stamatikos, T. Stanev, T. Stezelberger, T. Stürwald, T. Stuttard, G. W. Sullivan, I. Taboada, S. Ter-Antonyan, A. Terliuk, A. Thakuri, M. Thiesmeyer, W. G. Thompson, J. Thwaites, S. Tilav, K. Tollefson, S. Toscano, D. Tosi, A. Trettin, A. K. Upadhyay, K. Upshaw, A. Vaidyanathan, N. Valtonen-Mattila, J. Valverde, J. Vandenbroucke, T. Van Eeden, N. van Eijndhoven, L. Van Rootselaar, J. van Santen, J. Vara, F. Varsi, M. Venugopal, M. Vereecken, S. Vergara Carrasco, S. Verpoest, D. Veske, A. Vijai, J. Villarreal, C. Walck, A. Wang, E. H. S. Warrick, C. Weaver, P. Weigel, A. Weindl, J. Weldert, A. Y. Wen, C. Wendt, J. Werthebach, M. Weyrauch, N. Whitehorn, C. H. Wiebusch, D. R. Williams, L. Witthaus, M. Wolf, G. Wrede, X. W. Xu, J. P. Yanez, Y. Yao, E. Yildizci, S. Yoshida, R. Young, F. Yu, S. Yu, T. Yuan, S. Yun-Cárcamo, A. Zander Jurowitzki, A. Zegarelli, S. Zhang, Z. Zhang, P. Zhelnin, P. Zilberman

TL;DR

This work addresses the uncertainty in the prompt atmospheric neutrino flux, a background to IceCube's astrophysical neutrinos, by performing a Combined Fit that jointly analyzes cascade-like and track-like events with forward-folded templates. The analysis employs a flexible astrophysical flux parameterization and a robust treatment of systematic uncertainties, using $\phi^0_{\mathrm{prompt}}$ to normalize the prompt component relative to forward charm models like $\phi_{\mathrm{SIBYLL}}(E)$, and evaluates sensitivity via an Asimov null test with Feldman–Cousins statistics. The result is a non-zero best-fit prompt normalization that is statistically insignificant ($<1\sigma$), leading to a 90% CL upper limit of $\phi^0_{\mathrm{prompt}}=2.59$, with the combined analysis achieving tighter constraints than prior efforts and demonstrating robustness against astrophysical-model choices. The findings begin to constrain forward-charm predictions and emphasize the value of combining complementary event selections, while outlining future paths to further reduce backgrounds through improved modeling and additional IceCube channels.

Abstract

The IceCube Neutrino Observatory has observed a diffuse flux of high-energy astrophysical neutrinos for more than a decade. A relevant background to the astrophysical flux is prompt atmospheric neutrinos, originating from the decay of charmed mesons produced in cosmic-ray-induced air showers. The production rate of charmed mesons in the very forward phase space of hadronic interactions, and consequently, the prompt neutrino flux, remains uncertain and has not yet been observed by neutrino detectors. An accurate measurement of this flux would enhance our understanding of fundamental particle physics such as hadronic interactions in high-energy cosmic-ray-induced air showers and the nucleon structure. Furthermore, an experimental characterization of this background flux will improve the precision of astrophysical neutrino flux spectral measurements. In this work, we perform a combined fit of cascade-like and track-like neutrino events in IceCube to constrain the prompt atmospheric neutrino flux. Given that the prompt flux is a sub-dominant contribution, treating systematic uncertainties arising from the potential mis-modeling of the conventional and astrophysical neutrino fluxes is critical for its measurement. Our analysis yields a non-zero best-fit result, which is, however, consistent with the null hypothesis of no prompt flux within one standard deviation. Consequently, we establish an upper bound on the flux at $4\times 10^{-16}$ (GeV m$^2$ s sr)$^{-1}$ at 10 TeV.

Constraining the Prompt Atmospheric Neutrino Flux Combining IceCube's Cascade and Track Samples

TL;DR

This work addresses the uncertainty in the prompt atmospheric neutrino flux, a background to IceCube's astrophysical neutrinos, by performing a Combined Fit that jointly analyzes cascade-like and track-like events with forward-folded templates. The analysis employs a flexible astrophysical flux parameterization and a robust treatment of systematic uncertainties, using to normalize the prompt component relative to forward charm models like , and evaluates sensitivity via an Asimov null test with Feldman–Cousins statistics. The result is a non-zero best-fit prompt normalization that is statistically insignificant (), leading to a 90% CL upper limit of , with the combined analysis achieving tighter constraints than prior efforts and demonstrating robustness against astrophysical-model choices. The findings begin to constrain forward-charm predictions and emphasize the value of combining complementary event selections, while outlining future paths to further reduce backgrounds through improved modeling and additional IceCube channels.

Abstract

The IceCube Neutrino Observatory has observed a diffuse flux of high-energy astrophysical neutrinos for more than a decade. A relevant background to the astrophysical flux is prompt atmospheric neutrinos, originating from the decay of charmed mesons produced in cosmic-ray-induced air showers. The production rate of charmed mesons in the very forward phase space of hadronic interactions, and consequently, the prompt neutrino flux, remains uncertain and has not yet been observed by neutrino detectors. An accurate measurement of this flux would enhance our understanding of fundamental particle physics such as hadronic interactions in high-energy cosmic-ray-induced air showers and the nucleon structure. Furthermore, an experimental characterization of this background flux will improve the precision of astrophysical neutrino flux spectral measurements. In this work, we perform a combined fit of cascade-like and track-like neutrino events in IceCube to constrain the prompt atmospheric neutrino flux. Given that the prompt flux is a sub-dominant contribution, treating systematic uncertainties arising from the potential mis-modeling of the conventional and astrophysical neutrino fluxes is critical for its measurement. Our analysis yields a non-zero best-fit result, which is, however, consistent with the null hypothesis of no prompt flux within one standard deviation. Consequently, we establish an upper bound on the flux at (GeV m s sr) at 10 TeV.

Paper Structure

This paper contains 6 sections, 6 figures, 3 tables.

Figures (6)

  • Figure 1: Model predictions for prompt neutrino fluxes. Shown are the models SIBYLL Fedynitch:2018cbl, GRRST Gauld:2015kvh, GM-VFNS Benzke:2017yjn and BEJKRSS Bhattacharya:2016jce, as dash-dotted and dashed lines. Uncertainties for the latter three are plotted as colored bands in grey-green, olive, and red, respectively. The conventional neutrino flux Gaisser:2011klfFedynitch:2018cbl (Conv.) from vertical zenith direction $\theta=180^\circ$ (dashed line) and horizontal zenith direction $\theta=90^\circ$ (solid line) direction is shown in grey. Also shown are the results of this analysis as an upper limit on the prompt flux (dark red) and the best-fit single power-law spectrum (SPL) of astrophysical neutrinos (black line).
  • Figure 2: Ratio of prompt neutrino rate $S$ over the square root of the total background rate $B$ from conventional atmospheric and astrophysical neutrinos and atmospheric muons in the track and cascade samples. The axes correspond to the reconstructed zenith $\theta$ and energy $E$ of the respective selection. The choice of bins is identical to IceCube:2025tgpIceCube:2025ewu.
  • Figure 3: Likelihood difference of the best-fit to the injected null hypothesis $\phi_{\mathrm{prompt}} = 0$ and tested non-zero prompt flux normalizations. This is shown for the individual samples (cascades in red, Northern Track in turquoise) and the Combined Fit in blue. The dashed line corresponds to the critical value of 90% confidence after correction (see text). Sensitivities correspond to the crossing point of the likelihood profile and the critical value line.
  • Figure 4: Correlation coefficient of the prompt flux normalization with the other fit parameters.
  • Figure 5: Test of the bias on $\phi^0_{\mathrm{prompt}}$ introduced by the assumed astrophysical model parametrization in the fit. The columns correspond to the fitted astrophysical model; the rows to the injected model. A value closer to the injected prompt normalization $\phi^0_{\mathrm{prompt}}=1$, corresponds to a smaller bias caused by fitting the astrophysical model of the respective column. Model definitions are in the text; for the cutoff and BL-Lac models, please refer also to Abbasi:2021qfz and Padovani:2015mba.
  • ...and 1 more figures