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Constraining High-energy Neutrino Emission from Supernovae with IceCube

Constraining High-energy Neutrino Emission from Supernovae with IceCube The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 https://doi.org/10.3847/2041-8213/acd2c9 © 2023. The Author(s). Published by the American Astronomical Society. 1 2 3 4,65 5 6 7 R. Abbasi , M. Ackermann , J. Adams , S. K. Agarwalla , J. A. Aguilar , M. Ahlers , J. M. Alameddine , 8 9 10 11 4 2 8 12 N. M. Amin , K. Andeen , G. Anton , C. Argüelles , Y. Ashida , S. Athanasiadou , S. N. Axani , X. Bai , 4 4 13 4 14 15,16 17 A. Balagopal V. , M. Baricevic , S. W. Barwick , V. Basu , R. Bay , J. J. Beatty , K.-H. Becker , 18,66 19 20 21 22 23 24 J. Becker Tjus , J. Beise , C. Bellenghi , S. BenZvi , D. Berley , E. Bernardini , D. Z. Besson , 14,25 17 22 2 26 11 23 27 G. Binder , D. Bindig , E. Blaufuss , S. Blot , F. Bontempo , J. Y. Book , C. Boscolo Meneguolo , S. Böser , 19 28 6 4 29 2 30 31 O. Botner , J. Böttcher , E. Bourbeau , J. Braun , B. Brinson , J. Brostean-Kaiser , R. T. Burley , R. S. Busse , 4 32 11 30 4,65 29 33 D. Butterfield , M. A. Campana , K. Carloni , E. G. Carnie-Bronca , S. Chattopadhyay , C. Chen , Z. Chen , 4 34 22 31 19 35 15,16 35 D. Chirkin , S. Choi , B. A. Clark , L. Classen , A. Coleman , G. H. Collin , A. Connolly , J. M. Conrad , 36 36 37 38,39 29 36 40 P. Coppin , P. Correa , S. Countryman , D. F. Cowen , P. Dave , C. De Clercq , J. J. DeLaunay , 11 8 41 4 4 36 42 D. Delgado López , H. Dembinski , K. Deoskar , A. Desai , P. Desiati , K. D. de Vries , G. de Wasseige , 43 35 4 31 10 4 4 T. DeYoung , A. Diaz , J. C. Díaz-Vélez , M. Dittmer , A. Domi , H. Dujmovic , M. A. DuVernois , 27 20 26,44 4 22 8 22 4 T. Ehrhardt , P. Eller , R. Engel , H. Erpenbeck , J. Evans , P. A. Evenson , K. L. Fan , K. Fang , 45 46 47 10 41 2 38 18 A. R. Fazely , A. Fedynitch , N. Feigl , S. Fiedlschuster , C. Finley , L. Fischer , D. Fox , A. Franckowiak , 22 27 28 8 48 28 11 2 25 E. Friedman , A. Fritz , P. Fürst , T. K. Gaisser , J. Gallagher , E. Ganster , A. Garcia , S. Garrappa , L. Gerhardt , 40 19 20 10,19 44 8 40 43 A. Ghadimi , C. Glaser , T. Glauch , T. Glüsenkamp , N. Goehlke , J. G. Gonzalez , S. Goswami , D. Grant , 22 4 21 28 7 20 19 43 28 S. J. Gray , S. Griffin , S. Griswold , C. Günther , P. Gutjahr , C. Haack , A. Hallgren , R. Halliday , L. Halve , 4 33 20 4 35 43 49 26 F. Halzen , H. Hamdaoui , M. Ha Minh , K. Hanson , J. Hardin , A. A. Harnisch , P. Hatch , A. Haungs , 17 18 20 28 17 41 50 30 K. Helbing , J. Hellrung , F. Henningsen , L. Heuermann , S. Hickford , A. Hidvegi , C. Hill , G. C. Hill , 22 4,67 26 26 41 7 4 7 34 K. D. Hoffman , K. Hoshina , W. Hou , T. Huber , K. Hultqvist , M. Hünnefeld , R. Hussain , K. Hymon ,S.In , 5 50 4 41 51 4,65 34 11 N. Iovine , A. Ishihara , M. Jacquart , M. Jansson , G. S. Japaridze , K. Jayakumar , M. Jeong , M. Jin , 52 26 34 32 31 27 7 2 20 B. J. P. Jones , D. Kang ,W. Kang ,X. Kang , A. Kappes ,D. Kappesser , L. Kardum ,T. Karg ,M.Karl , 4 10 4 4 4 53,54 50 33 A. Karle , U. Katz ,M. Kauer ,J. L.Kelley , A. Khatee Zathul ,A. Kheirandish ,K. Kin , J. Kiryluk , 14,25 43 8 47 20 27 43 S. R. Klein , A. Kochocki ,R. Koirala ,H. Kolanoski , T. Kontrimas ,L. Köpke ,C.Kopper , 6 26 32 2,47 6 42 43 D. J. Koskinen , P. Koundal , M. Kovacevich , M. Kowalski , T. Kozynets , K. Kruiswijk ,E.Krupczak , 2 18 32 2 2 42 22 17 A. Kumar ,E.Kun ,N.Kurahashi ,N.Lad ,C.Lagunas Gualda , M. Lamoureux , M. J. Larson , F. Lauber , 4,11 34 38,39 8 18 4 55 J. P. Lazar ,J.W.Lee , K. Leonard DeHolton , A. Leszczyńska ,M.Lincetto ,Q. R.Liu ,M. Liubarska , 27 32 31 4 56 57 15,16 14,25 E. Lohfink ,C.Love , C. J. Lozano Mariscal ,L.Lu ,F.Lucarelli ,A.Ludwig ,W.Luszczak ,Y. Lyu , 2 4 43 4 4,23 4 5 37 37 W. Y. Ma ,J.Madsen ,K. B.M. Mahn ,Y.Makino ,S. Mancina , W. Marie Sainte ,I. C.Mariş ,S. Marka ,Z. Marka , 40 11 58 43 55 59 6 4 M. Marsee , I. Martinez-Soler ,R. Maruyama , F. Mayhew ,T. McElroy , F. McNally , J. V. Mead , K. Meagher , 2 16 50 20 36 18 43 5 S. Mechbal , A. Medina ,M. Meier , S. Meighen-Berger ,Y. Merckx , L. Merten , J. Micallef ,D. Mockler , 56 55 50 4 4 26 2 50 4 T. Montaruli ,R.W.Moore , Y. Morii ,R.Morse ,M.Moulai ,T.Mukherjee ,R.Naab ,R.Nagai ,M. Nakos , 17 2 31 43 43 28 43 U. Naumann , J. Necker ,M. Neumann , H. Niederhausen , M. U. Nisa ,A. Noell , S.C.Nowicki , 17 4 26 60 22 20 4 19 A. Obertacke Pollmann ,V. O’Dell , M. Oehler , B. Oeyen ,A. Olivas ,R. Orsoe , J. Osborn ,E. O’Sullivan , 8 49 52 8 9 19 4 28 H. Pandya , N. Park , G. K. Parker , E. N. Paudel ,L.Paul , C. Pérez de los Heros , J. Peterson , S. Philippen , 17 4 12 27 4 43 22 25 S. Pieper ,A.Pizzuto ,M.Plum ,Y. Popovych , M. Prado Rodriguez ,B. Pries , R. Procter-Murphy , G. T. Przybylski , 5 27 61 4 8 18 5 20 2 C. Raab , J. Rack-Helleis , K. Rawlins ,Z. Rechav ,A. Rehman ,P.Reichherzer ,G.Renzi , E. Resconi , S. Reusch , 7 32 4 30 14,25 34 34 27 W. Rhode , M. Richman ,B. Riedel , E.J.Roberts ,S.Robertson , S. Rodan , G. Roellinghoff , M. Rongen , 34,62 7 20 60 4,11 44 43 26 C. Rott , T. Ruhe , L. Ruohan , D. Ryckbosch ,I.Safa , J. Saffer , D. Salazar-Gallegos , P. Sampathkumar , 43 7 40 55 63 28 4 28 S. E. Sanchez Herrera , A. Sandrock ,M.Santander , S. Sarkar ,S.Sarkar , J. Savelberg ,P.Savina ,M.Schaufel , 26 10 31 22 10 8,26 20 H. Schieler ,S.Schindler , B. Schlüter ,T.Schmidt , J. Schneider , F. G. Schröder , L. Schumacher , 28 32 8 64 19 44 50 4 11 G. Schwefer , S. Sclafani , D. Seckel , S. Seunarine ,A.Sharma , S. Shefali , N. Shimizu ,M.Silva , B. Skrzypek , 52 4 7 6 44 18 20 64 B. Smithers ,R. Snihur , J. Soedingrekso ,A. Søgaard ,D.Soldin ,G.Sommani , C. Spannfellner , G. M. Spiczak , 2 16 8 2 2 25 17 6 C. Spiering , M. Stamatikos ,T.Stanev ,A. Stasik ,R.Stein , T. Stezelberger , T. Stürwald , T. Stuttard , 22 29 45 11 4 8 43 G. W. Sullivan , I. Taboada , S. Ter-Antonyan ,W.G.Thompson , J. Thwaites ,S.Tilav , K. Tollefson , 34 5 4 2 29 26 43 4 C. Tönnis , S. Toscano , D. Tosi , A. Trettin , C.F.Tung , R. Turcotte , J. P. Twagirayezu ,B. Ty , 31 4,65 45 19 4 M. A. Unland Elorrieta , A. K. Upadhyay , K. Upshaw , N. Valtonen-Mattila , J. Vandenbroucke , 36 35 2 31 4 26 60 N. van Eijndhoven , D. Vannerom , J. van Santen ,J.Vara , J. Veitch-Michaelis , M. Venugopal , S. Verpoest , 37 41 52 43 35 26 38,39 4 D. Veske ,C.Walck ,T. B.Watson , C. Weaver ,P. Weigel , A. Weindl ,J. Weldert ,C.Wendt , 7 26 43,57 28 43 40 20 10 J. Werthebach , M. Weyrauch , N. Whitehorn ,C. H.Wiebusch ,N. Willey , D. R. Williams ,M. Wolf ,G.Wrede , 18 45 55 4 50 11 43 4 33 11 J. Wulff ,X. W. Xu ,J.P. Yanez , E. Yildizci ,S.Yoshida ,F. Yu ,S. Yu , T. Yuan ,Z.Zhang , and P. Zhelnin IceCube Collaboration Department of Physics, Loyola University Chicago, Chicago, IL 60660, USA Deutsches Elektronen-Synchrotron DESY, Platanenallee 6, D-15738 Zeuthen, Germany Dept. of Physics and Astronomy, University of Canterbury, Private Bag 4800, Christchurch, New Zealand 1 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Dept. of Physics and Wisconsin IceCube Particle Astrophysics Center, University of Wisconsin-Madison, Madison, WI 53706, USA Université Libre de Bruxelles, Science Faculty CP230, B-1050 Brussels, Belgium Niels Bohr Institute, University of Copenhagen, DK-2100 Copenhagen, Denmark Dept. of Physics, TU Dortmund University, D-44221 Dortmund, Germany Bartol Research Institute and Dept. of Physics and Astronomy, University of Delaware, Newark, DE 19716, USA Department of Physics, Marquette University, Milwaukee, WI 53201, USA Erlangen Centre for Astroparticle Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, D-91058 Erlangen, Germany Department of Physics and Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, MA 02138, USA Physics Department, South Dakota School of Mines and Technology, Rapid City, SD 57701, USA Dept. of Physics and Astronomy, University of California, Irvine, CA 92697, USA Dept. of Physics, University of California, Berkeley, CA 94720, USA Dept. of Astronomy, Ohio State University, Columbus, OH 43210, USA Dept. of Physics and Center for Cosmology and Astro-Particle Physics, Ohio State University, Columbus, OH 43210, USA Dept. of Physics, University of Wuppertal, D-42119 Wuppertal, Germany Fakultät für Physik & Astronomie, Ruhr-Universität Bochum, D-44780 Bochum, Germany Dept. of Physics and Astronomy, Uppsala University, Box 516, SE-75120 Uppsala, Sweden Physik-department, Technische Universität München, D-85748 Garching, Germany Dept. of Physics and Astronomy, University of Rochester, Rochester, NY 14627, USA Dept. of Physics, University of Maryland, College Park, MD 20742, USA Dipartimento di Fisica e Astronomia Galileo Galilei, Università Degli Studi di Padova, I-35122 Padova PD, Italy Dept. of Physics and Astronomy, University of Kansas, Lawrence, KS 66045, USA Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA Karlsruhe Institute of Technology, Institute for Astroparticle Physics, D-76021 Karlsruhe, Germany Institute of Physics, University of Mainz, Staudinger Weg 7, D-55099 Mainz, Germany III. Physikalisches Institut, RWTH Aachen University, D-52056 Aachen, Germany School of Physics and Center for Relativistic Astrophysics, Georgia Institute of Technology, Atlanta, GA 30332, USA Department of Physics, University of Adelaide, Adelaide, 5005, Australia Institut für Kernphysik, Westfälische Wilhelms-Universität Münster, D-48149 Münster, Germany Dept. of Physics, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA Dept. of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794-3800, USA Dept. of Physics, Sungkyunkwan University, Suwon 16419, Republic of Korea Dept. of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Vrije Universiteit Brussel (VUB), Dienst ELEM, B-1050 Brussels, Belgium Columbia Astrophysics and Nevis Laboratories, Columbia University, New York, NY 10027, USA Dept. of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802, USA Dept. of Physics, Pennsylvania State University, University Park, PA 16802, USA Dept. of Physics and Astronomy, University of Alabama, Tuscaloosa, AL 35487, USA Oskar Klein Centre and Dept. of Physics, Stockholm University, SE-10691 Stockholm, Sweden Centre for Cosmology, Particle Physics and Phenomenology—CP3, Université catholique de Louvain, Louvain-la-Neuve, Belgium Dept. of Physics and Astronomy, Michigan State University, East Lansing, MI 48824, USA Karlsruhe Institute of Technology, Institute of Experimental Particle Physics, D-76021 Karlsruhe, Germany Dept. of Physics, Southern University, Baton Rouge, LA 70813, USA Institute of Physics, Academia Sinica, Taipei, 11529, Taiwan Institut für Physik, Humboldt-Universität zu Berlin, D-12489 Berlin, Germany Dept. of Astronomy, University of Wisconsin-Madison, Madison, WI 53706, USA Dept. of Physics, Engineering Physics, and Astronomy, Queen’s University, Kingston, ON K7L 3N6, Canada Dept. of Physics and The International Center for Hadron Astrophysics, Chiba University, Chiba 263-8522, Japan CTSPS, Clark-Atlanta University, Atlanta, GA 30314, USA Dept. of Physics, University of Texas at Arlington, 502 Yates St., Science Hall Rm 108, Box 19059, Arlington, TX 76019, USA Department of Physics & Astronomy, University of Nevada, Las Vegas, NV 89154, USA Nevada Center for Astrophysics, University of Nevada, Las Vegas, NV 89154, USA Dept. of Physics, University of Alberta, Edmonton, Alberta, T6G 2E1, Canada Département de physique nucléaire et corpusculaire, Université de Genève, CH-1211 Genève, Switzerland Department of Physics and Astronomy, UCLA, Los Angeles, CA 90095, USA Dept. of Physics, Yale University, New Haven, CT 06520, USA Department of Physics, Mercer University, Macon, GA 31207-0001, USA Dept. of Physics and Astronomy, University of Gent, B-9000 Gent, Belgium Dept. of Physics and Astronomy, University of Alaska Anchorage, 3211 Providence Dr., Anchorage, AK 99508, USA Department of Physics and Astronomy, University of Utah, Salt Lake City, UT 84112, USA Dept. of Physics, University of Oxford, Parks Road, Oxford OX1 3PU, UK Dept. of Physics, University of Wisconsin, River Falls, WI 54022, USA Received 2023 March 3; revised 2023 May 2; accepted 2023 May 5; published 2023 May 22 analysis@icecube.wisc.edu Also at Institute of Physics, Sachivalaya Marg, Sainik School Post, Bhubaneswar 751005, India. Also at Department of Space, Earth and Environment, Chalmers University of Technology, 412 96 Gothenburg, Sweden. Also at Earthquake Research Institute, University of Tokyo, Bunkyo, Tokyo 113-0032, Japan. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 2 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Abstract Core-collapse supernovae are a promising potential high-energy neutrino source class. We test for correlation between seven years of IceCube neutrino data and a catalog containing more than 1000 core-collapse supernovae of types IIn and IIP and a sample of stripped-envelope supernovae. We search both for neutrino emission from individual supernovae as well as for combined emission from the whole supernova sample, through a stacking analysis. No significant spatial or temporal correlation of neutrinos with the cataloged supernovae was found. All scenarios were tested against the background expectation and together yield an overall p-value of 93%; therefore, they show consistency with the background only. The derived upper limits on the total energy emitted in neutrinos 48 48 49 are 1.7 × 10 erg for stripped-envelope supernovae, 2.8 × 10 erg for type IIP, and 1.3 × 10 erg for type IIn SNe, the latter disfavoring models with optimistic assumptions for neutrino production in interacting supernovae. We conclude that stripped-envelope supernovae and supernovae of type IIn do not contribute more than 14.6% and 3 5 33.9%, respectively, to the diffuse neutrino flux in the energy range of about [ 10 –10 ] GeV, assuming that the neutrino energy spectrum follows a power-law with an index of −2.5. Under the same assumption, we can only constrain the contribution of type IIP SNe to no more than 59.9%. Thus, core-collapse supernovae of types IIn and stripped-envelope supernovae can both be ruled out as the dominant source of the diffuse neutrino flux under the given assumptions. Unified Astronomy Thesaurus concepts: Neutrino astronomy (1100); Core-collapse supernovae (304); Circumstellar matter (241); High-energy astrophysics (739) 1. Introduction model-dependent constraints on the fraction of supernovae type Ibc with a choked jet and the energy emitted in cosmic-rays IceCube has detected a diffuse flux of high-energy astro- (Esmaili & Murase 2018; Senno et al. 2018). physical neutrinos (Aartsen et al. 2013, 2015). The majority of Another possibility for producing high-energy neutrinos in the high-energy neutrinos follow an isotropic distribution, core-collapse supernovae (CCSNe) is through interactions of which suggests an extragalactic origin. The active galaxy NGC the SN ejecta with a dense circumstellar medium (CSM). 1068 was recently reported to be the first extragalactic point Strong stellar winds in the star’s late evolution stages or pre- source of high-energy neutrinos beyond the 4σ level (IceCube outburst could produce a sufficiently dense CSM (Ofek et al. Collaboration et al. 2022). While there is evidence that gamma- 2013; Strotjohann et al. 2021). When the supernova shock front ray blazars and tidal disruption events (TDEs) produce high- reaches this dense medium, efficient acceleration of charged energy neutrinos (Aartsen et al. 2018a, 2018b; Stein et al. 2021; particles on timescales ranging from a few tens of seconds to Reusch et al. 2022), the rate of observed coincidences ∼1000 days may occur (Murase et al. 2011; Zirakashvili & constrains the overall diffuse flux contribution of resolved Ptuskin 2016; Sarmah et al. 2022). CSM interactions can be gamma-ray blazars and TDEs to no more than 30% (Aartsen revealed through the detection of a combination of narrow and et al. 2017a) and 26% (Stein 2019), respectively, leaving the broad emission lines (as observed in type IIn SNe). The narrow majority of the diffuse flux unexplained. component of the spectral lines is produced by circumstellar In general, high-energy neutrinos are created through gas, which is ionized as the shock breaks out of the star. The interactions of high-energy protons with ambient matter or intermediate and broad components are produced by shocked, photon fields. Charged and neutral pions produced in those high-velocity SN ejecta, arising as a result of the collision of interactions decay to neutrinos and gamma-rays, respectively. the ejecta with circumstellar gas. Another indication might be a While gamma-rays can also be produced in leptonic processes long plateau in the SN light curve (as seen in Type IIP SNe), such as inverse Compton scattering, neutrinos are considered to which could be partly powered by SN shock breakout be a clear signature for hadronic interactions and thus also interaction with dense CSM (Moriya et al. 2011, 2012). Some cosmic-ray acceleration. IIP SNe show direct observational evidence for Several source classes have been proposed as candidate interactions (Mauerhan et al. 2013; Faran et al. 2014; Yaron neutrino (and cosmic-ray) sources. Among the most promising et al. 2017; Nakaoka et al. 2018). Studies find IIP supernovae are active galactic nuclei, gamma-ray bursts (GRBs) and to be viable candidates for neutrino production through supernovae (SNe)—see Kurahashi et al. (2022) for a recent interactions with the CSM (Murase 2018; Sarmah et al. review. While gamma-bright GRBs are strongly disfavored as the main contributor to the measured diffuse neutrino flux 2022). Pitik et al. (2022) found the high-energy neutrino IC200530A in spatial coincidence with the optical transient (Aartsen et al. 2017b), a large population of nearby low- AT2019fdr, which they interpret as a Type IIn superluminous luminosity bursts could still contribute significantly. The discovery of a connection between GRBs and type Ic-BL supernova. SNe implies that (mildly) relativistic jets should also exist in a Optical follow-up campaigns of IceCube high-energy neutrino alerts (Necker et al. 2022; Stein et al. 2022b) are fraction of core-collapse SNe (Razzaque et al. 2004; Ando & close to constraining the brightest observed superluminous Beacom 2005; Senno et al. 2016; Denton & Tamborra 2018), where such jets might be choked inside the envelope of the star. supernovae. In this scenario, the gamma-rays would be absorbed but the Here, for the first time, we probe different SN classes as neutrinos could still escape. A short neutrino burst (∼100 s) potential neutrino sources and calculate their possible contrib- ution to the observed diffuse neutrino flux. To search for cross- would be expected, in coincidence with the explosion time of the SNe (Senno et al. 2016). Past analyses did not find correlation between neutrinos and optically observed SNe, we significant correlation with high-energy neutrinos, and they put utilize data recorded by the IceCube Neutrino Observatory. 3 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. This paper is organized as follows: Section 2 describes the relevant data sets, followed by a discussion of the analysis methods in Section 3 and the presentation of the results in Section 4. Section 5 presents the constraints on the contribution of CCSNe to the diffuse neutrino flux. Section 6 summarizes the paper. Upper limits on the total energy released in neutrinos from individual SNe can be found in Appendix C. 2. The Data IceCube is a cubic-kilometer-sized neutrino detector, located in the transparent ice of the 2.8 km thick glacier covering the bedrock at the geographical South Pole (Aartsen et al. 2017c). Neutrino–nucleon interactions in the ice are detected indirectly, via Cherenkov light emission from secondary particles, by 5160 photomultiplier tubes. While charged-current interactions of muon neutrinos produce track-like signatures with subdegree Figure 1. Distance distribution of CSM SN sample and the stripped-envelope angular resolution, both charged-current interactions of elec- SN sample. The decrease at large distance is a result of limited detection tron and tau neutrinos as well as neutral-current interactions sensitivity and a selection bias toward brighter objects, which are easier to have angular resolutions of several degrees. This analysis classify spectroscopically. utilizes a selection of seven years of IceCube muon-track data that were optimized for point-source searches (Aartsen et al. 2017d), with roughly 700,000 events from years 2008 to 2014. and the background PDF is calculated similarly (Braun et al. The CCSN catalog for this analysis was compiled using 2010). The signal time PDF  corresponds to the expected publicly available records of optical detections of SNe. The neutrino flux as a function of time (light curve), and the primary sources were the WiseREP SN catalog (Yaron & Gal- background time PDF  assumes a constant background rate. Yam 2012) and the OpenSupernovaCatalog (Guillochon et al. The energy term  describes the expected neutrino energy 2017). In total, the compiled source sample contains 339 type 69 spectrum. As the data set is highly background-dominated, IIn SN, 198 type IIP SN, and 503 type Ib/c and type IIb SNe. we can safely assume that the signal contribution is negligible. The latter are referred to as stripped-envelope supernovae. Both The background energy proxy distribution is thus assumed to type IIn and type IIP SN are candidates for CSM interaction, follow the distribution observed in the data. The signal neutrino while stripped-envelope supernovae might host choked jets. In − γ energy distribution is described as a power-law function, E , Figure 1, the distance distribution of the two subsamples is where γ is the spectral index. For similar reasons, the shown. It should be noted that, while we did include many background spatial PDF as a function of decl. is chosen to supernovae in the analysis, we list only those of a smaller match the distribution of declinations found in the data. We subsample in Appendix A, as explained below. assume that the background spatial PDF is uniform in R.A., The distance was taken from the previously cited catalogs. 1 leading to  () df , =´  (d) for source decl. δ and ,dec 2p For cases in which entries were missing in the catalogs, the R.A. f. The signal spatial PDF,  , is assumed to follow a 2D distances were estimated using redshift measurements. The Gaussian distribution. ΛCDM model, with cosmological parameters measured by The likelihood function is maximized with respect to n and Planck (Ade et al. 2016), was used to convert from redshift to s γ. The best-fitted value n gives an estimate of the number of luminosity distance. We have assumed a peculiar motion of s −1 signal-like events, i.e., those that are likely to originate from a [300] km s , which also provides a lower distance limit for given SN. SNe with very small redshifts. SNe with neither distance nor We define the test statistic (TS) by redshift measurements were excluded from the catalog. The distance distribution peaks at about [100] Mpc, as can be seen (n ˆ , g ˆ) ⎛ ⎞ in Figure 1. l=´2log⎜⎟,3 () () 0 ⎝ ⎠ 3. Analysis Method where (n ˆ , gˆ) corresponds to the maximum of the likelihood To find an excess of neutrinos from the given SN positions function and() 0 to the null hypothesis, i.e., the case of neither and times, a time-dependent point-source likelihood method spatial nor temporal correlation of neutrinos and SNe (Braun (Braun et al. 2010) is used. The likelihood function is given by et al. 2008, 2010). N In principle, λ should follow a χ -distribution n n ss ⎛ ⎞ ⎛ ⎞ =+ ()nn1,- () (1) (Wilks 1938), in which case we could just use its analytical  ii N N ⎝ ⎠ ⎝ ⎠ i=1 form to describe the background distribution of the test statistic. However, in practice we constrain n to be positive where N is the number of neutrino events, ν is the ith neutrino, and n and γ are not independent, which causes deviations and n is the number of signal events.  and  are signal and 2 from the χ distribution. So instead, we estimate the background probability distribution functions (PDFs). Each background test statistic distribution by generating PDF is a product of a spatial term  , an energy term , and a time term  , which for the signal PDF can be expressed as For an astrophysical signal component in the data set with a spectral index 3 5 of γ = 2.5, we expect () 10 signal events and (10 ) atmospheric =´ ()g ´,2( )   background events, amounting to a signal contribution of <1%. 4 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. background-only pseudo-data sets and maximize the like- 4. Constraints on Supernova Subclasses lihood function with respect to n and γ. To be conservative In the following, we present results for selected individual and to avoid mismatches between simulations and data, we CCSNe, as well as for different subclasses of CCSNe. generate these data sets directly from the data. Because Stripped-envelope SNe, which might have choked jets, are IceCube is located at the South Pole, the distribution of the expected to emit a short burst of neutrinos in coincidence with data in R.A. is uniform and the background pseudo-data sets the SN explosion time (Senno et al. 2016). Motivated by can be generated by randomly sampling values for the R.A. theoretical uncertainties in the duration of the expected neutrino and shuffling the times of the neutrino events. This emission—and even larger uncertainties in the SNe explosion scrambling method is well established and preserves the time, due to sparse optical light-curve data—we used a box structureinenergyand decl. (see, e.g., Braun et al. 2008; function starting at 20 days before and extending up to the first Abbasi et al. 2022a, 2022b, 2022c). available optical data. This ensures the inclusion of the Given an experimental outcome and the background test explosion time for a typical SN even if the first detection exp statistic distribution P(λ), the p-value is computed as happened at peak time. All SN types were tested with box function PDFs of length pP = ()lld . exp 100, 300, and 1000 days, starting at the first available optical In addition to probing the neutrino fluxes from single SNe, data, because longer neutrino emission would be expected we combine the signal of a sample of SNe with a stacking under the scenario of CSM interaction. In addition, for SNe IIn analysis. Such a source stacking is implemented through a and IIP, light curves were tested of the form: weighted sum of the signal PDFs  of individual SNe j: -1 ⎛ ⎞ () t µ+1, (6) ⎜⎟  = w,4 () å jj pp ⎝ ⎠ where values of 0.02, 0.2, and 2 yr were used for the where the weights w represent the expected signal strength of characteristic timescale constant t ,as proposed byZirakashvili pp the sources. In this analysis, the weights are assumed to be &Ptuskin (2016). proportional to We first applied the maximum likelihood method described above to a selection of individual SNe, which were identified t E end max n -g based on their expected relative signal strength w as promising. w µ ´ LE A dtdE,5 () j j eff 2 òò t E D start min We did not find a statistically significant excess for any of the    Time Dependence selected sources. Source Properties The resulting upper limits on the total energy emitted in 2 7 −2 neutrinos between [ 10 ] GeV and [ 10 ] GeV, assuming an E with Φ as the intrinsic neutrino power of the sources, D as 0 p n power-law spectrum, are presented in Appendix C. In the the proper distance (Hogg 1999) of the SN, L () t the conversion from the number of neutrino events to flux, the − γ estimated neutrino light curve, E the neutrino energy systemic uncertainty is estimated to be about 11%, mainly spectrum, and A (t, δ , E) the effective area, the energy E, eff j arising from uncertainties in the optical properties of the ice and the decl. of the source δ. The effective area is time- and detector effects (Coenders 2016). 49 50 dependent, because the data set covers several distinct phases The individual upper limits range from 10 to 6.5 × 10 of detector construction. The weighting scheme assumes a erg, which corresponds to 1%–65% of the typical bolometric standard candle ansatz, since we assume the same Φ for each electromagnetic energy released in SNe. As the individual source. It is very sensitive to the estimated source distances, stripped-envelope and IIP SNe are typically closer than the IIn, we generally obtain more stringent limits for these objects. which can have large uncertainties. In order to improve our sensitivity, we performed a stacking A more detailed investigation of the supernova light curves analysis, looking for a combined excess from a catalog instead could mitigate these uncertainties, but the optical light curves of individual sources. As explained above, we separate of the supernovae in our catalog are typically sparse and make supernovae into SNe type IIn, SNe type IIP, and stripped- detailed modeling complicated. Wrongly estimated weights envelope SNe. It is worth noting that we decided to treat types will impact the sensitivity of the analysis, so for the first time in IIn and IIP separately because the presence of CSM interaction an IceCube analysis, we use a novel method of directly fitting in IIP is less certain. the weights w . Adding the flux per source as an additional free Each of the three subcatalogs was split into two samples: a parameter to the maximum likelihood removes the standard bright sample of nearby sources, containing about 70% of the candle assumption and also the dependence on the SN distance expected signal; and a larger sample, containing the remaining estimate, but it requires a more advanced numerical procedure dimmer sources. The bright samples include about 10 SN each, to maximize the likelihood function. To test the power of this depending on the SN class and the model. The catalogs of the method, we simulated five sources with random positions on bright samples are listed in Appendix A. Testing both samples the sky and respective weights. We then perturbed the weights independently allowed us to benefit from the better optical according to a log-normal distribution and used them to observations of the nearby sources in the small sample but also compute the sensitivity of the standard, fixed-weights like- utilize the larger statistics in the large sample. Because each lihood. Comparing to this, we find an improvement of up to source adds a free parameter in the likelihood maximization 40% when using the fitting-weights likelihood. We applied this when fitting the weights, this was only feasible for the smaller method in addition to the traditional standard candle one, yielding two separate results. Calculated by integrating over time. 5 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. bright sample. This sample contains(10) sources, which is a manageable amount of fit parameters. For the large sample, the standard candle ansatz was applied instead. The p-values are given in Appendix B. The most significant pre-trial p-value is 0.62%, and it is found in the search for neutrinos from the large sample of type IIP SNe in a 1000 day- long box-shaped light curve. However, this corresponds to a post-trial p-value of 19.5%, after accounting for the multiple tested scenarios through simulated pseudo-experiments of the ensemble of p-values, and it is thus consistent with background expectations. If this excess were due to astrophysical neutrinos, one would expect a corresponding excess in the sample of nearby type IIP SNe, where we do not find such an excess. The second-smallest p-value of 6.3% is found for the nearby type IIn SNe in the case of the fitted weights for the box-shaped light-curve model. The overall deviation of all tested scenarios from the background expectation using a Kolmogorov– Smirnov test leads to a p-value of 29%. To be conservative, we use the result from the fitting-weights analysis in the rest of the paper, as it resulted in weaker upper limits on the total emitted neutrino energy. Including systematic uncertainties, those are shown in Figure 2 for both models of the neutrino light curve. These limits assume that SNe within each category behave as neutrino standard candles. The stacking result provides us with stronger limits than individual source limits. We find that SNe type IIn emit less 49 48 than 1.3 × 10 erg and type IIP less than 2.4 × 10 erg, while the strongest limits for stripped-envelope SNe of 4.5 × 10 erg are obtained from the choked-jet scenario. If the longer box models that are associated with CSM interaction are assumed, Figure 2. Upper limits on total neutrino (nn + ¯ ) energy assuming a box-like mm -1 then the strongest limit becomes 2.7 × 10 erg. In general, the neutrino light curve (upper panel) and assuming a L µ+ 1 neutrino () t pp box time window provides tighter constraints for CSM- light curve as predicted by Zirakashvili & Ptuskin (2016). The energy ranges interacting SNe compared to the specific light-curve model of are the same as indicated in Figure 3. The model predictions by Murase et al. Zirakashvili & Ptuskin (2016). (2011) and Zirakashvili & Ptuskin (2016) are shown as red squares for comparison. 5. Diffuse Neutrino Flux Using the limits on neutrino energy obtained in the stacking of Figure 3 for a spectral index of γ = 2.0 as motivated by analysis (shown in Figure 2), we can estimate the maximal theoretical models (Murase 2018; Sarmah et al. 2022). contribution from the entire cosmological population of SNe to Following a data-driven approach, the top panel shows the the measured diffuse neutrino flux (Aartsen et al. 2015). Using limits for a spectral index of γ = 2.5 as motivated by the central the CCSNe rate density found by Strolger et al. (2015), r (z), value of the global fit diffuse neutrino flux (Aartsen et al. the diffuse flux is computed following the procedure in Ahlers 2015). Assuming the choked-jet scenario, stripped-envelope & Halzen (2014) assuming a 1:1:1 (ν : ν : ν ) neutrino flavor e μ τ SNe cannot contribute more than 14.6% of the observed diffuse ratio at Earth. It is worth noting that we assume the rate for the individual subclasses scales according to the corresponding neutrino flux. Assuming interaction with the CSM, stripped- percentage in the local Universe (Li et al. 2011). The diffuse envelope SNe and SNe type IIn can explain no more than flux is given by 26.6% and 33.9%, respectively. We mildly constrain the contribution of SNe type IIP to be less than 59.9%. We note 1 r () z dN c that the limit for type IIP SNe seems weaker when translating it f() E = dz,7 () 41 p 0 + z dE Hz () to a component of the diffuse flux, because they are the most abundant supernova type (Li et al. 2011). where dNdE is the time-integrated spectral density upper limit For stripped-envelope SNe, this analysis is complementary for each SN subclass, assuming that the subclass behaves as a to that of Chang et al. (2022), who take into account the neutrino standard candle class with a power-law energy fraction of supernovae f that harbor a choked-jet pointing in jet spectrum and that the power law holds over our sensitive our line of sight to arrive at a limit on the contribution to the energy range. This energy range is calculated by finding the diffuse flux that is about ten times less stringent. Because we energy bound for selecting simulated signal events. We find the assume the supernovae of each subclass to be standard candles values where our sensitivity drops by 5% for the lower and when deriving the upper limits on the total emitted neutrino upper bounds separately. The range between both values is our energy in Section 4, our results are robust for f ≈ 1 but they jet 90% energy range. will be less stringent for f = 1. jet The resulting upper limits on the contribution of different SN This analysis has different sensitivities for different energy types to the diffuse neutrino flux are shown in the bottom panel ranges; see Figure 4. The region of greatest sensitivity is 6 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. 6. Conclusion We have presented a search for neutrinos from certain types of CCSNe with IceCube. In a stacking analysis, we correlated more than 1000 SNe from optical surveys with roughly 700,000 muon-track events recorded by IceCube. The standard stacking method was extended to allow for fitting of individual weights for each source, in order to account for expected variation in the neutrino flux from individual sources. Type IIn SNe, type IIP SNe, and stripped-envelope SNe were tested individually with various neutrino emission time models. No significant temporal and spatial correlation of neutrinos and the cataloged SNe was found, allowing us to set upper limits on the contribution of those SNe to the diffuse neutrino flux. Type IIn CCSNe, type IIP CCSNe, and stripped-envelope SNe contribute less than 34%, 60%, and 27%, respectively, to the diffuse neutrino flux at the 90% confidence level, assuming CSM interaction and an extrapolation of the diffuse neutrino spectrum to low energies following an unbroken power law with index −2.5. This also assumes a choked-jet, stripped- envelope SNe cannot contribute more than 15%. Upper limits on the total neutrino energy emitted by a single CSM-interacting source are at levels comparable to model predictions by Murase et al. (2011)(see Figure 2), while model predictions from Zirakashvili & Ptuskin (2016) are strongly disfavored. It should be noted that the model prediction could easily be adjusted to lower neutrino flux predictions by assuming a lower CSM density or a lower kinetic SN energy. Improvements to the presented limits are expected in the near future with optical survey instruments such as the Zwicky Figure 3. Upper limit on the contribution of different SN types to the diffuse −2.5 −2.0 Transient Factory (Graham et al. 2019), which is able to neutrino flux (nn + ¯ ) assuming an E (top panel) and E (bottom panel) mm undertake a high-cadence survey across a large fraction of the energy spectrum compared with the measured diffuse astrophysical neutrino flux (gray band). The limits are derived from the corresponding strictest limit in sky, providing SN catalogs with much greater completeness. In Figure 2. The choked-jet model refers to the 20 day box model, as explained in combination with next-generation neutrino telescopes, this will Section 4. The energy range plotted here is the central 90% energy range of the significantly boost the sensitivity of this type of analysis, analyzed neutrino sample. allowing us to probe dimmer neutrino emitters and smaller contributions of CCSNe to the diffuse neutrino flux. The IceCube collaboration acknowledges the significant contributions to this manuscript from Jannis Necker, Alexander Stasik, and Robert Stein. We also gratefully acknowledge support from: USA—the U.S. National Science Foundation– Office of Polar Programs, the U.S. National Science Founda- tion–Physics Division, the U.S. National Science Foundation– EPSCoR, the Wisconsin Alumni Research Foundation, the Center for High Throughput Computing (CHTC) at the University of Wisconsin–Madison, the Open Science Grid (OSG), Advanced Cyberinfrastructure Coordination Ecosys- tem: Services & Support (ACCESS), the Frontera computing project at the Texas Advanced Computing Center, the U.S. Figure 4. Differential sensitivity as a function of energy for different source Department of Energy–National Energy Research Scientific declinations δ with one year of experimental data. The maximum sensitivity is 5 Computing Center, the Particle Astrophysics Research Com- achieved around [ 10 ] GeV for sources located in the northern sky and close to puting Center at the University of Maryland, the Institute for the equator. For sources located in the southern sky, the overall sensitivity is much worse, but it also peaks at higher energies of [ 10 ] GeV. Cyber-Enabled Research at Michigan State University, and the Astroparticle Physics Computational Facility at Marquette around 10–100 TeV. It can reach to higher energies as well, University; Belgium—Funds for Scientific Research (FRS- depending on the source decl. This broadly overlaps with the FNRS and FWO), the FWO Odysseus and Big Science energy range in which the diffuse IceCube neutrino flux global programmes, and the Belgian Federal Science Policy Office fit was measured. The quoted upper limits to the diffuse flux (Belspo); Germany—Bundesministerium für Bildung und contribution are thus not strongly dependent on the extrapola- Forschung (BMBF), Deutsche Forschungsgemeinschaft (DFG), tion of the measured diffuse flux to lower energies, where the Helmholtz Alliance for Astroparticle Physics (HAP),the flux has not yet been measured due to large atmospheric Initiative and Networking Fund of the Helmholtz Association, background. Deutsches Elektronen Synchrotron (DESY), and the High 7 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Performance Computing Cluster of the RWTH Aachen; Sweden —the National Research Foundation of Korea (NRF); Switzer- —the Swedish Research Council, the Swedish Polar Research land—the Swiss National Science Foundation (SNSF);United Secretariat, the Swedish National Infrastructure for Computing Kingdom—Oxford University, Department of Physics. (SNIC), and the Knut and Alice Wallenberg Foundation; Facilities: HST(STIS), Swift(XRT and UVOT), AAVSO, CTIO:1.3 m, CTIO:1.5 m, CXO. European Union—EGI Advanced Computing for Research; Software: flarestack (Stein et al. 2022a). Australia—the Australian Research Council; Canada—the Natural Sciences and Engineering Research Council of Canada, Calcul Québec, Compute Ontario, the Canada Foundation for Appendix A Innovation, WestGrid, and Compute Canada; Denmark—Villum Catalogs Fonden, the Carlsberg Foundation, and the European Commis- sion; New Zealand—the Marsden Fund; Japan—the Japan Tables 1, 2, and 3 list the supernova catalogues used in the Society for Promotion of Science (JSPS) and the Institute for fitting weights analysis as described in Section 4. Global Prominent Research (IGPR) of Chiba University; Korea Table 1 Interacting Supernovae Catalog Name R.A. Decl. Discovery Date Redshift Distance Source (rad)(rad)(Mpc) SN1999bw 2.70 0.79 1999-00-20 0.0032 9.80 1, 2 SN2002bu 3.22 0.80 2002-00-28 0.0030 8.90 1, 2, 3 SN2008S 5.39 1.05 2008-00-01 0.0012 5.60 4 SN2009kr 1.36 −0.27 2009-00-06 0.0075 16.00 5 SN2010jl 2.54 0.17 2010-00-03 0.0117 49.00 6 SN2011an 2.09 0.29 2011-00-01 0.0170 73.00 7 SN2011ht 2.65 0.90 2011-00-29 0.0046 19.20 8 SN2012ab 3.24 0.10 2012-00-31 0.0190 81.00 9 SN2013by 4.29 −1.05 2013-00-23 0.0038 14.80 10, 11 SN2013gc 2.13 −0.49 2013-00-07 0.0044 15.10 12 PSN J14041297-0938168 3.68 −0.17 2013-00-20 0.0038 12.55 13 CSS140111:060437-123740 1.59 −0.22 2013-00-24 0.0084 32.88 13 SN2014G 2.86 0.95 2014-00-14 0.0045 20.00 14 MASTER OT J044212.20+230616.7 1.23 0.40 2014-00-21 0.0170 72.00 15 SN2015da 3.63 0.69 2015-00-09 0.0079 32.14 16, 17 References. (1) Kochanek et al. 2012; (2) Smith et al. 2011; (3) Szczygiełet al. 2012; (4) Stanishev et al. 2008; (5) Steele et al. 2009a; (6) Benetti et al. 2010; (7) Marion & Calkins 2011; (8) Prieto et al. 2011; (9) Bilinski et al. 2018; (10) Margutti et al. 2013; (11) Parker et al. 2013; (12) Antezana et al. 2013; (13) Challis 2013; (14) Denisenko et al. 2014; (15) Shivvers et al. 2014; (16) Zhang & Wang 2015; (17) Tartaglia et al. 2020. 8 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Table 2 IIP Catalog Name R.A. Decl. Discovery Date Redshift Distance Source (rad)(rad)(Mpc) SN1999em 1.23 −0.05 1999-00-29 0.0034 7.50 1 SN2004dj 2.00 1.14 2004-00-31 0.0014 3.50 2 SN2004et 5.39 1.05 2004-00-27 0.0022 7.70 3, 4 SN2005cs 3.53 0.82 2005-00-28 0.0030 7.10 5, 6 SN2006ov 3.24 0.08 2006-00-24 0.0062 14.00 7 SN2008bk 6.27 −0.57 2008-00-25 0.0018 4.00 8 SN2009js 0.64 0.32 2009-00-11 0.0060 16.00 9 SN2009md 2.83 0.22 2009-00-05 0.0046 18.00 10 SN2009mf 0.27 0.83 2009-00-07 0.0087 23.00 11 SN2011dq 0.26 −0.13 2011-00-15 0.0055 24.40 12 SN2012A 2.73 0.30 2012-00-07 0.0034 9.80 13 SN2012aw 2.81 0.20 2012-00-16 0.0036 9.90 14 SNhunt141 3.57 −0.31 2012-00-24 0.0040 18.00 15 SN2012ec 0.72 −0.13 2012-00-12 0.0057 18.76 16 SN2013ab 3.81 0.17 2013-00-17 0.0063 23.64 17 SN2013am 2.96 0.23 2013-00-21 0.0037 12.77 18 SN2013bu 5.92 0.60 2013-00-21 0.0027 12.07 19 SN2013ej 0.42 0.28 2013-00-25 0.0020 9.00 20 SN2011ja 3.43 −0.86 2014-00-14 0.0018 3.36 21 SN2014bc 3.22 0.83 2014-00-19 0.0025 7.60 22 References. (1) Jha et al. 1999; (2) Patat et al. 2004; (3) Zwitter et al. 2004; (4) Li et al. 2005; (5) Modjaz et al. 2005; (6) Pastorello et al. 2009; (7) Li et al. 2007; (8) Morrell & Stritzinger 2008; (9) Gandhi et al. 2013; (10) Sollerman et al. 2009; (11) Steele et al. 2009b; (12) Valenti & Benetti 2011; (13) Stanishev & Pursimo 2012; (14) Quadri et al. 2012; (15) Cellier-Holzem et al. 2012; (16) Monard et al. 2012; (17) Bose et al. 2015; (18) Benetti et al. 2013; (19) Itagaki et al. 2013; (20) Dhungana et al. 2016; (21) Andrews et al. 2016; (22) Ochner et al. 2014. Table 3 Stripped-envelope Supernovae Catalog Name R.A. Decl. Discovery Date Redshift Distance Source (rad)(rad)(Mpc) SN2007gr 0.71 0.65 2007-00-15 0.0027 9.30 1, 2 SN2008ax 3.28 0.73 2008-00-03 0.0029 9.60 3, 4 SN2008dv 0.95 1.27 2008-00-01 0.0084 4.20 5 SN2009dq 2.66 −1.17 2009-00-24 0.0046 16.00 6 SN2009gj 0.13 −0.58 2009-00-21 0.0053 17.00 7 SN2009mk 0.03 −0.72 2009-00-15 0.0050 22.00 8, 9 SN2009mu 2.58 −0.58 2009-00-21 0.0098 25.00 10 SN2010br 3.16 0.78 2010-00-10 0.0033 13.00 11 SN2010gi 4.55 1.32 2010-00-18 0.0041 18.20 12 SN2011dh 3.53 0.82 2011-00-01 0.0025 8.40 5 SN2011jm 3.38 0.05 2011-00-24 0.0041 14.00 13 SN2012P 3.93 0.03 2012-00-22 0.0055 20.10 14, 15 SN2012cw 2.68 0.06 2012-00-14 0.0055 19.92 16, 17 SN2012fh 2.81 0.43 2012-00-18 0.0029 8.58 18, 19, 20 SN2013df 3.26 0.55 2013-00-07 0.0033 10.58 21, 22 iPTF13bvn 3.93 0.03 2013-00-17 0.0055 19.94 15, 23, 24, 25 MASTER OT J120451.50+265946.6 3.16 0.47 2013-00-02 0.0029 8.38 26, 27, 28 SN2013ge 2.77 0.38 2013-00-08 0.0054 19.34 29, 30 SN2014C 5.92 0.60 2014-00-05 0.0037 12.07 31, 32, 33 References. (1) Chornock et al. 2007; (2) Valenti et al. 2008; (3) Chornock et al. 2008; (4) Pastorello et al. 2008; (5) Silverman et al. 2008; (6) Anderson et al. 2009; (7) Stockdale et al. 2009; (8) Chornock & Berger 2009; (9) Marples & Drescher 2009; (10) Stritzinger et al. 2010; (11) Maxwell et al. 2010; (12) Yamanaka et al. 2010; (13) Foley & Fong 2011; (14) Borsato et al. 2012; (15) Fremling et al. 2016; (16) Itagaki et al. 2012; (17) Wang et al. 2012; (18) Johnson et al. 2017; (19) Takaki et al. 2012; (20) Tomasella et al. 2012; (21) Ciabattari et al. 2013; (22) Van Dyk et al. 2014; (23) Cao et al. 2013; (24) Milisavljevic et al. 2013; (25) Srivastav et al. 2014a; (26) Chandra et al. 2019; (27) Singh et al. 2019; (28) Srivastav et al. 2014b; (29) Drout et al. 2016; (30) Nakano et al. 2013; (31) Kim et al. 2014; (32) Milisavljevic et al. 2015; (33) Tinyanont et al. 2016. 9 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Appendix B P-values [%] Table 4 lists the pre-trial P-values of the fitted weights model of different length and for the CSM model of scenario given as percentages for a box-shaped light-curve Zirakashvili & Ptuskin (2016) for different choices of t . pp Table 4 Pre-trial P-values Box Length (days) t (yr) pp [−20, 0][0, 100][0, 300][0, 10000] 0.02 0.2 2.0 IIn L 8.6 6.3 >50 >50 >50 30.1 IIP L 48.6 >50 27.6 >50 >50 21.6 Stripped-envelope >50 >50 >50 34.8 LL L 10 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. −2 Appendix C assume a generic neutrino energy spectrum of E , rather than Upper Limits on Individual Sources tying them to the observed diffuse spectral shape, and an emission time window of 100 days. Table 5 lists IIn SNe, This section shows upper limits on individual SNe. Sources Table 6 IIP SNe, and Table 7 the stripped-envelope SNe. were selected based on their expected neutrino signal. Here, we Table 5 Upper Limits on Selected Type IIn SNe Name R.A. Decl. Discovery Date Distance Energy Upper Limit (rad)(rad)(Mpc)(10 erg) CSS140111:060437-123740 1.59 −0.22 2013-12-24 31.8 49.8 PSN J13522411+3941286 3.63 0.693 2015-01-09 32.1 16.8 PSN J14041297-0938168 3.68 −0.168 2013-12-20 12.5 4.8 PTF10aaxf 2.54 0.166 2010-11-03 52.3 29.5 SN2008S 5.39 1.049 2008-02-01 5.6 5.3 SN2009kr 1.36 −0.274 2009-11-06 16.0 19.1 SN2011an 2.09 0.287 2011-03-01 73.0 65.3 SN2011ht 2.65 0.905 2011-09-29 19.2 6.6 SN2012ab 3.24 0.098 2012-01-31 81.0 64.18 SN2013gc 2.13 −0.49 2013-11-07 15.1 28.4 Table 6 Upper Limits on Selected Type IIP SNe Discovery Energy Upper Name R.A. Decl. Date Distance Limit (rad)(rad)(Mpc)(10 erg) iPTF13aaz 2.96 0.228 2013-03-21 16.4 1.0 SN2012A 2.73 0.299 2012-01-07 9.0 1.0 SN2012aw 2.81 0.204 2012-03-16 9.6 1.0 SN2014bc 3.22 0.826 2014-05-19 7.6 3.0 Table 7 Upper Limits on Selected Stripped-envelope SNe (Ib/c and IIb) Energy Discovery Upper Name R.A. Decl. Date Distance Limit (rad)(rad)(Mpc)(10 erg) iPTF13bvn 3.93 0.033 2013-06-17 25.8 4.0 MASTER OT 3.16 0.471 2014-10-28 15.0 1.0 J120451.50 PTF11eon 3.53 0.823 2011-06-01 8.0 1.1 SN2008ax 3.28 0.727 2008-03-03 5.1 1.6 SN2008dv 0.95 1.267 2008-07-01 10.6 1.2 SN2010br 3.16 0.777 2010-04-10 9.9 4.1 SN2011jm 3.38 0.046 2011-12-24 14.0 1.8 SN2012cw 2.68 0.06 2012-06-14 31.3 4.3 SN2012fh 2.81 0.434 2012-10-18 8.6 1.1 SN2013df 3.26 0.545 2013-06-07 10.6 1.7 SN2014C 5.92 0.601 2014-01-05 12.1 2.3 11 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. ORCID iDs E. Ganster https://orcid.org/0000-0003-4393-6944 A. Garcia https://orcid.org/0000-0002-8186-2459 R. Abbasi https://orcid.org/0000-0001-6141-4205 S. Garrappa https://orcid.org/0000-0003-2403-4582 M. Ackermann https://orcid.org/0000-0001-8952-588X A. Ghadimi https://orcid.org/0000-0002-6350-6485 S. K. Agarwalla https://orcid.org/0000-0002-9714-8866 C. Glaser https://orcid.org/0000-0001-5998-2553 J. A. 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Constraining High-energy Neutrino Emission from Supernovae with IceCube

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G.; Thwaites, J.; Tilav, S.; Tollefson, K.; Tönnis, C.; Toscano, S.; Tosi, D.; Trettin, A.; Tung, C. F.; Turcotte, R.; Twagirayezu, J. P.; Ty, B.; Unland Elorrieta, M. A.; Upadhyay, A. K.; Upshaw, K.; Valtonen-Mattila, N.; Vandenbroucke, J.; van Eijndhoven, N.; Vannerom, D.; van Santen, J.; Vara, J.; Veitch-Michaelis, J.; Venugopal, M.; Verpoest, S.; Veske, D.; Walck, C.; Watson, T. B.; Weaver, C.; Weigel, P.; Weindl, A.; Weldert, J.; Wendt, C.; Werthebach, J.; Weyrauch, M.; Whitehorn, N.; Wiebusch, C. H.; Willey, N.; Williams, D. R.; Wolf, M.; Wrede, G.; Wulff, J.; Xu, X. W.; Yanez, J. P.; Yildizci, E.; Yoshida, S.; Yu, F.; Yu, S.; Yuan, T.; Zhang, Z.; Zhelnin, P.; ,
The Astrophysical Journal Letters , Volume 949 (1): 14 – May 1, 2023
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Publisher
IOP Publishing
Copyright
© 2023. The Author(s). Published by the American Astronomical Society.
ISSN
2041-8205
eISSN
2041-8213
DOI
10.3847/2041-8213/acd2c9
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See Article on Publisher Site

Abstract

The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 https://doi.org/10.3847/2041-8213/acd2c9 © 2023. The Author(s). Published by the American Astronomical Society. 1 2 3 4,65 5 6 7 R. Abbasi , M. Ackermann , J. Adams , S. K. Agarwalla , J. A. Aguilar , M. Ahlers , J. M. Alameddine , 8 9 10 11 4 2 8 12 N. M. Amin , K. Andeen , G. Anton , C. Argüelles , Y. Ashida , S. Athanasiadou , S. N. Axani , X. Bai , 4 4 13 4 14 15,16 17 A. Balagopal V. , M. Baricevic , S. W. Barwick , V. Basu , R. Bay , J. J. Beatty , K.-H. Becker , 18,66 19 20 21 22 23 24 J. Becker Tjus , J. Beise , C. Bellenghi , S. BenZvi , D. Berley , E. Bernardini , D. Z. Besson , 14,25 17 22 2 26 11 23 27 G. Binder , D. Bindig , E. Blaufuss , S. Blot , F. Bontempo , J. Y. Book , C. Boscolo Meneguolo , S. Böser , 19 28 6 4 29 2 30 31 O. Botner , J. Böttcher , E. Bourbeau , J. Braun , B. Brinson , J. Brostean-Kaiser , R. T. Burley , R. S. Busse , 4 32 11 30 4,65 29 33 D. Butterfield , M. A. Campana , K. Carloni , E. 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Valtonen-Mattila , J. Vandenbroucke , 36 35 2 31 4 26 60 N. van Eijndhoven , D. Vannerom , J. van Santen ,J.Vara , J. Veitch-Michaelis , M. Venugopal , S. Verpoest , 37 41 52 43 35 26 38,39 4 D. Veske ,C.Walck ,T. B.Watson , C. Weaver ,P. Weigel , A. Weindl ,J. Weldert ,C.Wendt , 7 26 43,57 28 43 40 20 10 J. Werthebach , M. Weyrauch , N. Whitehorn ,C. H.Wiebusch ,N. Willey , D. R. Williams ,M. Wolf ,G.Wrede , 18 45 55 4 50 11 43 4 33 11 J. Wulff ,X. W. Xu ,J.P. Yanez , E. Yildizci ,S.Yoshida ,F. Yu ,S. Yu , T. Yuan ,Z.Zhang , and P. Zhelnin IceCube Collaboration Department of Physics, Loyola University Chicago, Chicago, IL 60660, USA Deutsches Elektronen-Synchrotron DESY, Platanenallee 6, D-15738 Zeuthen, Germany Dept. of Physics and Astronomy, University of Canterbury, Private Bag 4800, Christchurch, New Zealand 1 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Dept. of Physics and Wisconsin IceCube Particle Astrophysics Center, University of Wisconsin-Madison, Madison, WI 53706, USA Université Libre de Bruxelles, Science Faculty CP230, B-1050 Brussels, Belgium Niels Bohr Institute, University of Copenhagen, DK-2100 Copenhagen, Denmark Dept. of Physics, TU Dortmund University, D-44221 Dortmund, Germany Bartol Research Institute and Dept. of Physics and Astronomy, University of Delaware, Newark, DE 19716, USA Department of Physics, Marquette University, Milwaukee, WI 53201, USA Erlangen Centre for Astroparticle Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, D-91058 Erlangen, Germany Department of Physics and Laboratory for Particle Physics and Cosmology, Harvard University, Cambridge, MA 02138, USA Physics Department, South Dakota School of Mines and Technology, Rapid City, SD 57701, USA Dept. of Physics and Astronomy, University of California, Irvine, CA 92697, USA Dept. of Physics, University of California, Berkeley, CA 94720, USA Dept. of Astronomy, Ohio State University, Columbus, OH 43210, USA Dept. of Physics and Center for Cosmology and Astro-Particle Physics, Ohio State University, Columbus, OH 43210, USA Dept. of Physics, University of Wuppertal, D-42119 Wuppertal, Germany Fakultät für Physik & Astronomie, Ruhr-Universität Bochum, D-44780 Bochum, Germany Dept. of Physics and Astronomy, Uppsala University, Box 516, SE-75120 Uppsala, Sweden Physik-department, Technische Universität München, D-85748 Garching, Germany Dept. of Physics and Astronomy, University of Rochester, Rochester, NY 14627, USA Dept. of Physics, University of Maryland, College Park, MD 20742, USA Dipartimento di Fisica e Astronomia Galileo Galilei, Università Degli Studi di Padova, I-35122 Padova PD, Italy Dept. of Physics and Astronomy, University of Kansas, Lawrence, KS 66045, USA Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA Karlsruhe Institute of Technology, Institute for Astroparticle Physics, D-76021 Karlsruhe, Germany Institute of Physics, University of Mainz, Staudinger Weg 7, D-55099 Mainz, Germany III. Physikalisches Institut, RWTH Aachen University, D-52056 Aachen, Germany School of Physics and Center for Relativistic Astrophysics, Georgia Institute of Technology, Atlanta, GA 30332, USA Department of Physics, University of Adelaide, Adelaide, 5005, Australia Institut für Kernphysik, Westfälische Wilhelms-Universität Münster, D-48149 Münster, Germany Dept. of Physics, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA Dept. of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794-3800, USA Dept. of Physics, Sungkyunkwan University, Suwon 16419, Republic of Korea Dept. of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Vrije Universiteit Brussel (VUB), Dienst ELEM, B-1050 Brussels, Belgium Columbia Astrophysics and Nevis Laboratories, Columbia University, New York, NY 10027, USA Dept. of Astronomy and Astrophysics, Pennsylvania State University, University Park, PA 16802, USA Dept. of Physics, Pennsylvania State University, University Park, PA 16802, USA Dept. of Physics and Astronomy, University of Alabama, Tuscaloosa, AL 35487, USA Oskar Klein Centre and Dept. of Physics, Stockholm University, SE-10691 Stockholm, Sweden Centre for Cosmology, Particle Physics and Phenomenology—CP3, Université catholique de Louvain, Louvain-la-Neuve, Belgium Dept. of Physics and Astronomy, Michigan State University, East Lansing, MI 48824, USA Karlsruhe Institute of Technology, Institute of Experimental Particle Physics, D-76021 Karlsruhe, Germany Dept. of Physics, Southern University, Baton Rouge, LA 70813, USA Institute of Physics, Academia Sinica, Taipei, 11529, Taiwan Institut für Physik, Humboldt-Universität zu Berlin, D-12489 Berlin, Germany Dept. of Astronomy, University of Wisconsin-Madison, Madison, WI 53706, USA Dept. of Physics, Engineering Physics, and Astronomy, Queen’s University, Kingston, ON K7L 3N6, Canada Dept. of Physics and The International Center for Hadron Astrophysics, Chiba University, Chiba 263-8522, Japan CTSPS, Clark-Atlanta University, Atlanta, GA 30314, USA Dept. of Physics, University of Texas at Arlington, 502 Yates St., Science Hall Rm 108, Box 19059, Arlington, TX 76019, USA Department of Physics & Astronomy, University of Nevada, Las Vegas, NV 89154, USA Nevada Center for Astrophysics, University of Nevada, Las Vegas, NV 89154, USA Dept. of Physics, University of Alberta, Edmonton, Alberta, T6G 2E1, Canada Département de physique nucléaire et corpusculaire, Université de Genève, CH-1211 Genève, Switzerland Department of Physics and Astronomy, UCLA, Los Angeles, CA 90095, USA Dept. of Physics, Yale University, New Haven, CT 06520, USA Department of Physics, Mercer University, Macon, GA 31207-0001, USA Dept. of Physics and Astronomy, University of Gent, B-9000 Gent, Belgium Dept. of Physics and Astronomy, University of Alaska Anchorage, 3211 Providence Dr., Anchorage, AK 99508, USA Department of Physics and Astronomy, University of Utah, Salt Lake City, UT 84112, USA Dept. of Physics, University of Oxford, Parks Road, Oxford OX1 3PU, UK Dept. of Physics, University of Wisconsin, River Falls, WI 54022, USA Received 2023 March 3; revised 2023 May 2; accepted 2023 May 5; published 2023 May 22 analysis@icecube.wisc.edu Also at Institute of Physics, Sachivalaya Marg, Sainik School Post, Bhubaneswar 751005, India. Also at Department of Space, Earth and Environment, Chalmers University of Technology, 412 96 Gothenburg, Sweden. Also at Earthquake Research Institute, University of Tokyo, Bunkyo, Tokyo 113-0032, Japan. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. 2 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Abstract Core-collapse supernovae are a promising potential high-energy neutrino source class. We test for correlation between seven years of IceCube neutrino data and a catalog containing more than 1000 core-collapse supernovae of types IIn and IIP and a sample of stripped-envelope supernovae. We search both for neutrino emission from individual supernovae as well as for combined emission from the whole supernova sample, through a stacking analysis. No significant spatial or temporal correlation of neutrinos with the cataloged supernovae was found. All scenarios were tested against the background expectation and together yield an overall p-value of 93%; therefore, they show consistency with the background only. The derived upper limits on the total energy emitted in neutrinos 48 48 49 are 1.7 × 10 erg for stripped-envelope supernovae, 2.8 × 10 erg for type IIP, and 1.3 × 10 erg for type IIn SNe, the latter disfavoring models with optimistic assumptions for neutrino production in interacting supernovae. We conclude that stripped-envelope supernovae and supernovae of type IIn do not contribute more than 14.6% and 3 5 33.9%, respectively, to the diffuse neutrino flux in the energy range of about [ 10 –10 ] GeV, assuming that the neutrino energy spectrum follows a power-law with an index of −2.5. Under the same assumption, we can only constrain the contribution of type IIP SNe to no more than 59.9%. Thus, core-collapse supernovae of types IIn and stripped-envelope supernovae can both be ruled out as the dominant source of the diffuse neutrino flux under the given assumptions. Unified Astronomy Thesaurus concepts: Neutrino astronomy (1100); Core-collapse supernovae (304); Circumstellar matter (241); High-energy astrophysics (739) 1. Introduction model-dependent constraints on the fraction of supernovae type Ibc with a choked jet and the energy emitted in cosmic-rays IceCube has detected a diffuse flux of high-energy astro- (Esmaili & Murase 2018; Senno et al. 2018). physical neutrinos (Aartsen et al. 2013, 2015). The majority of Another possibility for producing high-energy neutrinos in the high-energy neutrinos follow an isotropic distribution, core-collapse supernovae (CCSNe) is through interactions of which suggests an extragalactic origin. The active galaxy NGC the SN ejecta with a dense circumstellar medium (CSM). 1068 was recently reported to be the first extragalactic point Strong stellar winds in the star’s late evolution stages or pre- source of high-energy neutrinos beyond the 4σ level (IceCube outburst could produce a sufficiently dense CSM (Ofek et al. Collaboration et al. 2022). While there is evidence that gamma- 2013; Strotjohann et al. 2021). When the supernova shock front ray blazars and tidal disruption events (TDEs) produce high- reaches this dense medium, efficient acceleration of charged energy neutrinos (Aartsen et al. 2018a, 2018b; Stein et al. 2021; particles on timescales ranging from a few tens of seconds to Reusch et al. 2022), the rate of observed coincidences ∼1000 days may occur (Murase et al. 2011; Zirakashvili & constrains the overall diffuse flux contribution of resolved Ptuskin 2016; Sarmah et al. 2022). CSM interactions can be gamma-ray blazars and TDEs to no more than 30% (Aartsen revealed through the detection of a combination of narrow and et al. 2017a) and 26% (Stein 2019), respectively, leaving the broad emission lines (as observed in type IIn SNe). The narrow majority of the diffuse flux unexplained. component of the spectral lines is produced by circumstellar In general, high-energy neutrinos are created through gas, which is ionized as the shock breaks out of the star. The interactions of high-energy protons with ambient matter or intermediate and broad components are produced by shocked, photon fields. Charged and neutral pions produced in those high-velocity SN ejecta, arising as a result of the collision of interactions decay to neutrinos and gamma-rays, respectively. the ejecta with circumstellar gas. Another indication might be a While gamma-rays can also be produced in leptonic processes long plateau in the SN light curve (as seen in Type IIP SNe), such as inverse Compton scattering, neutrinos are considered to which could be partly powered by SN shock breakout be a clear signature for hadronic interactions and thus also interaction with dense CSM (Moriya et al. 2011, 2012). Some cosmic-ray acceleration. IIP SNe show direct observational evidence for Several source classes have been proposed as candidate interactions (Mauerhan et al. 2013; Faran et al. 2014; Yaron neutrino (and cosmic-ray) sources. Among the most promising et al. 2017; Nakaoka et al. 2018). Studies find IIP supernovae are active galactic nuclei, gamma-ray bursts (GRBs) and to be viable candidates for neutrino production through supernovae (SNe)—see Kurahashi et al. (2022) for a recent interactions with the CSM (Murase 2018; Sarmah et al. review. While gamma-bright GRBs are strongly disfavored as the main contributor to the measured diffuse neutrino flux 2022). Pitik et al. (2022) found the high-energy neutrino IC200530A in spatial coincidence with the optical transient (Aartsen et al. 2017b), a large population of nearby low- AT2019fdr, which they interpret as a Type IIn superluminous luminosity bursts could still contribute significantly. The discovery of a connection between GRBs and type Ic-BL supernova. SNe implies that (mildly) relativistic jets should also exist in a Optical follow-up campaigns of IceCube high-energy neutrino alerts (Necker et al. 2022; Stein et al. 2022b) are fraction of core-collapse SNe (Razzaque et al. 2004; Ando & close to constraining the brightest observed superluminous Beacom 2005; Senno et al. 2016; Denton & Tamborra 2018), where such jets might be choked inside the envelope of the star. supernovae. In this scenario, the gamma-rays would be absorbed but the Here, for the first time, we probe different SN classes as neutrinos could still escape. A short neutrino burst (∼100 s) potential neutrino sources and calculate their possible contrib- ution to the observed diffuse neutrino flux. To search for cross- would be expected, in coincidence with the explosion time of the SNe (Senno et al. 2016). Past analyses did not find correlation between neutrinos and optically observed SNe, we significant correlation with high-energy neutrinos, and they put utilize data recorded by the IceCube Neutrino Observatory. 3 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. This paper is organized as follows: Section 2 describes the relevant data sets, followed by a discussion of the analysis methods in Section 3 and the presentation of the results in Section 4. Section 5 presents the constraints on the contribution of CCSNe to the diffuse neutrino flux. Section 6 summarizes the paper. Upper limits on the total energy released in neutrinos from individual SNe can be found in Appendix C. 2. The Data IceCube is a cubic-kilometer-sized neutrino detector, located in the transparent ice of the 2.8 km thick glacier covering the bedrock at the geographical South Pole (Aartsen et al. 2017c). Neutrino–nucleon interactions in the ice are detected indirectly, via Cherenkov light emission from secondary particles, by 5160 photomultiplier tubes. While charged-current interactions of muon neutrinos produce track-like signatures with subdegree Figure 1. Distance distribution of CSM SN sample and the stripped-envelope angular resolution, both charged-current interactions of elec- SN sample. The decrease at large distance is a result of limited detection tron and tau neutrinos as well as neutral-current interactions sensitivity and a selection bias toward brighter objects, which are easier to have angular resolutions of several degrees. This analysis classify spectroscopically. utilizes a selection of seven years of IceCube muon-track data that were optimized for point-source searches (Aartsen et al. 2017d), with roughly 700,000 events from years 2008 to 2014. and the background PDF is calculated similarly (Braun et al. The CCSN catalog for this analysis was compiled using 2010). The signal time PDF  corresponds to the expected publicly available records of optical detections of SNe. The neutrino flux as a function of time (light curve), and the primary sources were the WiseREP SN catalog (Yaron & Gal- background time PDF  assumes a constant background rate. Yam 2012) and the OpenSupernovaCatalog (Guillochon et al. The energy term  describes the expected neutrino energy 2017). In total, the compiled source sample contains 339 type 69 spectrum. As the data set is highly background-dominated, IIn SN, 198 type IIP SN, and 503 type Ib/c and type IIb SNe. we can safely assume that the signal contribution is negligible. The latter are referred to as stripped-envelope supernovae. Both The background energy proxy distribution is thus assumed to type IIn and type IIP SN are candidates for CSM interaction, follow the distribution observed in the data. The signal neutrino while stripped-envelope supernovae might host choked jets. In − γ energy distribution is described as a power-law function, E , Figure 1, the distance distribution of the two subsamples is where γ is the spectral index. For similar reasons, the shown. It should be noted that, while we did include many background spatial PDF as a function of decl. is chosen to supernovae in the analysis, we list only those of a smaller match the distribution of declinations found in the data. We subsample in Appendix A, as explained below. assume that the background spatial PDF is uniform in R.A., The distance was taken from the previously cited catalogs. 1 leading to  () df , =´  (d) for source decl. δ and ,dec 2p For cases in which entries were missing in the catalogs, the R.A. f. The signal spatial PDF,  , is assumed to follow a 2D distances were estimated using redshift measurements. The Gaussian distribution. ΛCDM model, with cosmological parameters measured by The likelihood function is maximized with respect to n and Planck (Ade et al. 2016), was used to convert from redshift to s γ. The best-fitted value n gives an estimate of the number of luminosity distance. We have assumed a peculiar motion of s −1 signal-like events, i.e., those that are likely to originate from a [300] km s , which also provides a lower distance limit for given SN. SNe with very small redshifts. SNe with neither distance nor We define the test statistic (TS) by redshift measurements were excluded from the catalog. The distance distribution peaks at about [100] Mpc, as can be seen (n ˆ , g ˆ) ⎛ ⎞ in Figure 1. l=´2log⎜⎟,3 () () 0 ⎝ ⎠ 3. Analysis Method where (n ˆ , gˆ) corresponds to the maximum of the likelihood To find an excess of neutrinos from the given SN positions function and() 0 to the null hypothesis, i.e., the case of neither and times, a time-dependent point-source likelihood method spatial nor temporal correlation of neutrinos and SNe (Braun (Braun et al. 2010) is used. The likelihood function is given by et al. 2008, 2010). N In principle, λ should follow a χ -distribution n n ss ⎛ ⎞ ⎛ ⎞ =+ ()nn1,- () (1) (Wilks 1938), in which case we could just use its analytical  ii N N ⎝ ⎠ ⎝ ⎠ i=1 form to describe the background distribution of the test statistic. However, in practice we constrain n to be positive where N is the number of neutrino events, ν is the ith neutrino, and n and γ are not independent, which causes deviations and n is the number of signal events.  and  are signal and 2 from the χ distribution. So instead, we estimate the background probability distribution functions (PDFs). Each background test statistic distribution by generating PDF is a product of a spatial term  , an energy term , and a time term  , which for the signal PDF can be expressed as For an astrophysical signal component in the data set with a spectral index 3 5 of γ = 2.5, we expect () 10 signal events and (10 ) atmospheric =´ ()g ´,2( )   background events, amounting to a signal contribution of <1%. 4 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. background-only pseudo-data sets and maximize the like- 4. Constraints on Supernova Subclasses lihood function with respect to n and γ. To be conservative In the following, we present results for selected individual and to avoid mismatches between simulations and data, we CCSNe, as well as for different subclasses of CCSNe. generate these data sets directly from the data. Because Stripped-envelope SNe, which might have choked jets, are IceCube is located at the South Pole, the distribution of the expected to emit a short burst of neutrinos in coincidence with data in R.A. is uniform and the background pseudo-data sets the SN explosion time (Senno et al. 2016). Motivated by can be generated by randomly sampling values for the R.A. theoretical uncertainties in the duration of the expected neutrino and shuffling the times of the neutrino events. This emission—and even larger uncertainties in the SNe explosion scrambling method is well established and preserves the time, due to sparse optical light-curve data—we used a box structureinenergyand decl. (see, e.g., Braun et al. 2008; function starting at 20 days before and extending up to the first Abbasi et al. 2022a, 2022b, 2022c). available optical data. This ensures the inclusion of the Given an experimental outcome and the background test explosion time for a typical SN even if the first detection exp statistic distribution P(λ), the p-value is computed as happened at peak time. All SN types were tested with box function PDFs of length pP = ()lld . exp 100, 300, and 1000 days, starting at the first available optical In addition to probing the neutrino fluxes from single SNe, data, because longer neutrino emission would be expected we combine the signal of a sample of SNe with a stacking under the scenario of CSM interaction. In addition, for SNe IIn analysis. Such a source stacking is implemented through a and IIP, light curves were tested of the form: weighted sum of the signal PDFs  of individual SNe j: -1 ⎛ ⎞ () t µ+1, (6) ⎜⎟  = w,4 () å jj pp ⎝ ⎠ where values of 0.02, 0.2, and 2 yr were used for the where the weights w represent the expected signal strength of characteristic timescale constant t ,as proposed byZirakashvili pp the sources. In this analysis, the weights are assumed to be &Ptuskin (2016). proportional to We first applied the maximum likelihood method described above to a selection of individual SNe, which were identified t E end max n -g based on their expected relative signal strength w as promising. w µ ´ LE A dtdE,5 () j j eff 2 òò t E D start min We did not find a statistically significant excess for any of the    Time Dependence selected sources. Source Properties The resulting upper limits on the total energy emitted in 2 7 −2 neutrinos between [ 10 ] GeV and [ 10 ] GeV, assuming an E with Φ as the intrinsic neutrino power of the sources, D as 0 p n power-law spectrum, are presented in Appendix C. In the the proper distance (Hogg 1999) of the SN, L () t the conversion from the number of neutrino events to flux, the − γ estimated neutrino light curve, E the neutrino energy systemic uncertainty is estimated to be about 11%, mainly spectrum, and A (t, δ , E) the effective area, the energy E, eff j arising from uncertainties in the optical properties of the ice and the decl. of the source δ. The effective area is time- and detector effects (Coenders 2016). 49 50 dependent, because the data set covers several distinct phases The individual upper limits range from 10 to 6.5 × 10 of detector construction. The weighting scheme assumes a erg, which corresponds to 1%–65% of the typical bolometric standard candle ansatz, since we assume the same Φ for each electromagnetic energy released in SNe. As the individual source. It is very sensitive to the estimated source distances, stripped-envelope and IIP SNe are typically closer than the IIn, we generally obtain more stringent limits for these objects. which can have large uncertainties. In order to improve our sensitivity, we performed a stacking A more detailed investigation of the supernova light curves analysis, looking for a combined excess from a catalog instead could mitigate these uncertainties, but the optical light curves of individual sources. As explained above, we separate of the supernovae in our catalog are typically sparse and make supernovae into SNe type IIn, SNe type IIP, and stripped- detailed modeling complicated. Wrongly estimated weights envelope SNe. It is worth noting that we decided to treat types will impact the sensitivity of the analysis, so for the first time in IIn and IIP separately because the presence of CSM interaction an IceCube analysis, we use a novel method of directly fitting in IIP is less certain. the weights w . Adding the flux per source as an additional free Each of the three subcatalogs was split into two samples: a parameter to the maximum likelihood removes the standard bright sample of nearby sources, containing about 70% of the candle assumption and also the dependence on the SN distance expected signal; and a larger sample, containing the remaining estimate, but it requires a more advanced numerical procedure dimmer sources. The bright samples include about 10 SN each, to maximize the likelihood function. To test the power of this depending on the SN class and the model. The catalogs of the method, we simulated five sources with random positions on bright samples are listed in Appendix A. Testing both samples the sky and respective weights. We then perturbed the weights independently allowed us to benefit from the better optical according to a log-normal distribution and used them to observations of the nearby sources in the small sample but also compute the sensitivity of the standard, fixed-weights like- utilize the larger statistics in the large sample. Because each lihood. Comparing to this, we find an improvement of up to source adds a free parameter in the likelihood maximization 40% when using the fitting-weights likelihood. We applied this when fitting the weights, this was only feasible for the smaller method in addition to the traditional standard candle one, yielding two separate results. Calculated by integrating over time. 5 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. bright sample. This sample contains(10) sources, which is a manageable amount of fit parameters. For the large sample, the standard candle ansatz was applied instead. The p-values are given in Appendix B. The most significant pre-trial p-value is 0.62%, and it is found in the search for neutrinos from the large sample of type IIP SNe in a 1000 day- long box-shaped light curve. However, this corresponds to a post-trial p-value of 19.5%, after accounting for the multiple tested scenarios through simulated pseudo-experiments of the ensemble of p-values, and it is thus consistent with background expectations. If this excess were due to astrophysical neutrinos, one would expect a corresponding excess in the sample of nearby type IIP SNe, where we do not find such an excess. The second-smallest p-value of 6.3% is found for the nearby type IIn SNe in the case of the fitted weights for the box-shaped light-curve model. The overall deviation of all tested scenarios from the background expectation using a Kolmogorov– Smirnov test leads to a p-value of 29%. To be conservative, we use the result from the fitting-weights analysis in the rest of the paper, as it resulted in weaker upper limits on the total emitted neutrino energy. Including systematic uncertainties, those are shown in Figure 2 for both models of the neutrino light curve. These limits assume that SNe within each category behave as neutrino standard candles. The stacking result provides us with stronger limits than individual source limits. We find that SNe type IIn emit less 49 48 than 1.3 × 10 erg and type IIP less than 2.4 × 10 erg, while the strongest limits for stripped-envelope SNe of 4.5 × 10 erg are obtained from the choked-jet scenario. If the longer box models that are associated with CSM interaction are assumed, Figure 2. Upper limits on total neutrino (nn + ¯ ) energy assuming a box-like mm -1 then the strongest limit becomes 2.7 × 10 erg. In general, the neutrino light curve (upper panel) and assuming a L µ+ 1 neutrino () t pp box time window provides tighter constraints for CSM- light curve as predicted by Zirakashvili & Ptuskin (2016). The energy ranges interacting SNe compared to the specific light-curve model of are the same as indicated in Figure 3. The model predictions by Murase et al. Zirakashvili & Ptuskin (2016). (2011) and Zirakashvili & Ptuskin (2016) are shown as red squares for comparison. 5. Diffuse Neutrino Flux Using the limits on neutrino energy obtained in the stacking of Figure 3 for a spectral index of γ = 2.0 as motivated by analysis (shown in Figure 2), we can estimate the maximal theoretical models (Murase 2018; Sarmah et al. 2022). contribution from the entire cosmological population of SNe to Following a data-driven approach, the top panel shows the the measured diffuse neutrino flux (Aartsen et al. 2015). Using limits for a spectral index of γ = 2.5 as motivated by the central the CCSNe rate density found by Strolger et al. (2015), r (z), value of the global fit diffuse neutrino flux (Aartsen et al. the diffuse flux is computed following the procedure in Ahlers 2015). Assuming the choked-jet scenario, stripped-envelope & Halzen (2014) assuming a 1:1:1 (ν : ν : ν ) neutrino flavor e μ τ SNe cannot contribute more than 14.6% of the observed diffuse ratio at Earth. It is worth noting that we assume the rate for the individual subclasses scales according to the corresponding neutrino flux. Assuming interaction with the CSM, stripped- percentage in the local Universe (Li et al. 2011). The diffuse envelope SNe and SNe type IIn can explain no more than flux is given by 26.6% and 33.9%, respectively. We mildly constrain the contribution of SNe type IIP to be less than 59.9%. We note 1 r () z dN c that the limit for type IIP SNe seems weaker when translating it f() E = dz,7 () 41 p 0 + z dE Hz () to a component of the diffuse flux, because they are the most abundant supernova type (Li et al. 2011). where dNdE is the time-integrated spectral density upper limit For stripped-envelope SNe, this analysis is complementary for each SN subclass, assuming that the subclass behaves as a to that of Chang et al. (2022), who take into account the neutrino standard candle class with a power-law energy fraction of supernovae f that harbor a choked-jet pointing in jet spectrum and that the power law holds over our sensitive our line of sight to arrive at a limit on the contribution to the energy range. This energy range is calculated by finding the diffuse flux that is about ten times less stringent. Because we energy bound for selecting simulated signal events. We find the assume the supernovae of each subclass to be standard candles values where our sensitivity drops by 5% for the lower and when deriving the upper limits on the total emitted neutrino upper bounds separately. The range between both values is our energy in Section 4, our results are robust for f ≈ 1 but they jet 90% energy range. will be less stringent for f = 1. jet The resulting upper limits on the contribution of different SN This analysis has different sensitivities for different energy types to the diffuse neutrino flux are shown in the bottom panel ranges; see Figure 4. The region of greatest sensitivity is 6 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. 6. Conclusion We have presented a search for neutrinos from certain types of CCSNe with IceCube. In a stacking analysis, we correlated more than 1000 SNe from optical surveys with roughly 700,000 muon-track events recorded by IceCube. The standard stacking method was extended to allow for fitting of individual weights for each source, in order to account for expected variation in the neutrino flux from individual sources. Type IIn SNe, type IIP SNe, and stripped-envelope SNe were tested individually with various neutrino emission time models. No significant temporal and spatial correlation of neutrinos and the cataloged SNe was found, allowing us to set upper limits on the contribution of those SNe to the diffuse neutrino flux. Type IIn CCSNe, type IIP CCSNe, and stripped-envelope SNe contribute less than 34%, 60%, and 27%, respectively, to the diffuse neutrino flux at the 90% confidence level, assuming CSM interaction and an extrapolation of the diffuse neutrino spectrum to low energies following an unbroken power law with index −2.5. This also assumes a choked-jet, stripped- envelope SNe cannot contribute more than 15%. Upper limits on the total neutrino energy emitted by a single CSM-interacting source are at levels comparable to model predictions by Murase et al. (2011)(see Figure 2), while model predictions from Zirakashvili & Ptuskin (2016) are strongly disfavored. It should be noted that the model prediction could easily be adjusted to lower neutrino flux predictions by assuming a lower CSM density or a lower kinetic SN energy. Improvements to the presented limits are expected in the near future with optical survey instruments such as the Zwicky Figure 3. Upper limit on the contribution of different SN types to the diffuse −2.5 −2.0 Transient Factory (Graham et al. 2019), which is able to neutrino flux (nn + ¯ ) assuming an E (top panel) and E (bottom panel) mm undertake a high-cadence survey across a large fraction of the energy spectrum compared with the measured diffuse astrophysical neutrino flux (gray band). The limits are derived from the corresponding strictest limit in sky, providing SN catalogs with much greater completeness. In Figure 2. The choked-jet model refers to the 20 day box model, as explained in combination with next-generation neutrino telescopes, this will Section 4. The energy range plotted here is the central 90% energy range of the significantly boost the sensitivity of this type of analysis, analyzed neutrino sample. allowing us to probe dimmer neutrino emitters and smaller contributions of CCSNe to the diffuse neutrino flux. The IceCube collaboration acknowledges the significant contributions to this manuscript from Jannis Necker, Alexander Stasik, and Robert Stein. We also gratefully acknowledge support from: USA—the U.S. National Science Foundation– Office of Polar Programs, the U.S. National Science Founda- tion–Physics Division, the U.S. National Science Foundation– EPSCoR, the Wisconsin Alumni Research Foundation, the Center for High Throughput Computing (CHTC) at the University of Wisconsin–Madison, the Open Science Grid (OSG), Advanced Cyberinfrastructure Coordination Ecosys- tem: Services & Support (ACCESS), the Frontera computing project at the Texas Advanced Computing Center, the U.S. Figure 4. Differential sensitivity as a function of energy for different source Department of Energy–National Energy Research Scientific declinations δ with one year of experimental data. The maximum sensitivity is 5 Computing Center, the Particle Astrophysics Research Com- achieved around [ 10 ] GeV for sources located in the northern sky and close to puting Center at the University of Maryland, the Institute for the equator. For sources located in the southern sky, the overall sensitivity is much worse, but it also peaks at higher energies of [ 10 ] GeV. Cyber-Enabled Research at Michigan State University, and the Astroparticle Physics Computational Facility at Marquette around 10–100 TeV. It can reach to higher energies as well, University; Belgium—Funds for Scientific Research (FRS- depending on the source decl. This broadly overlaps with the FNRS and FWO), the FWO Odysseus and Big Science energy range in which the diffuse IceCube neutrino flux global programmes, and the Belgian Federal Science Policy Office fit was measured. The quoted upper limits to the diffuse flux (Belspo); Germany—Bundesministerium für Bildung und contribution are thus not strongly dependent on the extrapola- Forschung (BMBF), Deutsche Forschungsgemeinschaft (DFG), tion of the measured diffuse flux to lower energies, where the Helmholtz Alliance for Astroparticle Physics (HAP),the flux has not yet been measured due to large atmospheric Initiative and Networking Fund of the Helmholtz Association, background. Deutsches Elektronen Synchrotron (DESY), and the High 7 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Performance Computing Cluster of the RWTH Aachen; Sweden —the National Research Foundation of Korea (NRF); Switzer- —the Swedish Research Council, the Swedish Polar Research land—the Swiss National Science Foundation (SNSF);United Secretariat, the Swedish National Infrastructure for Computing Kingdom—Oxford University, Department of Physics. (SNIC), and the Knut and Alice Wallenberg Foundation; Facilities: HST(STIS), Swift(XRT and UVOT), AAVSO, CTIO:1.3 m, CTIO:1.5 m, CXO. European Union—EGI Advanced Computing for Research; Software: flarestack (Stein et al. 2022a). Australia—the Australian Research Council; Canada—the Natural Sciences and Engineering Research Council of Canada, Calcul Québec, Compute Ontario, the Canada Foundation for Appendix A Innovation, WestGrid, and Compute Canada; Denmark—Villum Catalogs Fonden, the Carlsberg Foundation, and the European Commis- sion; New Zealand—the Marsden Fund; Japan—the Japan Tables 1, 2, and 3 list the supernova catalogues used in the Society for Promotion of Science (JSPS) and the Institute for fitting weights analysis as described in Section 4. Global Prominent Research (IGPR) of Chiba University; Korea Table 1 Interacting Supernovae Catalog Name R.A. Decl. Discovery Date Redshift Distance Source (rad)(rad)(Mpc) SN1999bw 2.70 0.79 1999-00-20 0.0032 9.80 1, 2 SN2002bu 3.22 0.80 2002-00-28 0.0030 8.90 1, 2, 3 SN2008S 5.39 1.05 2008-00-01 0.0012 5.60 4 SN2009kr 1.36 −0.27 2009-00-06 0.0075 16.00 5 SN2010jl 2.54 0.17 2010-00-03 0.0117 49.00 6 SN2011an 2.09 0.29 2011-00-01 0.0170 73.00 7 SN2011ht 2.65 0.90 2011-00-29 0.0046 19.20 8 SN2012ab 3.24 0.10 2012-00-31 0.0190 81.00 9 SN2013by 4.29 −1.05 2013-00-23 0.0038 14.80 10, 11 SN2013gc 2.13 −0.49 2013-00-07 0.0044 15.10 12 PSN J14041297-0938168 3.68 −0.17 2013-00-20 0.0038 12.55 13 CSS140111:060437-123740 1.59 −0.22 2013-00-24 0.0084 32.88 13 SN2014G 2.86 0.95 2014-00-14 0.0045 20.00 14 MASTER OT J044212.20+230616.7 1.23 0.40 2014-00-21 0.0170 72.00 15 SN2015da 3.63 0.69 2015-00-09 0.0079 32.14 16, 17 References. (1) Kochanek et al. 2012; (2) Smith et al. 2011; (3) Szczygiełet al. 2012; (4) Stanishev et al. 2008; (5) Steele et al. 2009a; (6) Benetti et al. 2010; (7) Marion & Calkins 2011; (8) Prieto et al. 2011; (9) Bilinski et al. 2018; (10) Margutti et al. 2013; (11) Parker et al. 2013; (12) Antezana et al. 2013; (13) Challis 2013; (14) Denisenko et al. 2014; (15) Shivvers et al. 2014; (16) Zhang & Wang 2015; (17) Tartaglia et al. 2020. 8 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Table 2 IIP Catalog Name R.A. Decl. Discovery Date Redshift Distance Source (rad)(rad)(Mpc) SN1999em 1.23 −0.05 1999-00-29 0.0034 7.50 1 SN2004dj 2.00 1.14 2004-00-31 0.0014 3.50 2 SN2004et 5.39 1.05 2004-00-27 0.0022 7.70 3, 4 SN2005cs 3.53 0.82 2005-00-28 0.0030 7.10 5, 6 SN2006ov 3.24 0.08 2006-00-24 0.0062 14.00 7 SN2008bk 6.27 −0.57 2008-00-25 0.0018 4.00 8 SN2009js 0.64 0.32 2009-00-11 0.0060 16.00 9 SN2009md 2.83 0.22 2009-00-05 0.0046 18.00 10 SN2009mf 0.27 0.83 2009-00-07 0.0087 23.00 11 SN2011dq 0.26 −0.13 2011-00-15 0.0055 24.40 12 SN2012A 2.73 0.30 2012-00-07 0.0034 9.80 13 SN2012aw 2.81 0.20 2012-00-16 0.0036 9.90 14 SNhunt141 3.57 −0.31 2012-00-24 0.0040 18.00 15 SN2012ec 0.72 −0.13 2012-00-12 0.0057 18.76 16 SN2013ab 3.81 0.17 2013-00-17 0.0063 23.64 17 SN2013am 2.96 0.23 2013-00-21 0.0037 12.77 18 SN2013bu 5.92 0.60 2013-00-21 0.0027 12.07 19 SN2013ej 0.42 0.28 2013-00-25 0.0020 9.00 20 SN2011ja 3.43 −0.86 2014-00-14 0.0018 3.36 21 SN2014bc 3.22 0.83 2014-00-19 0.0025 7.60 22 References. (1) Jha et al. 1999; (2) Patat et al. 2004; (3) Zwitter et al. 2004; (4) Li et al. 2005; (5) Modjaz et al. 2005; (6) Pastorello et al. 2009; (7) Li et al. 2007; (8) Morrell & Stritzinger 2008; (9) Gandhi et al. 2013; (10) Sollerman et al. 2009; (11) Steele et al. 2009b; (12) Valenti & Benetti 2011; (13) Stanishev & Pursimo 2012; (14) Quadri et al. 2012; (15) Cellier-Holzem et al. 2012; (16) Monard et al. 2012; (17) Bose et al. 2015; (18) Benetti et al. 2013; (19) Itagaki et al. 2013; (20) Dhungana et al. 2016; (21) Andrews et al. 2016; (22) Ochner et al. 2014. Table 3 Stripped-envelope Supernovae Catalog Name R.A. Decl. Discovery Date Redshift Distance Source (rad)(rad)(Mpc) SN2007gr 0.71 0.65 2007-00-15 0.0027 9.30 1, 2 SN2008ax 3.28 0.73 2008-00-03 0.0029 9.60 3, 4 SN2008dv 0.95 1.27 2008-00-01 0.0084 4.20 5 SN2009dq 2.66 −1.17 2009-00-24 0.0046 16.00 6 SN2009gj 0.13 −0.58 2009-00-21 0.0053 17.00 7 SN2009mk 0.03 −0.72 2009-00-15 0.0050 22.00 8, 9 SN2009mu 2.58 −0.58 2009-00-21 0.0098 25.00 10 SN2010br 3.16 0.78 2010-00-10 0.0033 13.00 11 SN2010gi 4.55 1.32 2010-00-18 0.0041 18.20 12 SN2011dh 3.53 0.82 2011-00-01 0.0025 8.40 5 SN2011jm 3.38 0.05 2011-00-24 0.0041 14.00 13 SN2012P 3.93 0.03 2012-00-22 0.0055 20.10 14, 15 SN2012cw 2.68 0.06 2012-00-14 0.0055 19.92 16, 17 SN2012fh 2.81 0.43 2012-00-18 0.0029 8.58 18, 19, 20 SN2013df 3.26 0.55 2013-00-07 0.0033 10.58 21, 22 iPTF13bvn 3.93 0.03 2013-00-17 0.0055 19.94 15, 23, 24, 25 MASTER OT J120451.50+265946.6 3.16 0.47 2013-00-02 0.0029 8.38 26, 27, 28 SN2013ge 2.77 0.38 2013-00-08 0.0054 19.34 29, 30 SN2014C 5.92 0.60 2014-00-05 0.0037 12.07 31, 32, 33 References. (1) Chornock et al. 2007; (2) Valenti et al. 2008; (3) Chornock et al. 2008; (4) Pastorello et al. 2008; (5) Silverman et al. 2008; (6) Anderson et al. 2009; (7) Stockdale et al. 2009; (8) Chornock & Berger 2009; (9) Marples & Drescher 2009; (10) Stritzinger et al. 2010; (11) Maxwell et al. 2010; (12) Yamanaka et al. 2010; (13) Foley & Fong 2011; (14) Borsato et al. 2012; (15) Fremling et al. 2016; (16) Itagaki et al. 2012; (17) Wang et al. 2012; (18) Johnson et al. 2017; (19) Takaki et al. 2012; (20) Tomasella et al. 2012; (21) Ciabattari et al. 2013; (22) Van Dyk et al. 2014; (23) Cao et al. 2013; (24) Milisavljevic et al. 2013; (25) Srivastav et al. 2014a; (26) Chandra et al. 2019; (27) Singh et al. 2019; (28) Srivastav et al. 2014b; (29) Drout et al. 2016; (30) Nakano et al. 2013; (31) Kim et al. 2014; (32) Milisavljevic et al. 2015; (33) Tinyanont et al. 2016. 9 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. Appendix B P-values [%] Table 4 lists the pre-trial P-values of the fitted weights model of different length and for the CSM model of scenario given as percentages for a box-shaped light-curve Zirakashvili & Ptuskin (2016) for different choices of t . pp Table 4 Pre-trial P-values Box Length (days) t (yr) pp [−20, 0][0, 100][0, 300][0, 10000] 0.02 0.2 2.0 IIn L 8.6 6.3 >50 >50 >50 30.1 IIP L 48.6 >50 27.6 >50 >50 21.6 Stripped-envelope >50 >50 >50 34.8 LL L 10 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. −2 Appendix C assume a generic neutrino energy spectrum of E , rather than Upper Limits on Individual Sources tying them to the observed diffuse spectral shape, and an emission time window of 100 days. Table 5 lists IIn SNe, This section shows upper limits on individual SNe. Sources Table 6 IIP SNe, and Table 7 the stripped-envelope SNe. were selected based on their expected neutrino signal. Here, we Table 5 Upper Limits on Selected Type IIn SNe Name R.A. Decl. Discovery Date Distance Energy Upper Limit (rad)(rad)(Mpc)(10 erg) CSS140111:060437-123740 1.59 −0.22 2013-12-24 31.8 49.8 PSN J13522411+3941286 3.63 0.693 2015-01-09 32.1 16.8 PSN J14041297-0938168 3.68 −0.168 2013-12-20 12.5 4.8 PTF10aaxf 2.54 0.166 2010-11-03 52.3 29.5 SN2008S 5.39 1.049 2008-02-01 5.6 5.3 SN2009kr 1.36 −0.274 2009-11-06 16.0 19.1 SN2011an 2.09 0.287 2011-03-01 73.0 65.3 SN2011ht 2.65 0.905 2011-09-29 19.2 6.6 SN2012ab 3.24 0.098 2012-01-31 81.0 64.18 SN2013gc 2.13 −0.49 2013-11-07 15.1 28.4 Table 6 Upper Limits on Selected Type IIP SNe Discovery Energy Upper Name R.A. Decl. Date Distance Limit (rad)(rad)(Mpc)(10 erg) iPTF13aaz 2.96 0.228 2013-03-21 16.4 1.0 SN2012A 2.73 0.299 2012-01-07 9.0 1.0 SN2012aw 2.81 0.204 2012-03-16 9.6 1.0 SN2014bc 3.22 0.826 2014-05-19 7.6 3.0 Table 7 Upper Limits on Selected Stripped-envelope SNe (Ib/c and IIb) Energy Discovery Upper Name R.A. Decl. Date Distance Limit (rad)(rad)(Mpc)(10 erg) iPTF13bvn 3.93 0.033 2013-06-17 25.8 4.0 MASTER OT 3.16 0.471 2014-10-28 15.0 1.0 J120451.50 PTF11eon 3.53 0.823 2011-06-01 8.0 1.1 SN2008ax 3.28 0.727 2008-03-03 5.1 1.6 SN2008dv 0.95 1.267 2008-07-01 10.6 1.2 SN2010br 3.16 0.777 2010-04-10 9.9 4.1 SN2011jm 3.38 0.046 2011-12-24 14.0 1.8 SN2012cw 2.68 0.06 2012-06-14 31.3 4.3 SN2012fh 2.81 0.434 2012-10-18 8.6 1.1 SN2013df 3.26 0.545 2013-06-07 10.6 1.7 SN2014C 5.92 0.601 2014-01-05 12.1 2.3 11 The Astrophysical Journal Letters, 949:L12 (14pp), 2023 May 20 Abbasi et al. ORCID iDs E. Ganster https://orcid.org/0000-0003-4393-6944 A. Garcia https://orcid.org/0000-0002-8186-2459 R. Abbasi https://orcid.org/0000-0001-6141-4205 S. Garrappa https://orcid.org/0000-0003-2403-4582 M. Ackermann https://orcid.org/0000-0001-8952-588X A. Ghadimi https://orcid.org/0000-0002-6350-6485 S. K. Agarwalla https://orcid.org/0000-0002-9714-8866 C. Glaser https://orcid.org/0000-0001-5998-2553 J. A. 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