IceCube Data for Neutrino Point-Source Searches Years 2008-2018
IceCube Collaboration, R. Abbasi, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, M. Ahrens, C. Alispach, N. M. Amin, K. Andeen, T. Anderson, I. Ansseau, G. Anton, C. Argüelles, S. Axani, X. Bai, A. Balagopal V., A. Barbano, S. W. Barwick, B. Bastian, V. Basu, V. Baum, S. Baur, R. Bay, J. J. Beatty, K.-H. Becker, J. Becker Tjus, C. Bellenghi, S. BenZvi, D. Berley, E. Bernardini, D. Z. Besson, G. Binder, D. Bindig, E. Blaufuss, S. Blot, C. Bohm, S. Böser, O. Botner, J. Böttcher, E. Bourbeau, J. Bourbeau, F. Bradascio, J. Braun, S. Bron, J. Brostean-Kaiser, A. Burgman, J. Buscher, R. S. Busse, M. A. Campana, T. Carver, C. Chen, E. Cheung, D. Chirkin, S. Choi, B. A. Clark, K. Clark, L. Classen, A. Coleman, G. H. Collin, J. M. Conrad, P. Coppin, P. Correa, D. F. Cowen, R. Cross, P. Dave, C. De Clercq, J. J. DeLaunay, H. Dembinski, K. Deoskar, S. De Ridder, A. Desai, P. Desiati, K. D. de Vries, G. de Wasseige, M. de With, T. DeYoung, S. Dharani, A. Diaz, J. C. Díaz-Vélez, H. Dujmovic, M. Dunkman, M. A. DuVernois, E. Dvorak, T. Ehrhardt, P. Eller, R. Engel, P. A. Evenson, S. Fahey, A. R. Fazely, J. Felde, A.T. Fienberg, K. Filimonov, C. Finley, L. Fischer, D. Fox, A. Franckowiak, E. Friedman, A. Fritz, T. K. Gaisser, et al. (274 additional authors not shown)
IIceCube Data for Neutrino Point-Source Searches: Years 2008–2018
R. Abbasi, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, M. Ahrens, C. Alispach, N. M.Amin, K. Andeen, T. Anderson, I. Ansseau, G. Anton, C. Arg¨uelles, S. Axani, X. Bai, A. BalagopalV., A. Barbano, S. W. Barwick, B. Bastian, V. Basu, V. Baum, S. Baur, R. Bay, J. J. Beatty,
20, 21
K.-H. Becker, J. Becker Tjus, C. Bellenghi, S. BenZvi, D. Berley, E. Bernardini, ∗ D. Z. Besson, † G.Binder,
8, 9
D. Bindig, E. Blaufuss, S. Blot, C. Bohm, S. B¨oser, O. Botner, J. B¨ottcher, E. Bourbeau, J. Bourbeau, F. Bradascio, J. Braun, S. Bron, J. Brostean-Kaiser, A. Burgman, J. Buscher, R. S.Busse, M. A. Campana, T. Carver, C. Chen, E. Cheung, D. Chirkin, S. Choi, B. A. Clark, K. Clark, L. Classen, A. Coleman, G. H. Collin, J. M. Conrad, P. Coppin, P. Correa, D. F. Cowen,
53, 54
R. Cross, P. Dave, C. De Clercq, J. J. DeLaunay, H. Dembinski, K. Deoskar, S. De Ridder, A. Desai, P. Desiati, K. D. de Vries, G. de Wasseige, M. de With, T. DeYoung, S. Dharani, A. Diaz, J. C. D´ıaz-V´elez, H.Dujmovic, M. Dunkman, M. A. DuVernois, E. Dvorak, T. Ehrhardt, P. Eller, R. Engel, P. A.Evenson, S. Fahey, A. R. Fazely, J. Felde, A.T. Fienberg, K. Filimonov, C. Finley, L. Fischer, D.Fox, A. Franckowiak, E. Friedman, A. Fritz, T. K. Gaisser, J. Gallagher, E. Ganster, S. Garrappa, L.Gerhardt, A. Ghadimi, T. Glauch, T. Gl¨usenkamp, A. Goldschmidt, J. G. Gonzalez, S. Goswami, D.Grant, T. Gr´egoire, Z. Griffith, S. Griswold, M. G¨und¨uz, C. Haack, A. Hallgren, R. Halliday, L.Halve, F. Halzen, M. Ha Minh, K. Hanson, J. Hardin, A. Haungs, S. Hauser, D. Hebecker, P. Heix, K.Helbing, R. Hellauer, F. Henningsen, S. Hickford, J. Hignight, C. Hill, G. C. Hill, K. D. Hoffman, R.Hoffmann, T. Hoinka, B. Hokanson-Fasig, K. Hoshina, ‡ F. Huang, M. Huber, T. Huber, K.Hultqvist, M. H¨unnefeld, R. Hussain, S. In, N. Iovine, A. Ishihara, M. Jansson, G. S. Japaridze, M.Jeong, B. J. P. Jones, F. Jonske, R. Joppe, D. Kang, W. Kang, X. Kang, A. Kappes, D. Kappesser, T. Karg, M. Karl, A. Karle, U. Katz, M. Kauer, M. Kellermann, J. L. Kelley, A. Kheirandish, J.Kim, K. Kin, T. Kintscher, J. Kiryluk, T. Kittler, S. R. Klein,
8, 9
R. Koirala, H. Kolanoski, L.K¨opke, C. Kopper, S. Kopper, D. J. Koskinen, P. Koundal, M. Kovacevich, M. Kowalski,
10, 57
K.Krings, G. Kr¨uckl, N. Kulacz, N. Kurahashi, A. Kyriacou, C. Lagunas Gualda, J. L. Lanfranchi, M. J.Larson, F. Lauber, J. P. Lazar,
14, 37
K. Leonard, A. Leszczy´nska, Y. Li, Q. R. Liu, E. Lohfink, C. J.Lozano Mariscal, L. Lu, F. Lucarelli, A. Ludwig, J. L¨unemann, W. Luszczak, Y. Lyu,
8, 9
W. Y. Ma, J.Madsen, G. Maggi, K. B. M. Mahn, Y. Makino, P. Mallik, S. Mancina, I. C. Mari¸s, R. Maruyama, K.Mase, R. Maunu, F. McNally, K. Meagher, A. Medina, M. Meier, S. Meighen-Berger, J. Merz, J.Micallef, D. Mockler, G. Moment´e, T. Montaruli, R. W. Moore, R. Morse, M. Moulai, P. Muth, R.Naab, R. Nagai, U. Naumann, J. Necker, G. Neer, L. V. Nguy˜ˆen, H. Niederhausen, M. U. Nisa, S. C. Nowicki, D. R. Nygren, A. Obertacke Pollmann, M. Oehler, A. Olivas, E. O’Sullivan, H.Pandya, D. V. Pankova, N. Park, G. K. Parker, E. N. Paudel, P. Peiffer, C. P´erez de los Heros, S. Philippen, D. Pieloth, S. Pieper, A. Pizzuto, M. Plum, Y. Popovych, A. Porcelli, M. PradoRodriguez, P. B. Price, G. T. Przybylski, C. Raab, A. Raissi, M. Rameez, K. Rawlins, I. C. Rea, A.Rehman, R. Reimann, M. Renschler, G. Renzi, E. Resconi, S. Reusch, W. Rhode, M. Richman, B. Riedel, S. Robertson,
8, 9
G. Roellinghoff, M. Rongen, C. Rott, T. Ruhe, D. Ryckbosch, D.Rysewyk Cantu, I. Safa,
14, 37
S. E. Sanchez Herrera, A. Sandrock, J. Sandroos, M. Santander, S.Sarkar, S. Sarkar, K. Satalecka, M. Scharf, M. Schaufel, H. Schieler, P. Schlunder, T. Schmidt, A.Schneider, J. Schneider, F. G. Schr¨oder,
31, 41
L. Schumacher, S. Sclafani, D. Seckel, S. Seunarine, S.Shefali, M. Silva, B. Smithers, R. Snihur, J. Soedingrekso, D. Soldin, M. Song, G. M. Spiczak, C. Spiering, † J. Stachurska, M. Stamatikos, T. Stanev, R. Stein, J. Stettner, A. Steuer, T.Stezelberger, R. G. Stokstad, N. L. Strotjohann, T. St¨urwald, T. Stuttard, G. W. Sullivan, I. Taboada, F.Tenholt, S. Ter-Antonyan, S. Tilav, K. Tollefson, L. Tomankova, C. T¨onnis, S. Toscano, D. Tosi, A.Trettin, M. Tselengidou, C. F. Tung, A. Turcati, R. Turcotte, C. F. Turley, J. P. Twagirayezu, B. Ty, E. Unger, M. A. Unland Elorrieta, J. Vandenbroucke, D. van Eijk, N. van Eijndhoven, D. Vannerom, J. van Santen, S. Verpoest, M. Vraeghe, C. Walck, A. Wallace, T. B. Watson, C. Weaver, A. Weindl, M. J. Weiss, J. Weldert, C. Wendt, J. Werthebach, B. J. Whelan, N. †† Email: [email protected] a r X i v : . [ a s t r o - ph . H E ] J a n Whitehorn, K. Wiebe, C. H. Wiebusch, D. R. Williams, M. Wolf, T. R. Wood, K. Woschnagg, G.Wrede, J. Wulff, X. W. Xu, Y. Xu, J. P. Yanez, S. Yoshida, T. Yuan, Z. Zhang, and M. Z¨ocklein (IceCube Collaboration †† ) III. Physikalisches Institut, RWTH Aachen University, D-52056 Aachen, Germany Department of Physics, University of Adelaide, Adelaide, 5005, Australia Dept. of Physics and Astronomy, University of Alaska Anchorage,3211 Providence Dr., Anchorage, AK 99508, USA Dept. of Physics, University of Texas at Arlington, 502 Yates St.,Science Hall Rm 108, Box 19059, Arlington, TX 76019, USA CTSPS, Clark-Atlanta University, Atlanta, GA 30314, USA School of Physics and Center for Relativistic Astrophysics,Georgia Institute of Technology, Atlanta, GA 30332, USA Dept. of Physics, Southern University, Baton Rouge, LA 70813, USA Dept. of Physics, University of California, Berkeley, CA 94720, USA Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA Institut f¨ur Physik, Humboldt-Universit¨at zu Berlin, D-12489 Berlin, Germany Fakult¨at f¨ur Physik & Astronomie, Ruhr-Universit¨at Bochum, D-44780 Bochum, Germany Universit´e Libre de Bruxelles, Science Faculty CP230, B-1050 Brussels, Belgium Vrije Universiteit Brussel (VUB), Dienst ELEM, B-1050 Brussels, Belgium Department of Physics and Laboratory for Particle Physics and Cosmology,Harvard University, Cambridge, MA 02138, USA Dept. of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Dept. of Physics and Institute for Global Prominent Research, Chiba University, Chiba 263-8522, Japan Department of Physics, Loyola University Chicago, Chicago, IL 60660, USA Dept. of Physics and Astronomy, University of Canterbury, Private Bag 4800, Christchurch, New Zealand Dept. of Physics, University of Maryland, College Park, MD 20742, 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 Niels Bohr Institute, University of Copenhagen, DK-2100 Copenhagen, Denmark Dept. of Physics, TU Dortmund University, D-44221 Dortmund, Germany Dept. of Physics and Astronomy, Michigan State University, East Lansing, MI 48824, USA Dept. of Physics, University of Alberta, Edmonton, Alberta, Canada T6G 2E1 Erlangen Centre for Astroparticle Physics, Friedrich-Alexander-Universit¨at Erlangen-N¨urnberg, D-91058 Erlangen, Germany Physik-department, Technische Universit¨at M¨unchen, D-85748 Garching, Germany D´epartement de physique nucl´eaire et corpusculaire,Universit´e de Gen`eve, CH-1211 Gen`eve, Switzerland Dept. of Physics and Astronomy, University of Gent, B-9000 Gent, Belgium Dept. of Physics and Astronomy, University of California, Irvine, CA 92697, USA Karlsruhe Institute of Technology, Institut f¨ur Kernphysik, D-76021 Karlsruhe, Germany Dept. of Physics and Astronomy, University of Kansas, Lawrence, KS 66045, USA SNOLAB, 1039 Regional Road 24, Creighton Mine 9, Lively, ON, Canada P3Y 1N2 Department of Physics and Astronomy, UCLA, Los Angeles, CA 90095, USA Department of Physics, Mercer University, Macon, GA 31207-0001, USA Dept. of Astronomy, University of Wisconsin–Madison, Madison, WI 53706, USA Dept. of Physics and Wisconsin IceCube Particle Astrophysics Center,University of Wisconsin–Madison, Madison, WI 53706, USA Institute of Physics, University of Mainz, Staudinger Weg 7, D-55099 Mainz, Germany Department of Physics, Marquette University, Milwaukee, WI, 53201, USA Institut f¨ur Kernphysik, Westf¨alische Wilhelms-Universit¨at M¨unster, D-48149 M¨unster, Germany Bartol Research Institute and Dept. of Physics and Astronomy,University of Delaware, Newark, DE 19716, USA Dept. of Physics, Yale University, New Haven, CT 06520, USA Dept. of Physics, University of Oxford, Parks Road, Oxford OX1 3PU, UK Dept. of Physics, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA Physics Department, South Dakota School of Mines and Technology, Rapid City, SD 57701, USA Dept. of Physics, University of Wisconsin, River Falls, WI 54022, USA Dept. of Physics and Astronomy, University of Rochester, Rochester, NY 14627, USA Oskar Klein Centre and Dept. of Physics, Stockholm University, SE-10691 Stockholm, Sweden Dept. of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794-3800, USA Dept. of Physics, Sungkyunkwan University, Suwon 16419, Korea Institute of Basic Science, Sungkyunkwan University, Suwon 16419, Korea Dept. of Physics and Astronomy, University of Alabama, Tuscaloosa, AL 35487, 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, Uppsala University, Box 516, S-75120 Uppsala, Sweden Dept. of Physics, University of Wuppertal, D-42119 Wuppertal, Germany DESY, D-15738 Zeuthen, Germany
IceCube has performed several all-sky searches for point-like neutrino sources using track-likeevents, including a recent time-integrated analysis using 10 years of IceCube data. This paperaccompanies the public data release of these neutrino candidates detected by IceCube betweenApril 6, 2008 and July 8, 2018. The selection includes through-going tracks, primarily due to muonneutrino candidates, that reach the detector from all directions, as well as neutrino track eventsthat start within the instrumented volume. An updated selection and reconstruction for data takenafter April 2012 slightly improves the sensitivity of the sample. While more than 80% of the sampleoverlaps between the old and new versions, differing events can lead to changes relative to theprevious 7 year event selection. An a posteriori estimate of the significance of the 2014-2015 TXSflare is reported with an explanation of observed discrepancies with previous results. This publicdata release, which includes 10 years of data and binned detector response functions for muonneutrino signal events, shows improved sensitivity in generic time-integrated point source analysesand should be preferred over previous releases.
I. INTRODUCTION
The IceCube Observatory [1] at the geographic SouthPole has been operating at full capacity for the pastten years. In 2013, IceCube reported first evidence ofan isotropic flux of astrophysical neutrinos in the TeV-PeV energy range [2, 3]. While the flux is by now ob-served with high significance [4–7] its astrophysical ori-gin remains uncertain [8]. In parallel, IceCube has beensearching for high-energy neutrino emission from indi-vidual time-integrated point sources, including unbiasedall-sky searches [9–13] as well as individual source candi-dates like cores of active galaxies [14], blazars [15], γ -raybursts [16–19], fast radio bursts [20], nearby galaxies [21],diffuse Galactic emission [22], Galactic γ -ray sources [23],pulsar wind nebulae [24], or X-ray binaries [25]. IceCubealso takes part in various realtime multi-messenger ac-tivities via its fast response to external alerts in pho-tons [26, 27] or gravitational waves [28–30] and by re-porting astrophysical neutrino candidate events [31, 32].Recently, IceCube was able to report first compelling ev-idence of neutrino emission from the γ -ray blazar TXS0506+056 [33–35].In order to encourage engagement with the broadermulti-messenger astrophysics community, IceCube isdedicated to releasing datasets for public use. Datahas been released in various formats [36–46]. To betterequip the community, IceCube is releasing a new 10 yeardataset of track-like events previously developed for Ice-Cube’s recent 10 year time integrated point source search[13] along with binned instrument response functions todescribe the detector.This paper accompanies the public data release oftrack-like neutrino candidates detected by IceCube be-tween April 6, 2008 and July 8, 2018 [47]. The releasedsample shows evidence of cumulative excess of eventsfrom a catalogue of 110 sources with respect to the ex-pected atmospheric neutrino background. Its significanceof 3.3 σ is mostly determined by four sources, in order of importance NGC 1068, TXS 0506+056, PKS 1424+240and GB6 J1542+6129. NGC 1068, a Seyfert galaxy ata redshift of z=0.003, is spatially coincident with thehottest spot in the full Northern sky search.The underlying event selection, called PSTracks in thefollowing, is designed for point-source studies that benefitfrom the good angular resolution of tracks and can tol-erate larger atmospheric background contributions com-pared to diffuse neutrino analyses. The
PSTracks samplehas recently been updated from 7 years ( v2 ) to 10 years( v3 ). PSTracks v3, which includes an improved selectionand reconstruction for data collected after April 2012, isnow being released to the community.This data release applies to IceCube data collectedprior to July 2018 and may be used to reproduce analysespublished on the
PSTracks v3 dataset. The IceCube Col-laboration continues to evaluate and refine the selection,reconstructions, and calibrations for internal use and reg-ular future public releases including these updates will beprovided.In the following, we give an account of the IceCubedetector (Sec. II), the event selection (Sec. III), and de-tector performance (Sec. IV). We also highlight changesto previous data selections and releases (Sec. V).
II. THE ICECUBE OBSERVATORY
The IceCube Observatory identifies neutrino interac-tions in the vicinity of the detector by the Cherenkovlight emitted by relativistic charged secondary particlestraveling through the deep ultra-clear glacial ice. Thein-ice detector consists of 5,160 Digital Optical Modules(DOMs) that are distributed across a cubic kilometer ofglacial ice at the South Pole [48, 49]. The DOMs are dis-tributed on 86 read-out and support cables (“strings”)and are deployed between 1.45 km and 2.45 km belowthe surface. Most strings follow a triangular grid witha width of 125 m, evenly spaced over the volume. TheDOMs consist of a photomultiplier tube, electronics fordigitization, and LEDs for detector calibration [48, 49].The main IceCube array has a neutrino energy thresh-old of about 100 GeV. Contained within the main Ice-Cube detector, a denser array in the clearest glacial ice,known as DeepCore, lowers the energy threshold to about10 GeV. The IceCube Observatory also includes a surfacearray of 82 pairs of water Cherenkov detectors, calledIceTop [50], that detects and reconstructs cosmic ray airshowers above 300 TeV.Neutrino interactions observed in the IceCube arraygenerally may either follow a track-like or cascade-liketopology. The track -like signal events originate primarilyin charged-current interactions of muon (anti-)neutrinos( ν µ & ¯ ν µ ) with nucleons producing energetic muons. Tau(anti-)neutrinos ( ν τ & ¯ ν τ ) may also produce charged-current interactions leading to energetic muons. Below700 GeV, secondary muons lose energy mainly due toionization; above 700 GeV, stochastic energy losses dueto radiative emission become the dominant component.At TeV energies, muons travel long distances, larger thanseveral kilometers in the Antarctic ice [51]. Light is con-stantly emitted along the track. The resulting long leverarm allows precise directional reconstruction with me-dian angular resolution ∆Ψ < ◦ . The absolute point-ing accuracy of IceCube has been demonstrated to be (cid:46) . ◦ [52] via measurements of the effect of the Moonshadow on the background cosmic ray (CR) flux.Charged-current interactions of astrophysical electronor tau (anti-)neutrinos, as well as neutral current inter-actions of any neutrino type, primarily produce cascade -like signal events with an almost spherically symmetricCherenkov light emission, resulting in a median angularresolution of ∼ ◦ –15 ◦ [53]. These signal event signa-tures are, in general, less useful for point-source studies,except in searches for soft neutrino sources in the South-ern hemisphere [54], extended Galactic neutrino emis-sion [54], and transient sources, such as γ -ray bursts [18].Moreover, the number of track-like events greatly out-numbers that of cascade-like events because neutrinoscan interact far outside the detector prior to the detec-tion of the secondary muon with IceCube.The majority of the background of the PSTracks sam-ple originates from CRs interacting with the atmosphereto produce showers of particles including atmosphericmuons and neutrinos. The atmospheric muons from theSouthern hemisphere are able to penetrate the ice and aredetected as track-like events in IceCube at a rate ordersof magnitude higher than the corresponding atmosphericneutrinos [1]. Atmospheric neutrinos also produce muonsfrom charged-current muon (anti-)neutrinos interactions,acting as an irreducible background in both hemispheres.Atmospheric muons from the Northern hemisphere arefiltered out by the Earth.This data release includes events that were observedduring the last three years of the construction phase ofthe IceCube observatory. These data seasons are referredto as IC40, IC59, and IC79 in Table I, with the names
Data SamplesSeason Start End Livetime Events Ref.IC40 2008/04/06 2009/05/20 376.4 d 36900 [9]IC59 2009/05/20 2010/05/31 352.6 d 107011 [10]IC79 2010/06/01 2011/05/13 316.0 d 93133 [55]IC86-I 2011/05/13 2012/05/15 332.9 d 136244 [11]IC86-II 2012/04/26 a b c a Start of test runs of new processing; remainder of this seasonbegan 2012/05/15 b Start of test runs of new processing; remainder of this seasonbegan 2014/05/06 c Start of test runs of new processing; remainder of this seasonbegan 2015/05/18
TABLE I. IceCube seasons with corresponding start and enddates, lifetime, and total event numbers. We also indicatereferences in which the sample selection is described in detail. corresponding to the number of installed detector strings.Years following detector completion are referred to asIC86 with a numeral indicating the years since comple-tion. Selections, software, and calibrations used by Ice-Cube varied through these years until being standardizedfor seasons starting in IC86-II.
PSTracks v3 includes updates to the selection andreconstruction for IC86-II through IC86-IV along withthree additional years of data. More than 80% of theevents from these seasons pass both v2 and v3 selections.The IC40 [36], IC59 [38], IC79, and IC86-I[47] selectionsremain unchanged relative to the
PSTracks v2 sampleand are identical to previously released versions of eachdataset. These years are included in the current data re-lease in order to standardize formatting and to provideeffective area and descriptions of detector responses.Below, we briefly describe the event selection used inthe released samples. See Tab. I references for further de-tails about each sample. Additionally, we describe the re-sponse of the
PSTracks v3 selection to signal of through-going muons from cosmic neutrinos and to atmosphericbackgrounds. For more detailed information, refer to [9],[10], and [11].
III. EVENT SELECTION
The
PSTracks event selection identifies high-energymuons passing through the IceCube detector with a goalof identifying sources of astrophysical neutrinos. Theselection applies differing criteria in the Northern andSouthern hemisphere – corresponding to events originat-ing below (“up-going”) and above (“down-going”) the log ( E estim [GeV]) − . − . . . . s i n ( δ )
90% IC86-201790% MC, γ =-390% MC, γ =-2 N u m b e r o f E v e n t s FIG. 1. The distribution of events in one year of data for thefinal event selection as a function of reconstructed declinationand estimated energy. The 90% energy range for the data(black), as well as simulated astrophysical signal Monte-Carlo(MC) for an E − and an E − spectrum are shown in magentaand orange respectively as a guide for the relevant energyrange of IceCube (from Ref. [13]). IceCube detector, respectively – with different atmo-spheric backgrounds. The boundary between the hemi-spheres is at declination δ = − ◦ , which is identical to azenith angle of 95 ◦ for the special location of IceCube.In the Northern hemisphere, atmospheric muons arefiltered by the Earth. While some atmospheric muons areerroneously reconstructed into the Northern sky, the mis-reconstructed events can be removed by selecting high-quality track-like events.In the Southern hemisphere, the atmospheric back-ground is reduced by strict cuts on the reconstructionquality and minimum energy, since the astrophysical neu-trino fluxes are expected to have a harder energy spec-trum than the background of atmospheric muons andneutrinos.Data seasons IC86-II through IC86-VII use multi-variate Boosted Decision Trees (BDT) to reduce thebackground of atmospheric muons and cascade events.Previous searches have shown the benefit of BDTs in theNorthern sky [12, 56]. In PSTracks v3 , a single BDT istrained for the Northern sky to recognize three classesof events: single muon tracks from atmospheric and as-trophysical neutrinos, atmospheric muons, and cascades;neutrino-induced tracks are treated as signal. This BDTuses 11 variables related to event topology and recon-struction quality. The Northern BDT preserves ∼
90% ofthe atmospheric neutrinos and ∼ .
1% of the atmosphericmuons from the initial selection of track-like events [13].In the Southern hemisphere, BDTs are used to selectonly the best-reconstructed track-like events at the high-est energies. In addition, the BDTs use four variables re-lated to deposited energy along the track, as well as thelight-arrival time of photons at the DOMs [11, 56]. The large backgrounds of atmospheric muons and muon bun-dles require harsh cuts to reduce their rate significantly,resulting in an effective selection of only very high energyevents. The selection effectively removes most South-ern hemisphere events with an estimated energy below (cid:39)
10 TeV; see Fig. 1. The IceTop surface array is used inaddition as an active veto against coincident air-showerevents for vertically down-going events [10].The final all-sky event rate of about 4 mHz is domi-nated by atmospheric muon neutrino interactions fromthe Northern hemisphere and by high-energy, well-reconstructed atmospheric muons in the Southern hemi-sphere. The preceding four years of data, collected withconfigurations IC40 through IC86-I, are handled exactlyas in the past [9–11, 55].
IV. DETECTOR RESPONSE
Muon tracks induced by astrophysical neutrino inter-actions are the main signal category in the search forpoint-like sources of neutrinos. Detailed Monte Carlosimulation is used to evaluate the response of IceCubeto such events and distinguish them from atmosphericbackgrounds. These simulations may be characterizedby a combination of the effective areas ( A eff ) and thereconstruction response functions.The number of expected events N ν is given by N ν = (cid:90) dt (cid:90) d Ω ∞ (cid:90) dE A eff ( E, Ω) φ ν ( E ν , Ω , t ) (1)The incident neutrino flux φ ν can have an assumed formor be derived from simulation; see [6]. The effective areafor each season varies as a function of neutrino energyand declination as shown in Figure 2. Tabulated effectiveareas for each season are included in this data release.Reconstruction of events in PSTracks proceeds in threesteps, each incorporating effects from modeling of theAntarctic glacial ice medium. To begin, the direction oforigin of the the candidate muon is reconstructed fromthe observed timing and charge in the detector follow-ing the algorithm described in Section 8.1 of Ref. [57].The angular distance between the reconstructed muondirection and the true neutrino direction is described bythe point spread function (“PSF”). Binned examples ofIceCube’s PSF are shown in Figure 3.The total energy loss of the muon track is then esti-mated following the description in section 9.1 of Ref. [58].The energy reconstruction yields a proxy for the muonenergy at detector entry and a lower limit on the candi-date neutrino energy. The observed distribution of theenergy proxy can vary significantly for different decli-nations. For the Southern sky, observed muons frommuon neutrino charged current interactions occur nearthe detector, giving an energy proxy close to the origi-nal neutrino’s energy. For the Northern sky, neutrinosmay interact while crossing the Earth before reaching True Neutrino Energy (GeV) T r u e S i n () IC40 Effective Area CC E ff e c t i v e A r e a ( c m ) True Neutrino Energy (GeV) T r u e S i n () IC59 Effective Area CC E ff e c t i v e A r e a ( c m ) True Neutrino Energy (GeV) T r u e S i n () IC79 Effective Area CC E ff e c t i v e A r e a ( c m ) True Neutrino Energy (GeV) T r u e S i n () IC86-I Effective Area CC E ff e c t i v e A r e a ( c m ) True Neutrino Energy (GeV) T r u e S i n () IC86-II Effective Area CC E ff e c t i v e A r e a ( c m ) FIG. 2. The effective areas for each uniform data-taking period included in the current data release. IC40 through IC79used the partially-completed detector while IC86-I and later followed detector completion. Software and calibration differencesseparate IC86-I from later years. Differences in the tools and applied selection have a small, but important impact on thesample for each period. True Angular Separation, ( ) F r a c t i o n i n B i n Northern Sky True Angular Separation, ( ) F r a c t i o n i n B i n Horizon True Angular Separation, ( ) F r a c t i o n i n B i n Southern Sky
FIG. 3. The binned point spread functions measured for the Northern sky ( δ < − ◦ ), horizon ( − ◦ ≤ δ < − ◦ ), andSouthern sky ( δ ≥ ◦ ) for IC86-II and later seasons. Each colored histogram corresponds to a different true neutrino energyrange. For a falling E − spectrum, most muons are reconstructed less than 1 ◦ from the neutrino origin. Log (Energy Proxy) F r a c t i o n i n B i n Northern Sky
Log (Energy Proxy) F r a c t i o n i n B i n Horizon
Log (Energy Proxy) F r a c t i o n i n B i n Southern Sky
FIG. 4. The binned muon energy proxy reconstruction measured for the Northern sky ( δ < − ◦ ), horizon ( − ◦ ≤ δ < − ◦ ),and Southern sky ( δ ≥ ◦ ) for IC86-II and later seasons. Each colored histogram corresponds to a different true neutrinoenergy range. In the Southern sky, high energy events reconstruct near the incident neutrino energy. In the Northern sky andat the horizon, high energy events may interact far from the detector, producing energy losses which are not visible in IceCube. IceCube, leading to unobservable energy losses, particu-larly at high energies. The energy proxy reconstructionis shown for IC86-II and later seasons in Figure 4.The final stage is the estimation of the reconstruc-tion angular uncertainty. The reconstruction likelihoodspace near the best-fit direction is mapped and fit witha paraboloid following Ref. [59]. The two dimensionalwidth of the paraboloid fit is circularized by averaging thewidth across the two axes. In cases where the paraboloidmethod fails,
PSTracks instead relies on the Cramer-Raomethod described in Ref. [60]. In order to correct forthe kinematic angle between neutrino and muon direc-tion and to ensure correct coverage, a correction as afunction of reconstructed energy is applied assuming an E − flux such that the median estimated uncertainty asa function of energy gives 50% containment for a two di-mensional Gaussian distribution. While this correctioncan change with differing flux assumptions, the impactis small. A lower limit of 0.2 ◦ is applied to all events inorder to avoid strong impacts from mismodeling of iceproperties and to ensure that no single event dominatesour likelihood calculations. The reconstruction angularuncertainties are shown in Figure 5.Reconstructed quantities are used to build probabilitydensity functions that the point source analysis uses inapplying a maximum likelihood method. See Ref. [13] fordetails of the likelihood construction, which exploits thespectral and spatial differences of astrophysical neutrinosand atmospheric backgrounds. V. COMPARISON TO PREVIOUS RELEASES
There have been multiple previous IceCube data re-leases presenting track-like events in the Northern andSouthern hemisphere, primarily for the purpose of neu-trino astronomy [9, 10, 42, 43, 45]. The dataset detailedin this document is the latest iteration of a high statis-tics sample of track-like events. In this way, this datasetcan be considered to be a successor of the previous datareleases [36, 38, 42], providing an updated description ofthe data from 2010–2012 [42], as well as adding six addi-tional years of data in 2012–2018. Notably, this samplewas used for the IceCube 10-year all-sky time-integratedanalysis detailed in Ref. [13].This sample includes several improvements in additionto the standardization of the IC86 data taking periodspublished in Ref. [42]. In the latest version of the datasample, referred to here as
PSTracks v3 , the event clas-sifier and sample pre-cuts have been altered to better re-ject cascade-like events and accept track-like events. Ad-ditionally, the angular reconstruction has been updated,with more than a 10% improvement in angular resolutionfor events greater than 10 TeV [13]. The energy proxyremains unchanged between the two versions of the sam-ple.The net effect of the sample changes is an increase inevent rate ( ∼ PSTracks v2 ) and newer (
PSTracks v3 ) ver- Estimated Angular Uncertainty ( ) F r a c t i o n i n B i n Northern Sky Estimated Angular Uncertainty ( ) F r a c t i o n i n B i n Horizon Estimated Angular Uncertainty ( ) F r a c t i o n i n B i n Southern Sky
FIG. 5. The binned estimated angular uncertainty on the reconstructed direction measured for the Northern sky ( δ < − ◦ ),horizon ( − ◦ ≤ δ < − ◦ ), and Southern sky ( δ ≥ ◦ ) for IC86-II and later seasons. Each colored histogram corresponds toa different true neutrino energy range. The estimated angular uncertainties have been calibrated to give correct coverage foran E − spectrum. In order to avoid unaccounted-for uncertainties and to ensure no single event dominates our likelihood, afloor of 0.2 ◦ is included for all events. sions of this sample can be seen in Table II. A comparisonof the one-year time-integrated sensitivity for the IC86-IV season for the two samples can be seen in Figure 6.While the PSTracks v3 selection is expected to be, onaverage, more sensitive than the v2 selection, differencesin event counts or reconstructions may lead to more var-ied changes in specific results.As an example of how the changing content of the dif-ferent versions of this data sample can affect the pro-cess of searching for hotspots in IceCube data, we ex-amine the 2014/2015 neutrino flare associated with TXS0506+056 [35]. The 3 . σ excess seen in 2014/2015 [35]was originally identified using the data sample corre-sponding to the data release Ref. [45]. Here, we re-peat the untriggered flare search analysis, originally per-formed in Ref. [35], but instead use the newest version ofthe data sample presented in this document, PSTracksv3 . The results of this cross-check can be seen in Ta-ble III. Notably, the significance of the 2014/2015 neu-trino flare decreases from p = 7 . × − ( PSTracks v2 )to p = 8 . × − ( PSTracks v3 ) when using the mostrecent version of the data sample. A comparison of thereconstructed parameters of the most signal-like neutrinoevents contributing to the 2014/2015 flare in both ver-sions of the data sample can be seen in Table IV andFigure 7.The lower significance of the 2014/2015 neutrino flarein the most recent version of the sample has mainlybeen caused by the absence of two cascade-like events,occurring at MJD=56992.1586 and MJD=57014.1910,that existed in the
PSTracks v2 data sample [45] as-sociated with Ref. [35], but have been removed fromthe
PSTracks v3 data sample presented in this docu-ment. While cascade-like events may be used to searchfor point sources, they provide worse localization thantrack-like events and can provide additional backgrounds.In
PSTracks v2 , a contribution from cascade-like eventspassing the selection was included in both the back-ground and signal modeling. In PSTracks v3, events mustpass a track length pre-cut requiring that all northern-sky events have a reconstructed track length greaterthan 200 meters, reducing the contribution from cas- cade events. As the two events at MJD=56992.1586and MJD=57014.1910 have reconstructed track lengthsless than 200 meters, they are removed from
PSTracksv3 prior to the application of the BDT. Performing theuntriggered flare search using
PSTracks v2 (Ref. [45])with the two cascade events manually removed results ina drop in significance similar to that which is observedwhen using
PSTracks v3 , as seen in Table III. The dropin significance cannot be otherwise adequately explainedby changes to the angular reconstruction or other differ-ences between the two versions of the sample.It should be noted that the apparent drop in signifi-cance of the 2014/2015 neutrino flare is not entirely un-precedented. A reduction in the pre-trials significanceof a time-integrated analysis preformed only at the loca-tion of TXS 056+056 is also seen in Ref. [13] when usingthe newer version of this sample: p = 2 . × − (4 . σ )with PSTracks v2 [35], and p = 1 . × − (3 . σ ) with PSTracks v3 [13]. Note that these significances do notinclude corrections for the number of searches (e.g. nei-ther of these values are penalized for the fact that wehave examined TXS 0506+056 multiple times, nor thefact that this same framework has been applied to othersource locations), as in Ref. [13] and Ref. [35], and aresimply used to compare the results of similar statisticalframeworks applied to both
PSTracks v2 and
PSTracksv3 .While both the time integrated and untriggered flareresults associated with TXS 0506+056 appear to be lesssignificant when using the newer version of this data sam-ple, it is important to recognize that the results presentedabove are a posteriori cross checks preformed in order toexplore the effects of the altered content of
PSTracks v3 in comparison to previous versions. Because
PSTracksv2 and
PStracks v3 differ in the specific event contentand reconstructions, some fluctuations in significance ofsource candidates between versions is expected. Bothsamples are self-consistent, with
PSTracks v3 expectedto show better sensitivity to a generic, all-sky time-integrated analysis. For this reason,
PSTracks v3 is pre-ferred in the general use case.
Event Comparison Between
PSTracks v2 and
PSTracks v3
Season Start End Livetime
PSTracks v2 PSTracks v3 v2 → v3 Overlap v3 → v2 OverlapIC86-II 2012/04/26 a b a Start date for test runs of the new processing. The remainder of this season began 2012/05/15 b Start date for test runs of the new processing. The remainder of this season began 2014/05/06
TABLE II. A comparison of the sample content between
PSTracks v2 and
PSTracks v3 for the period of overlap between thetwo samples. The rightmost two columns report the overlap in event content between the old and new versions of the samplesfor periods of shared livetime. The entry “ v2 → v3 ” refers to the percentage of events in PSTracks v2 that are also in
PSTracksv3 , and “ v3 → v2 ” is the reverse. The older version ( v2 ) of the sample has been discontinued as of the IC86-2015 season, havingbeen replaced by PSTracks v3 . Seasons prior to IC86-II are identical between the two versions of the sample, and seasons afterIC86-IV only exist in the newer ( v3 ) version of the sample.Untriggered Flare Cross-check ResultsSample p-value (pre-trial) T start T stop n s γ PSTracks v2 [35, 45] 7.0e-5 56937.81 57096.22 14.39 2.20
PSTracks v2 w/o cascades 1.17e-3 56937.81 57112.65 12.22 2.26
PSTracks v3 (this release) 8.14e-3 56927.86 57116.76 11.87 2.22TABLE III. The results of repeating the untriggered flare analysis preformed in [35], but using
PSTracks v3 in place of
PSTracks v2 [45], the dataset that was originally used. The apparent drop in significance when using
PSTracks v3 can beexplained by cascade-like events present in v2 that have been removed from v3 .Events Contributing to the 2014 TXS 0506+056 Neutrino Flare PSTracks v2 [35, 45]
PSTracks v3 (this release)MJD RA (deg) Dec (deg) σ (deg) log ( E/ GeV) RA (deg) Dec (deg) σ (deg) log ( E/ GeV)56940.9084 77.55 5.40 0.20 3.97 77.35 5.42 0.20 3.9757009.5301 77.28 5.54 0.38 3.91 77.32 5.50 0.34 3.9157089.4395 77.68 5.89 0.20 3.69 77.71 5.90 0.20 3.6957072.9895 76.45 5.43 1.09 4.17 76.35 5.22 0.36 4.1756992.1586 78.82 6.26 1.77 4.30 - - - -56981.1313 76.34 6.04 0.50 4.13 76.16 6.19 0.43 4.1356955.7917 77.55 5.72 0.36 3.09 77.60 5.56 0.48 3.0957014.1910 77.49 5.79 1.65 3.79 - - - -57112.6530 77.14 5.54 0.98 3.46 77.43 5.34 1.09 3.4656991.9383 76.77 6.06 0.79 3.42 76.77 5.80 0.77 3.4257072.2089 77.03 5.14 1.05 3.43 76.35 5.22 0.36 3.4356990.4325 77.14 5.01 0.60 1.99 77.14 5.15 0.63 1.9956940.5215 77.90 5.82 0.78 2.82 - - - -56937.8190 77.73 6.36 0.64 2.91 77.75 6.23 0.63 2.9156973.3971 - - - - 77.05 5.05 0.40 3.7156927.8601 - - - - 77.39 4.93 0.33 3.5356917.5296 78.27 5.86 0.54 3.05 78.32 5.85 0.52 3.05TABLE IV. The most signal-like events contributing to the 2014/2015 TXS 0506+056 neutrino flare in, both, the data samplepublished in Ref. [45] (
PSTracks v2 ) as well as the data sample presented here (
PSTracks v3 ). There were no changes toenergy reconstruction between the two sample versions, but the angular reconstruction and sample event content have changed.The events occurring at MJD=56992.1586 and MJD=57014.1910 are cascade events that have been treated as tracks by thereconstruction, and as such the direction and energy information reported in the
PSTracks v2 sample is unlikely to be a gooddescription of the true event properties. + T e V ( G e V c m s ) Time-Integrated Sensitivity for IC86-IVPSTracks v2PSTracks v3 sin( ) P S v2 P S v3 FIG. 6. A comparison of the 90% C.L. sensitivity of a time-integrated point source search to an E − source at variousdeclinations. This is similar to the curves in figure 3 of Ref. [13], but here we calculate these values using only the IC86-IVseason of both PSTracks v2 and
PSTracks v3 for the purpose of comparing the two. For most declinations (particularly nearthe horizon),
PSTracks v3 is a slight improvement over
PSTracks v2 .
74 75 76 77 78 79 80
RA [degrees] D e c [ d e g r ee s ] MJD:56992.15MJD:57014.19
PSTracks v2 TXS 0506+056 l o g ( E n e r g y P r o x y )
74 75 76 77 78 79 80
RA [degrees] D e c [ d e g r ee s ] PSTracks v3 TXS 0506+056 l o g ( E n e r g y P r o x y ) FIG. 7. The top 14 most signal-like flare events contributing to the 2014/2015 neutrino flare associated with TXS 0506+056(black “ × ”), both in PSTracks v2 (left, used for the analysis published in Ref. [35]), and the updated sample presented in thisdocument (
PSTracks v3 , right). The two cascade-like events present in v2 that were subsequently removed in v3 are shown asdashed circles in the plot on the left. The size of the colored circles corresponds to the 1 σ containment region of the angularreconstruction of that event, and the color of the circle corresponds to the reconstructed energy proxy. PSTracks v2
MJD
PSTracks v3 l o g ( E n e r g y P r o x y ) FIG. 8. The approximate time window of the 2014 neutrino flare associated with TXS 0506+056. Events listed in Table IVare plotted as vertical lines with height equal to the event reconstructed energy proxy. Events present in
PSTracks v2 , but not
PSTracks v3 are shown as dotted orange lines.
ACKNOWLEDGMENTS
USA – U.S. National Science Foundation-Office of Po-lar Programs, U.S. National Science Foundation-PhysicsDivision, Wisconsin Alumni Research Foundation, Cen-ter for High Throughput Computing (CHTC) at theUniversity of Wisconsin–Madison, Open Science Grid(OSG), Extreme Science and Engineering DiscoveryEnvironment (XSEDE), U.S. Department of Energy-National Energy Research Scientific Computing Cen-ter, Particle astrophysics research computing center atthe University of Maryland, Institute for Cyber-EnabledResearch at Michigan State University, and Astropar-ticle physics computational facility at Marquette Uni-versity; Belgium – Funds for Scientific Research (FRS-FNRS and FWO), FWO Odysseus and Big Science pro-grammes, and Belgian Federal Science Policy Office (Bel-spo); Germany – Bundesministerium f¨ur Bildung undForschung (BMBF), Deutsche Forschungsgemeinschaft (DFG), Helmholtz Alliance for Astroparticle Physics(HAP), Initiative and Networking Fund of the HelmholtzAssociation, Deutsches Elektronen Synchrotron (DESY),and High Performance Computing cluster of the RWTHAachen; Sweden – Swedish Research Council, SwedishPolar Research Secretariat, Swedish National Infrastruc-ture for Computing (SNIC), and Knut and Alice Wallen-berg Foundation; Australia – Australian Research Coun-cil; Canada – Natural Sciences and Engineering ResearchCouncil of Canada, Calcul Qu´ebec, Compute Ontario,Canada Foundation for Innovation, WestGrid, and Com-pute Canada; Denmark – Villum Fonden, Danish Na-tional Research Foundation (DNRF), Carlsberg Foun-dation; New Zealand – Marsden Fund; Japan – JapanSociety for Promotion of Science (JSPS) and Institutefor Global Prominent Research (IGPR) of Chiba Uni-versity; Korea – National Research Foundation of Korea(NRF); Switzerland – Swiss National Science Foundation(SNSF); United Kingdom – Department of Physics, Uni-versity of Oxford. ∗ also at Universit`a di Padova, I-35131 Padova, Italy † also at National Research Nuclear University, MoscowEngineering Physics Institute (MEPhI), Moscow115409, Russia ‡ also at Earthquake Research Institute, University ofTokyo, Bunkyo, Tokyo 113-0032, Japan[1] M. Aartsen et al. , (IceCube Collaboration), JINST no. 03, (2017) P03012, arXiv:1612.05093 .[2] M. Aartsen et al. , (IceCube Collaboration), Phys. Rev.Lett. (2013) 021103, arXiv:1304.5356 .[3] M. Aartsen et al. , (IceCube Collaboration),
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