Search for dark matter annihilations in the Sun with the 79-string IceCube detector
IceCube collaboration, M. G. Aartsen, R. Abbasi, Y. Abdou, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, D. Altmann, K. Andeen, J. Auffenberg, X. Bai, M. Baker, S. W. Barwick, V. Baum, R. Bay, K. Beattie, J. J. Beatty, S. Bechet, J. Becker Tjus, K.-H. Becker, M. Bell, M. L. Benabderrahmane, S. BenZvi, J. Berdermann, P. Berghaus, D. Berley, E. Bernardini, D. Bertrand, D. Z. Besson, D. Bindig, M. Bissok, E. Blaufuss, J. Blumenthal, D. J. Boersma, S. Bohaichuk, C. Bohm, D. Bose1, S. Böser, O. Botner, L. Brayeur, A. M. Brown, R. Bruijn, J. Brunner, S. Buitink, M. Carson, J. Casey, M. Casier, D. Chirkin, B. Christy, K. Clark, F. Clevermann, S. Cohen, D. F. Cowen, A. H. Cruz Silva, M. Danninger, J. Daughhetee, J. C. Davis, C. De Clercq, S. De Ridder, F. Descamps, P. Desiati, G. de Vries-Uiterweerd, T. DeYoung, J. C. Díaz-Vélez, J. Dreyer, J. P. Dumm, M. Dunkman, R. Eagan, B. Eberhardt, J. Eisch, R. W. Ellsworth, O. Engdegård, S. Euler, P. A. Evenson, O. Fadiran, A. R. Fazely, A. Fedynitch, J. Feintzeig, T. Feusels, K. Filimonov, C. Finley, T. Fischer-Wasels, S. Flis, A. Franckowiak, R. Franke, K. Frantzen, T. Fuchs, T. K. Gaisser, J. Gallagher, L. Gerhardt, L. Gladstone, T. Glüsenkamp, A. Goldschmidt, G. Golup, J. A. Goodman, D. Góra, D. Grant, A. Groß, S. Grullon, et al. (177 additional authors not shown)
aa r X i v : . [ a s t r o - ph . H E ] S e p APS/123-QED
Search for dark matter annihilations in the Sun with the 79-string IceCube detector
M. G. Aartsen, R. Abbasi, Y. Abdou, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, D. Altmann, J. Auffenberg, X. Bai, ∗ M. Baker, S. W. Barwick, V. Baum, R. Bay, K. Beattie, J. J. Beatty,
17, 18
S. Bechet, J. Becker Tjus, K.-H. Becker, M. Bell, M. L. Benabderrahmane, S. BenZvi, J. Berdermann, P. Berghaus, D. Berley, E. Bernardini, A. Bernhard, D. Bertrand, D. Z. Besson, D. Bindig, M. Bissok, E. Blaufuss, J. Blumenthal, D. J. Boersma,
39, 1
S. Bohaichuk, C. Bohm, D. Bose, S. B¨oser, O. Botner, L. Brayeur, A. M. Brown, R. Bruijn, J. Brunner, S. Buitink, M. Carson, J. Casey, M. Casier, D. Chirkin, B. Christy, K. Clark, F. Clevermann, S. Cohen, D. F. Cowen,
38, 37
A. H. Cruz Silva, M. Danninger, J. Daughhetee, J. C. Davis, C. De Clercq, S. De Ridder, P. Desiati, G. de Vries-Uiterweerd, M. de With, T. DeYoung, J. C. D´ıaz-V´elez, J. Dreyer, M. Dunkman, R. Eagan, B. Eberhardt, J. Eisch, R. W. Ellsworth, O. Engdeg˚ard, S. Euler, P. A. Evenson, O. Fadiran, A. R. Fazely, A. Fedynitch, J. Feintzeig, T. Feusels, K. Filimonov, C. Finley, T. Fischer-Wasels, S. Flis, A. Franckowiak, R. Franke, K. Frantzen, T. Fuchs, T. K. Gaisser, J. Gallagher, L. Gerhardt,
8, 7
L. Gladstone, T. Gl¨usenkamp, A. Goldschmidt, G. Golup, J. A. Goodman, D. G´ora, D. Grant, A. Groß, M. Gurtner, C. Ha,
8, 7
A. Haj Ismail, A. Hallgren, F. Halzen, K. Hanson, D. Heereman, P. Heimann, D. Heinen, K. Helbing, R. Hellauer, S. Hickford, G. C. Hill, K. D. Hoffman, R. Hoffmann, A. Homeier, K. Hoshina, W. Huelsnitz, † P. O. Hulth, K. Hultqvist, S. Hussain, A. Ishihara, E. Jacobi, J. Jacobsen, G. S. Japaridze, K. Jero, O. Jlelati, B. Kaminsky, A. Kappes, T. Karg, A. Karle, J. L. Kelley, J. Kiryluk, F. Kislat, J. Kl¨as, S. R. Klein,
8, 7
J.-H. K¨ohne, G. Kohnen, H. Kolanoski, L. K¨opke, C. Kopper, S. Kopper, D. J. Koskinen, M. Kowalski, M. Krasberg, G. Kroll, J. Kunnen, N. Kurahashi, T. Kuwabara, M. Labare, H. Landsman, M. J. Larson, M. Lesiak-Bzdak, J. Leute, J. L¨unemann, J. Madsen, R. Maruyama, K. Mase, H. S. Matis, F. McNally, K. Meagher, M. Merck, P. M´esz´aros,
T. Meures, S. Miarecki,
8, 7
E. Middell, N. Milke, J. Miller, L. Mohrmann, T. Montaruli, ‡ R. Morse, R. Nahnhauer, U. Naumann, H. Niederhausen, S. C. Nowicki, D. R. Nygren, A. Obertacke, S. Odrowski, A. Olivas, M. Olivo, A. O’Murchadha, L. Paul, J. A. Pepper, C. P´erez de los Heros, C. Pfendner, D. Pieloth, N. Pirk, J. Posselt, P. B. Price, G. T. Przybylski, L. R¨adel, K. Rawlins, P. Redl, E. Resconi, W. Rhode, M. Ribordy, M. Richman, B. Riedel, J. P. Rodrigues, C. Rott, T. Ruhe, B. Ruzybayev, D. Ryckbosch, S. M. Saba, T. Salameh, H.-G. Sander, M. Santander, S. Sarkar, K. Schatto, M. Scheel, F. Scheriau, T. Schmidt, M. Schmitz, S. Schoenen, S. Sch¨oneberg, L. Sch¨onherr, A. Sch¨onwald, A. Schukraft, L. Schulte, O. Schulz, D. Seckel, S. H. Seo, Y. Sestayo, S. Seunarine, C. Sheremata, M. W. E. Smith, M. Soiron, D. Soldin, G. M. Spiczak, C. Spiering, M. Stamatikos, § T. Stanev, A. Stasik, T. Stezelberger, R. G. Stokstad, A. St¨oßl, E. A. Strahler, R. Str¨om, G. W. Sullivan, H. Taavola, I. Taboada, A. Tamburro, S. Ter-Antonyan, S. Tilav, P. A. Toale, S. Toscano, M. Usner, D. van der Drift,
8, 7
N. van Eijndhoven, A. Van Overloop, J. van Santen, M. Vehring, M. Voge, M. Vraeghe, C. Walck, T. Waldenmaier, M. Wallraff, R. Wasserman, Ch. Weaver, M. Wellons, C. Wendt, S. Westerhoff, N. Whitehorn, K. Wiebe, C. H. Wiebusch, D. R. Williams, H. Wissing, M. Wolf, T. R. Wood, K. Woschnagg, C. Xu, D. L. Xu, X. W. Xu, J. P. Yanez, G. Yodh, S. Yoshida, P. Zarzhitsky, J. Ziemann, S. Zierke, A. Zilles, and M. Zoll (IceCube Collaboration) III. Physikalisches Institut, RWTH Aachen University, D-52056 Aachen, Germany School of Chemistry & Physics, University of Adelaide, Adelaide SA, 5005 Australia Dept. of Physics and Astronomy, University of Alaska Anchorage,3211 Providence Dr., Anchorage, AK 99508, 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 Physikalisches Institut, Universit¨at Bonn, Nussallee 12, D-53115 Bonn, Germany Universit´e Libre de Bruxelles, Science Faculty CP230, B-1050 Brussels, Belgium Vrije Universiteit Brussel, Dienst ELEM, B-1050 Brussels, Belgium Dept. of Physics, Chiba University, Chiba 263-8522, Japan 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 Physics and Center for Cosmology and Astro-Particle Physics,Ohio State University, Columbus, OH 43210, USA Dept. of Astronomy, Ohio State University, Columbus, OH 43210, USA Dept. of Physics, TU Dortmund University, D-44221 Dortmund, Germany Dept. of Physics, University of Alberta, Edmonton, Alberta, Canada T6G 2G7 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 Laboratory for High Energy Physics, ´Ecole Polytechnique F´ed´erale, CH-1015 Lausanne, Switzerland Dept. of Physics and Astronomy, University of Kansas, Lawrence, KS 66045, USA Dept. of Astronomy, University of Wisconsin, Madison, WI 53706, USA Dept. of Physics and Wisconsin IceCube Particle Astrophysics Center,University of Wisconsin, Madison, WI 53706, USA Institute of Physics, University of Mainz, Staudinger Weg 7, D-55099 Mainz, Germany Universit´e de Mons, 7000 Mons, Belgium T.U. Munich, D-85748 Garching, Germany Bartol Research Institute and Department of Physics and Astronomy,University of Delaware, Newark, DE 19716, USA Dept. of Physics, University of Oxford, 1 Keble Road, Oxford OX1 3NP, UK Dept. of Physics, University of Wisconsin, River Falls, WI 54022, USA Oskar Klein Centre and Dept. of Physics, Stockholm University, SE-10691 Stockholm, Sweden Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794-3800, USA 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-15735 Zeuthen, Germany (Dated: September 4, 2015)We have performed a search for muon neutrinos from dark matter annihilation in the center ofthe Sun with the 79-string configuration of the IceCube neutrino telescope. For the first time, theDeepCore sub-array is included in the analysis, lowering the energy threshold and extending thesearch to the austral summer. The 317 days of data collected between June 2010 and May 2011are consistent with the expected background from atmospheric muons and neutrinos. Upper limitsare set on the dark matter annihilation rate, with conversions to limits on spin-dependent and spin-independent WIMP-proton cross-sections for WIMP masses in the range 20 - 5000 GeV/c . Theseare the most stringent spin-dependent WIMP-proton cross-sections limits to date above 35 GeV/c for most WIMP models. PACS numbers: 95.35.+d, 14.80.Nb, 14.80.Rt, 96.50.S-, 98.70.Sa
While the presence of dark matter (DM) in the uni-verse has been inferred through its gravitational inter-actions, its nature remains a mystery. One of the mostpromising and experimentally accessible candidates forDM are so-called Weakly Interacting Massive Particles(WIMPs) [1], predicted in extensions of the StandardModel of particle physics (SM). DM may be capturedin large celestial bodies like the Sun [2] where self-annihilation to SM particles can result in a flux of high-energy neutrinos. These neutrinos can be searched foras a point-like source by IceCube [3, 4]. These indirectsearches for DM are sensitive to the WIMP-proton scat-tering cross section, which initiates the capture process in the Sun. They complement direct DM searches onEarth as they scale with the averaged DM density alongthe solar circle and are more sensitive to low WIMP ve-locities [5]. Indirect searches depend only weakly on theunderlying WIMP velocity distribution [6] and we havechosen parameters to be conservative in our analysis.In this work, we present new IceCube limits on darkmatter captured by the Sun, with data taken in the 79-string configuration of the detector. This analysis incor-porates two significant additions compared to previouswork. Firstly, we extend the search to the austral sum-mer when the Sun is above the horizon. This doubles thelivetime of the analysis, but imposes new challenges to re-duce the downgoing atmospheric muon background. Sec-ondly, we search for neutrinos from WIMPs with masses( m χ ) as low as 20 GeV/c whereas past IceCube searcheshave only been sensitive above 50 GeV/c .The IceCube detector [7] is situated at the South Pole.Digital Optical Modules (DOMs) arranged on verticalstrings deep in the ice sheet record the Cherenkov lightemitted by relativistic charged particles, including suchcreated in neutrino interactions in the ice. The detectionof photon yields and arrival times in DOMs allows thereconstruction of direction and energy of the secondaries.This analysis used 317 live-days of data taken betweenJune 2010 and May 2011. During this period, thedetector was operating in its 79-string configuration,which includes six more densely instrumented strings inthe center of the array, optimized for low energies. Thesestrings feature reduced vertical spacing between DOMsand higher quantum efficiency photomultiplier tubes.Along with the seven surrounding regular strings, theyform the DeepCore subarray [8]. Both the improvementin livetime and in energy threshold, which this analysishas achieved over previous IceCube analyses, can beattributed to the use of the DeepCore array.The background in this search consists of muonsand neutrinos created in cosmic ray interactions in theEarth’s atmosphere. The dominant down-going muoncomponent is simulated with CORSIKA [11], including sim-ulations of single and coincident air showers. The ν µ and ν e components of the atmospheric spectrum are gener-ated following the Honda flux model [12]. For verificationand cross-checks, a dedicated simulation of atmospheric ν s below 200 GeV/c is performed with GENIE [13]. Thebackground at final analysis level from solar atmosphericneutrinos, originating from cosmic ray interactions in theSun’s atmosphere, has been calculated to be of order 1event, independent of the flux model [14–16]. To reducethe dependence on simulation and associated systematicerrors, we use off-source data to estimate the backgroundat all analysis levels. Background simulation is merelyused to verify accurate understanding of the detector.Off-source data consists of data recorded when the Sunwas outside the respective analysis region.Propagation of muons through the ice is simulated [18],and transport of light from these particles to the DOMs isperformed using direct photon tracking [19], taking intoaccount measured ice properties [20]. Particle and pho-ton propagation simulations at the lowest targeted ener-gies below 50 GeV/c have been independently verifiedusing GEANT4 [17].In this work the full dataset is split into three indepen-dent non-overlapping event selections; first into ‘summer’and ‘winter’ seasons, when the Sun is above and belowthe horizon, respectively. The ‘winter’ dataset is fur-ther split into a low energy sample (WL), with focuson neutrino-induced muon tracks starting within Deep- Core, and a higher energy sample (WH), aiming to selecttrack-like events with no particular containment require-ment. The ‘summer’ selection is a dedicated low energyevent sample (SL) for which the surrounding IceCubestrings are used as an active muon veto in order to se-lect neutrino-induced events starting within DeepCore.Separation into these samples is necessary owing to thedifferent characteristics of the overwhelming down-goingmuon background within each dataset. The event selec-tion is carried out separately for each independent sam-ple and the final search is conducted using a combinedlikelihood function. In order to avoid potential bias, astrict blindness criterion is imposed by scrambling theazimuthal position of the Sun in data.In IceCube, filters pre-select data to enhance the con-tent of signal-like muon events above the dominant at-mospheric muon background. To increase the signal-to-background ratio, we only select events that pass anyof three filters: the dedicated DeepCore low energy fil-ter [8] and two filters selecting muon-like events with anupwards pointing track reconstruction. At this point,the dataset is split into the two seasonal streams, whereSeptember 22nd 2010 and March 22nd 2011 mark thebeginning and ending dates of the SL selection. We firstdiscuss the additional ‘winter’ cut selections: Cuts areapplied on the zenith angle and quality of the likelihood-based track reconstruction, on hit and string multiplic-ity, and on timing and topological variables. For Deep-Core contained events, the zenith acceptance region isextended to reflect the broadened signal point spreadfunction at low energies.The first data reduction is followed by additional pro-cessing, including an estimate of the angular uncertaintyof the muon track fit. Some signal neutrinos will arrivein coincidence with atmospheric backgrounds ( 10%). Inorder to retain these signal events, a set of topologicalcriteria are applied to ‘split’ these combined hit patternsinto distinct sub-events. These sub-events are then pro-cessed as above, and undergo all subsequent event selec-tion in their own right. Following the addition of eventsfrom splitting, the dataset is divided into independentlow and high energy event samples. For events to be in-cluded in the WL sample, we demand that the numberof hit DOMs within DeepCore must be larger than out-side. Additionally, the number of outside hits must beless than seven. This ensures that events with a long leverarm and therefore good angular resolution are assignedto the complement sample. Events that fail the WL cri-teria are classified as WH events, and undergo a series ofadditional, stricter cuts on the same variables as in theinitial event selection. WL events, conversely, undergo aveto cut, removing events with hits in the 10 upper mostlayers of DOMs on the regular (non-DeepCore) strings.The final background reduction utilizes one Boosted De-cision Tree (BDT) [38] for each dataset to discriminatetrue up-going muon-like events from mis-reconstructed dataset WH (winter, high-energy) E v en t s dataset WL (winter, low-energy) ) Ψ cos( dataset SL (summer, low-energy) FIG. 1. Cosine of the angle between the reconstructed trackand the direction of the Sun, Ψ, for observed events (squares)with one standard deviation error bars, and the atmosphericbackground expectation from atmospheric muons and neutri-nos (dashed line). Also shown is a simulated signal (1 TeV/c hard for dataset WH, 50 GeV/c hard for datasets WL andSL) scaled to µ (details in Table I). atmospheric muons. For training and testing an inde-pendent, high statistics, set of signal simulations is usedand discarded afterwards. For background training thismultivariate analysis uses one month of off-source data.Through an iterative process, individual variables wereremoved and added and the performance of the BDTevaluated, until we arrived at a final set of 14 variablesin the WH stream and 10 in the WL stream. All inputdistributions for simulated backgrounds and data are ingood agreement. The selected variables describe boththe quality of the track reconstruction and the time evo-lution of the pattern of hit DOMs and spatial positionswithin the detector.The SL event sample uses a different set of cuts, be-cause the dominant background is comprised of well-reconstructed down-going muons penetrating the detec-tor. To reduce these backgrounds, we focus on low m χ signals with a reconstructed neutrino interaction vertexinside the DeepCore fiducial volume. Selecting only theseevents, cuts are placed on the zenith angle of the trackreconstruction, hit multiplicity, and vertical extension ofthe event. A 14 DOM layer top veto is imposed to re-ject down-going events. Additionally, events are requiredto be DeepCore dominated (defined in the same wayas for the ‘winter’ analysis) and fulfill a tight hit-timecontainment criterion. The final step in background re-jection again consists of one BDT with 10 input vari-ables. These are selected using the same iterative selec- tion process. Track quality parameters yield less separa-tion power within this down-going sample. As a result,the final BDT input observables mainly describe the de-gree of containment and the vertical and lateral extensionof the event within the detector.The cut on the BDT score is optimized for eachevent selection to minimize the model rejection factor,MRF [25], in the full likelihood analysis. Total signalcut-efficiencies range between 1-5% for low m χ signalsand up to 30-40% for high m χ . The final step of theanalysis is a likelihood ratio hypothesis test based on thevalues of the reconstructed angle to the Sun Ψ, using theFeldman-Cousins unified approach [24]. This results inconfidence intervals for the mean number of signal events, µ s . The required probability densities for signal are com-puted from simulations, while for background they arebased on real data events at the final selection level, withscrambled azimuth direction. A single result is calculatedfrom all three data samples with a combined likelihood,constructed from the set of three independent probabilitydistributions of signal and background, weighting each bythe respective livetime and effective volume (see Ref. [4]for details).After unblinding the direction of the events in the finaldata samples, the observed distributions are compared tothe expected background distributions from atmosphericmuons and neutrinos, shown in Fig. 1. The observednumber of events from the direction of the Sun are con-sistent with the background-only hypothesis. Upper 90%CL limits on µ s are calculated and listed for each signalhypothesis in Table I.The upper limit on µ s can be translated into a limit onthe signal flux and annihilation rate in the Sun. The ef-fect of different sources of systematic uncertainties on sig-nal flux expectations is calculated for three signal energyregions, defined in Table II by corresponding benchmarkWIMP masses. Sources of uncertainties are divided intotwo classes; measurement and parameterization errors oncross sections and neutrino properties on the one handand limitations in the detector simulation and uncertain-ties in detector calibrations on the other hand. The firstclass, Class-I, affects signal normalizations only, whereasthe latter (Class-II) alters signal acceptance and intro-duces changes in the point spread function that is the ba-sis for the likelihood analysis. Class-II uncertainties areevaluated using alternative signal simulations with variedcalibration parameters, processed through the same anal-ysis chain, and evaluated with the full multi-dataset com-bined likelihood. This procedure explicitly determinesthe systematic effect on µ s .Uncertainties in neutrino-nucleon cross-sections forsignal simulations arise in the parameterization of theCTEQ6-DIS parton distribution functions as used in nusigma [22]. In addition to this theoretical uncertaintyon σ ν , the energy dependent error on the experimen-tal σ ν -measurement [23] is included. The uncertainty TABLE I. Results from the combination of the three independent datasets. Upper 90% limits on the number of signal events µ , the WIMP annihilation rate in the Sun Γ A , the muon flux Φ µ and neutrino flux Φ ν , and the WIMP-proton scatteringcross-sections (spin-independent, σ SI,p , and spin-dependent, σ SD,p ), at the 90% confidence level including systematic errors.The sensitivity Φ µ (see text) is shown for comparison. m χ Channel µ Γ A Φ µ Φ µ Φ ν σ SI,p σ SD,p (GeV/c ) ( s − ) (km − y − ) (km − y − ) (km − y − ) (cm ) (cm )20 τ + τ −
162 2 . × . × . × . × . × − . × − τ + τ − . . × . × . × . × . × − . × −
35 b¯b 128 1 . × . × . × . × . × − . × − τ + τ − . . × . × . × . × . × − . × −
50 b¯b 55 . . × . × . × . × . × − . × −
100 W + W − . . × . × . × . × . × − . × −
100 b¯b 28 . . × . × . × . × . × − . × −
250 W + W − . . × . × . × . × . × − . × −
250 b¯b 19 . . × . × . × . × . × − . × −
500 W + W − . . × . × . × . × . × − . × −
500 b¯b 30 . . × . × . × . × . × − . × − + W − . . × . × . × . × . × − . × − . . × . × . × . × . × − . × − + W − . . × . × . × . × . × − . × − . . × . × . × . × . × − . × − + W − . . × . × . × . × . × − . × − . a . × . × . × . × . × − . × − Value has been corrected with respect to typo in published version of the paper. in neutrino oscillation parameters used in signal flux cal-culations is investigated through variations of mixing pa-rameters within the quoted 1 σ regions [23]. Here, thedominant effect results from the least constrained mix-ing angle, θ , maximizing tau (dis)appearance withinthe expected flux expectation.The second class of uncertainties includes absolutecalibration and DOM to DOM variation of sensitivity,optical properties of the glacial ice, and photon prop-agation to the detector. The systematic uncertaintieson absolute DOM sensitivity are evaluated with sets ofsignal simulations with an overall shift of 10% in DOMefficiency. As baseline simulations do not account forvarying relative DOM efficiency, dedicated signal simu-lations are performed with individual DOM efficienciesfrom a Gaussian fitted to the in-situ measured spread( σ = 0 . µ s for each signal hypothesis arethen converted to limits on the neutrino to muon con- version rate and, through DarkSUSY [9], to limits onthe WIMP annihilation rate in the Sun, Γ A . For bet-ter comparison to other experiments limits on the neu-trino flux (Φ ν ) from the Sun, and the corresponding in-duced muon flux in the ice (Φ µ ), both integrated above1 GeV, are computed at the 90% confidence level. Theselimits are listed in Table I. Also specified is the me-dian sensitivity, ¯Φ µ , derived from simulations withoutsignal. Under the assumption of equilibrium betweenWIMP capture and annihilation in the Sun, limits on Γ A are converted into limits on the spin-dependent, σ SD , p ,and spin-independent, σ SI , p , WIMP-proton scatteringcross-sections, using the method from Ref [39].Resultsare listed in Table I and shown in Fig. 2 together withother experimental limits [28–37]. We assume a stan-dard DM halo with a local density of 0 . [23]and a Maxwellian WIMP velocity distribution with anRMS velocity of 270 km/s. We do not include the de-tailed effects of diffusion and planets upon the capturerate, as the simple free-space approximation [2] includedin DarkSUSY is found to be accurate [40]. Limits on theWIMP-nucleon scattering cross section can also be de-duced from limits on mono-jet and mono-photon signalsat hadron colliders, but these depend strongly on thechoice of the underlying effective theory and mediatormasses [41–43], and consequently not included in Fig. 2.In conclusion, we have presented the most stringentlimits to date on the spin-dependent WIMP-proton cross-section for WIMPs annihilating into W + W − or τ + τ − ) -2 / GeV c χ log10 ( m ) / c m S I, p σ l og10 ( -46-45-44-43-42-41-40-39-38 MSSM incl. XENON (2012) ATLAS + CMS (2012)DAMA no channeling (2008)CDMS (2010)CDMS 2keV reanalyzed (2011)CoGENT (2010)XENON100 (2012))bIceCube 2012 (b ♦ ) - W + IceCube 2012 (W ) = 80.4GeV/c W 35 35 -100 > ν oscillations 6 6 6 ν -nucleon cross-section 7 5.5 3.5 µ -propagation in ice < < < ∗ ∗ 15 10 5Absolute DOM efficiency ∗ 50 20 15Total uncertainty 54 25 21 lowing agencies: U.S. National Science Foundation-Officeof Polar Programs, U.S. National Science Foundation-Physics Division, University of Wisconsin Alumni Re-search Foundation, the Grid Laboratory Of Wisconsin(GLOW) grid infrastructure at the University of Wis-consin - Madison, the Open Science Grid (OSG) gridinfrastructure; U.S. Department of Energy, and Na-tional Energy Research Scientific Computing Center, theLouisiana Optical Network Initiative (LONI) grid com-puting resources; National Science and Engineering Re-search Council of Canada; Swedish Research Council,Swedish Polar Research Secretariat, Swedish National In-frastructure for Computing (SNIC), and Knut and AliceWallenberg Foundation, Sweden; German Ministry forEducation and Research (BMBF), Deutsche Forschungs-gemeinschaft (DFG), Helmholtz Alliance for Astropar-ticle Physics (HAP), Research Department of Plasmaswith Complex Interactions (Bochum), Germany; Fundfor Scientific Research (FNRS-FWO), FWO Odysseusprogramme, Flanders Institute to encourage scientificand technological research in industry (IWT), BelgianFederal Science Policy Office (Belspo); University of Ox-ford, United Kingdom; Marsden Fund, New Zealand;Australian Research Council; Japan Society for Promo-tion of Science (JSPS); the Swiss National Science Foun-dation (SNSF), Switzerland. ∗ Physics Department, South Dakota School of Mines andTechnology, Rapid City, SD 57701, USA † Los Alamos National Laboratory, Los Alamos, NM87545, USA ‡ also Sezione INFN, Dipartimento di Fisica, I-70126, Bari,Italy § NASA Goddard Space Flight Center, Greenbelt, MD20771, USA[1] G. 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