Neutrinos are the ideal cosmic messengers, and can be used to explore the most powerful accelerators in the Universe, in particular the mechanisms for producing and accelerating cosmic rays to incredible energies. By studying clustering of neutrino candidate events in the IceCube detector we can discover sites of hadronic acceleration. We present results on searches for point-like sources of astrophysical neutrinos located in the Southern hemisphere, at energies between 100 GeV and a few TeV. The data were collected during the first year of the completed 86-string detector, corresponding to a detector livetime of 329 days. The event selection focuses on identifying events starting inside the instrumented volume, utilizing several advanced veto techniques, successfully reducing the large background of atmospheric muons. An unbinned maximum likelihood method is used to search for clustering of neutrino-like events. We perform a search in the full Southern hemisphere and a dedicated search using a catalog of 96 pre-defined known gamma-ray emitting sources seen in ground-based telescopes. No evidence of neutrino emission from point-like sources is found. The hottest spot is located at R.A. 305.2° and Dec. -8.5°, with a post-trial p-value of 88.1%. The most significant source in the a priori list is QSO 2022-077 with a post-trial p-value of 14.8%. In the absence of evidence for a signal, we calculate upper limits on the flux of muon-neutrinos for a range of spectra. For an unbroken E-2 neutrino spectrum, the observed limits are between 2.8 and 9.4×10-10 TeV cm-2 s-1, while for an E-2 neutrino spectrum with an exponential cut-off at 10 TeV, the observed limits are between 0.6 and 3.6×10-9 TeV cm-2 s-1. / IceCube

The search for the sources of astrophysical neutrinos is a central open question in particle astrophysics. Thanks to substantial experimental efforts, we now have large-scale neutrino detectors in the oceans and polar ice. The neutrino sky seems mostly isotropic, but hints of possible source-neutrino associations have started to emerge, leading to much excitement within the astrophysics community. As more data are collected and future experiments planned, the question of how to statistically quantify point source detection in a robust way becomes increasingly pertinent. The standard approach to null-hypothesis testing leads to reporting the results in terms of a p-value, with detection typically corresponding to surpassing the coveted 5-sigma threshold. While widely used, p-values and significance thresholds are notorious in the statistical community as challenging to interpret and potentially misleading. We explore an alternative Bayesian approach to reporting point source detection and the connections and differences with the frequentist view. In this thesis, two methods for associating neutrino events to candidate sources are implemented on data from a simplified simulation of high-energy neutrino generation and detection. One is a maximum likelihood-based method that has been used in some high-profile articles, and the alternative uses Bayesian Hierarchical modelling with Hamiltonian Monte Carlo to sample the joint posterior of key parameters. Both methods are applied to a set of test cases to gauge their differences and similarities when applied on identical data. The comparisons suggest the applicability of this Bayesian approach as alternative or complement to the frequentist, and illustrate how the two approaches differ. A discussion is also conducted on the applicability and validity of the study itself as well as some potential benefits of incorporating a Bayesian framework, with suggestions for additional aspects to analyze. / Sökandet efter källorna till astrofysiska neutriner är en central öppen fråga i astropartikel- fysik. Tack vare omfattande experimentella ansträngningar har vi nu storskaliga neutrino-detektorer i haven och polarisen. Neutrinohimlen verkar mestadels isotropisk, men antydningar till möjliga källneutrinoföreningar har börjat antydas, vilket har lett till mycket spänning inom astrofysikgemenskapen. När mer data samlas in och framtida experiment planeras, blir frågan om hur man statistiskt kvantifierar punktkälledetektering på ett robust sätt alltmer relevant. Standardmetoden för nollhypotes-testning leder ofta till rapportering av resultat i termer av p-värden, då en specifik tröskel i signifikans eftertraktas. Samtidigt som att vara starkt utbredda, är p-värden och signifikansgränser mycket omdiskuterade i det statistiska samfundet angående deras tolkning. Vi utforskar en alternativ Bayesisk inställning till utvärderingen av punktkälldetektering och jämför denna med den frekvensentistiska utgångspunkten. I denna uppsats tillämpas två metoder för att associera neutrinohändelser till kandidatkällor på basis av simulerad data. Den första använder en maximum likelihood-metod anpassad från vissa uppmärksammade rapporter, medan den andra använder Hamiltonsk Monte Carlo till att approximera den gemensamma aposteriorifördelningen hos modellens parametrar. Båda metoderna tillämpas på en uppsättning testfall för att uppskatta deras skillnader och likheter tillämpade på identisk data. Jämförelserna antyder tillämpligheten av den Bayesianska som alternativ eller komplement till den klassiska, och illustrerar hur de två metoderna skiljer sig åt. En diskussion förs också om validiteten av studien i sig samt några potentiella fördelar med att använda ett Bayesiskt ramverk, med förslag på ytterligare aspekter att analysera.

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