Tau Neutrino Appearance with 8 Years of IceCube Neutrino Data Étienne Bourbeau, for the IceCube Collaboration Niels Bohr Institute etienne.bourbeau@icecube.wisc.edu References [1] S. Parke, M. Ross-Lonergan. Phys. Rev. D, 93, 113009 (2016) [arXiv:1508.05095] [2] Aartsen et al (IceCube Collaboration). JINST 12 P03012 (2017) [arXiv: 1612.05093] [3] Aartsen et al (IceCube Collaboration). Phys. Rev. D, 99 032007 (2019) [4] A. Fedynitch. Matrix Cascade Equation. https://github.com/afedynitch/MCEq [5] G.D. Barr et al. Phy. Rev. D, 74, 094009 (2006) [arXiv: astro-ph/0611266] The IceCube and DeepCore Detectors Neutrino Oscillations in IceCube Unitarity • Significance based on likelihood Test Statistic : 𝑈!" 𝑈!# 𝑈!$ 𝑈%" 𝑈%# 𝑈%$ 𝑈&" 𝑈&# 𝑈&$ + + ² ² ² = 1 + + ² ² = 1 Analysis Principle Digital Optical Module (DOM) • 30 cm photomultiplier tube + digitizer encapsulated in a pressure vessel • Designed to detect Cherenkov radiation from particle interactions in the ice • Elementary unit of the detector 0 m 1450 m 2450 m IceCube Neutrino Observatory [2] • Deployed to detect neutrinos of astrophysical origin • Consists of 86 strings of sensors buried underneath the South Pole The DeepCore Sub-Array • 8 strings of high quantum efficiency DOMs • 10 Mton fiducial volume • ~ 500 sensors in closer spacing • Rest of IceCube is used as a veto region Systematics Uncertainties: Analysis treats uncertainties as nuisance parameters in the fit: • Neutrinos and muon spectral index • Atmospheric Neutrino Flux ([4], [5]) • Quasielastic and resonant form factor • Deep Inelastic scattering cross section • Earth Model (neutrino propagation) • Dom Efficiency • Refrozen ice parametrisation • Bulk Ice absorption & scattering Reconstruction of neutrino events • Charge and time of hits from all DOMs are fed into a likelihood-based event reconstruction algorithm • 𝝊𝝁,𝑪𝑪interactions have mostly track- like profiles, while 𝝊𝒆,𝑪𝑪, 𝝊𝝉,𝑪𝑪and all 𝝊𝑵𝑪interactions produce point-like (ie cascade) profiles • Neutrino oscillations constitute the only experimental evidence of non- conformity to the Standard Model (potential evidence for new physics) • It describes transitions between flavor states to mass states Sensitivity Projections Event Selection Production (as 𝝊𝝁‘s) Propagation (as superpositions of 𝝊𝟏‘s, 𝝊𝟐 ) 𝐬and 𝝊𝟑’s) Detection (as 𝝊𝒆‘s, 𝝊𝝁) 𝐬and 𝝊𝝉’s) • PMNS unitarity constraints are weakest for the third generation of neutrinos, an area where IceCube is highly sensitive [3] • Non-unitarity could indicate that the 3x3 PMNS matrix is a subset of a larger N x N mixing matrix • IceCube operates in energy ranges were 𝝂𝝉,𝑪𝑪cross- section is much less kinematically suppressed than in accelerator experiments • We count the number of neutrinos detected per particle ID (ie flavor), energy and zenith bins • We then compare the result to our expectations from standard oscillation • Tau neutrino fraction is fit as a statistical excess of events in non-track events (ie we don’t identify individual tau neutrino events) Cascade-Like Events Mixed Events Track-Like Events Neutrinos from cosmic-ray interactions in the atmosphere are reconstructed with associated energy and direction (proxy for distance travelled). They allow IceCube to cover a wide range of oscillation baselines (~10 to 10000 km, and 5 to 300 GeV) • We perform a multi-dimensional fit of a Monte-Carlo template to our data. The fit includes both physical (𝜟𝒎𝟑𝟐 𝟐, 𝜽𝟐𝟑, tau normalization 𝑵𝝉) and nuisance parameters to handle systematics. • Ratio of a scenario with 𝑵𝝉= 0.5 w.r.t standard oscillation paradigm −2 𝐿𝐿𝐻+,-./01. 𝐿𝐿𝐻2!34 The Sample in Numbers • Consists of eight years of detector data (mid-2011 to mid-2019) • Several cuts applied to eliminate atmospheric muons and self-triggered noise events (our main backgrounds) • Use of new machine-learning classifiers (boosted decision trees) to perform final- level muon rejection + PID classification • Yields a large statistics sample of neutrinos that well suited for 𝝊𝝁disapp