Neural Analogical Matching

Analogy is core to human cognition. It allows us to solve problems based on prior experience, it governs the way we conceptualize new information, and it even influences our visual perception. The importance of analogy to humans has made it an active area of research in the broader field of artificial intelligence, resulting in data-efficient models that learn and reason in human-like ways. While cognitive perspectives of analogy and deep learning have generally been studied independently of one another, the integration of the two lines of research is a promising step towards more robust and efficient learning techniques. As part of a growing body of research on such an integration, we introduce the Analogical Matching Network: a neural architecture that learns to produce analogies between structured, symbolic representations that are largely consistent with the principles of Structure-Mapping Theory.Comment: AAAI versio

TXS 0506+056 with Updated IceCube Data

Past results from the IceCube Collaboration have suggested that the blazar TXS 0506+056 is a potential source of astrophysical neutrinos. However, in the years since there have been numerous updates to event processing and reconstruction, as well as improvements to the statistical methods used to search for astrophysical neutrino sources. These improvements in combination with additional years of data have resulted in the identification of NGC 1068 as a second neutrino source candidate. This talk will re-examine time-dependent neutrino emission from TXS 0506+056 using the most recent northern-sky data sample that was used in the analysis of NGC 1068. The results of using this updated data sample to obtain a significance and flux fit for the 2014 TXS 0506+056 "untriggered" neutrino flare are reported

Galactic Core-Collapse Supernovae at IceCube: “Fire Drill” Data Challenges and follow-up

The next Galactic core-collapse supernova (CCSN) presents a once-in-a-lifetime opportunity to make astrophysical measurements using neutrinos, gravitational waves, and electromagnetic radiation. CCSNe local to the Milky Way are extremely rare, so it is paramount that detectors are prepared to observe the signal when it arrives. The IceCube Neutrino Observatory, a gigaton water Cherenkov detector below the South Pole, is sensitive to the burst of neutrinos released by a Galactic CCSN at a level >10σ. This burst of neutrinos precedes optical emission by hours to days, enabling neutrinos to serve as an early warning for follow-up observation. IceCube\u27s detection capabilities make it a cornerstone of the global network of neutrino detectors monitoring for Galactic CCSNe, the SuperNova Early Warning System (SNEWS 2.0). In this contribution, we describe IceCube\u27s sensitivity to Galactic CCSNe and strategies for operational readiness, including "fire drill" data challenges. We also discuss coordination with SNEWS 2.0

All-Energy Search for Solar Atmospheric Neutrinos with IceCube

The interaction of cosmic rays with the solar atmosphere generates a secondary flux of mesons that decay into photons and neutrinos – the so-called solar atmospheric flux. Although the gamma-ray component of this flux has been observed in Fermi-LAT and HAWC Observatory data, the neutrino component remains undetected. The energy distribution of those neutrinos follows a soft spectrum that extends from the GeV to the multi-TeV range, making large Cherenkov neutrino telescopes a suitable for probing this flux. In this contribution, we will discuss current progress of a search for the solar neutrino flux by the IceCube Neutrino Observatory using all available data since 2011. Compared to the previous analysis which considered only high-energy muon neutrino tracks, we will additionally consider events produced by all flavors of neutrinos down to GeV-scale energies. These new events should improve our analysis sensitivity since the flux falls quickly with energy. Determining the magnitude of the neutrino flux is essential, since it is an irreducible background to indirect solar dark matter searches

Multiplicity of TeV muons in extensive air showers detected with IceTop and IceCube

We report on an analysis of the high-energy muon component in near-vertical extensive air showers detected by the surface array IceTop in coincidence with the in-ice array of the IceCube Neutrino Observatory. In the coincidence measurement, the predominantly electromagnetic signal measured by IceTop is used to estimate the cosmic-ray primary energy, and the energy loss of the muon bundle in the deep in-ice array is used to estimate the number of muons in the shower with energies above 500 GeV (“TeV muons”). The average multiplicity of these TeV muons is determined for cosmic-ray energies between 2.5 PeV and 100 PeV assuming three different hadronic interaction models: Sibyll 2.1, QGSJet-II.04, and EPOS-LHC. For all models considered, the results are found to be in good agreement with the expectations from simulations. A tension exists, however, between the high-energy muon multiplicity and other observables; most importantly the density of GeV muons measured by IceTop using QGSJet-II.04 and EPOS-LHC

Searching for IceCube sub-TeV neutrino counterparts to sub-threshold Gravitational Wave events

Since the release of the Gravitational Wave Transient Catalogue GWTC-2.1 by the LIGO-Virgo collaboration, sub-threshold gravitational wave (GW) candidates are publicly available. They are expected to be released in real-time as well, in the upcoming O4 run. Using these GW candidates for multi-messenger studies complement the ongoing efforts to identify neutrino counterparts to GW events. This in turn, allows us to schedule electromagnetic follow-up searches more efficiently. However, the definition and criteria for sub-threshold candidates are pretty flexible. Finding a multi-messenger counterpart via archival studies for these candidates will help to set up strong bounds on the GW parameters which are useful for defining a GW signal as sub-threshold, thereby increasing their significance for scheduling follow-up searches. Here, we present the current status of this ongoing work with the IceCube Neutrino Observatory. We perform a selection of the sub-threshold GW candidates from GWTC-2.1 and conduct an archival search for sub-TeV neutrino counterparts detected by the dense infill array of the IceCube Neutrino Observatory, known as "DeepCore". For this, an Unbinned Maximum Likelihood (UML) method is used. We report the 90% C.L. sensitivities of this sub-TeV neutrino dataset for each selected sub-threshold GW candidate, considering the spatial and temporal correlation between the GW and neutrino events within a 1000 s time window