Ultra-high neutrino fluxes as a probe for non-standard physics

We examine how light neutrinos coming from distant active galactic nuclei (AGN) and similar high energy sources may be used as tools to probe non-standard physics. In particular we discuss how studying the energy spectra of each neutrino flavour coming from such distant sources and their distortion relative to each other may serve as pointers to exotic physics such as neutrino decay, Lorentz symmetry violation, pseudo-Dirac effects, CP and CPT violation and quantum decoherence. This allows us to probe hitherto unexplored ranges of parameters for the above cases, for example lifetimes in the range $10^{-3}-10^{4}$ s/eV for the case of neutrino decay. We show that standard neutrino oscillations ensure that the different flavours arrive at the earth with similar shapes even if their flavour spectra at source may differ strongly in both shape and magnitude. As a result, observed differences between the spectra of various flavours at the detector would be signatures of non-standard physics altering neutrino fluxes during propagation rather than those arising during their production at source. Since detection of ultra-high energy (UHE) neutrinos is perhaps imminent, it is possible that such differences in spectral shapes will be tested in neutrino detectors in the near future. To that end, using the IceCube detector as an example, we show how our results translate to observable shower and muon-track event rates.Comment: 16 pages, 10 figure

Sensitivity of the IceCube Detector to Astrophysical Sources of High Energy Muon Neutrinos

We present the results of a Monte-Carlo study of the sensitivity of the planned IceCube detector to predicted fluxes of muon neutrinos at TeV to PeV energies. A complete simulation of the detector and data analysis is used to study the detector's capability to search for muon neutrinos from sources such as active galaxies and gamma-ray bursts. We study the effective area and the angular resolution of the detector as a function of muon energy and angle of incidence. We present detailed calculations of the sensitivity of the detector to both diffuse and pointlike neutrino emissions, including an assessment of the sensitivity to neutrinos detected in coincidence with gamma-ray burst observations. After three years of datataking, IceCube will have been able to detect a point source flux of E^2*dN/dE = 7*10^-9 cm^-2s^-1GeV at a 5-sigma significance, or, in the absence of a signal, place a 90% c.l. limit at a level E^2*dN/dE = 2*10^-9 cm^-2s^-1GeV. A diffuse E-2 flux would be detectable at a minimum strength of E^2*dN/dE = 1*10^-8 cm^-2s^-1sr^-1GeV. A gamma-ray burst model following the formulation of Waxman and Bahcall would result in a 5-sigma effect after the observation of 200 bursts in coincidence with satellite observations of the gamma-rays.Comment: 33 pages, 13 figures, 6 table

Energy and Flux Measurements of Ultra-High Energy Cosmic Rays Observed During the First ANITA Flight

The first flight of the Antarctic Impulsive Transient Antenna (ANITA) experiment recorded 16 radio signals that were emitted by cosmic-ray induced air showers. For 14 of these events, this radiation was reflected from the ice. The dominant contribution to the radiation from the deflection of positrons and electrons in the geomagnetic field, which is beamed in the direction of motion of the air shower. This radiation is reflected from the ice and subsequently detected by the ANITA experiment at a flight altitude of 36km. In this paper, we estimate the energy of the 14 individual events and find that the mean energy of the cosmic-ray sample is 2.9 EeV. By simulating the ANITA flight, we calculate its exposure for ultra-high energy cosmic rays. We estimate for the first time the cosmic-ray flux derived only from radio observations. In addition, we find that the Monte Carlo simulation of the ANITA data set is in agreement with the total number of observed events and with the properties of those events.Comment: Added more explanation of the experimental setup and textual improvement

On the selection of AGN neutrino source candidates for a source stacking analysis with neutrino telescopes

The sensitivity of a search for sources of TeV neutrinos can be improved by grouping potential sources together into generic classes in a procedure that is known as source stacking. In this paper, we define catalogs of Active Galactic Nuclei (AGN) and use them to perform a source stacking analysis. The grouping of AGN into classes is done in two steps: first, AGN classes are defined, then, sources to be stacked are selected assuming that a potential neutrino flux is linearly correlated with the photon luminosity in a certain energy band (radio, IR, optical, keV, GeV, TeV). Lacking any secure detailed knowledge on neutrino production in AGN, this correlation is motivated by hadronic AGN models, as briefly reviewed in this paper. The source stacking search for neutrinos from generic AGN classes is illustrated using the data collected by the AMANDA-II high energy neutrino detector during the year 2000. No significant excess for any of the suggested groups was found.Comment: 43 pages, 12 figures, accepted by Astroparticle Physic

Detecting a stochastic gravitational wave background with the Laser Interferometer Space Antenna

The random superposition of many weak sources will produce a stochastic background of gravitational waves that may dominate the response of the LISA (Laser Interferometer Space Antenna) gravitational wave observatory. Unless something can be done to distinguish between a stochastic background and detector noise, the two will combine to form an effective noise floor for the detector. Two methods have been proposed to solve this problem. The first is to cross-correlate the output of two independent interferometers. The second is an ingenious scheme for monitoring the instrument noise by operating LISA as a Sagnac interferometer. Here we derive the optimal orbital alignment for cross-correlating a pair of LISA detectors, and provide the first analytic derivation of the Sagnac sensitivity curve.Comment: 9 pages, 11 figures. Significant changes to the noise estimate

IceCube - the next generation neutrino telescope at the South Pole

IceCube is a large neutrino telescope of the next generation to be constructed in the Antarctic Ice Sheet near the South Pole. We present the conceptual design and the sensitivity of the IceCube detector to predicted fluxes of neutrinos, both atmospheric and extra-terrestrial. A complete simulation of the detector design has been used to study the detector's capability to search for neutrinos from sources such as active galaxies, and gamma-ray bursts.Comment: 8 pages, to be published with the proceedings of the XXth International Conference on Neutrino Physics and Astrophysics, Munich 200

Revealing uncertainty in the status of biodiversity change

Biodiversity faces unprecedented threats from rapid global change1. Signals of biodiversity change come from time-series abundance datasets for thousands of species over large geographic and temporal scales. Analyses of these biodiversity datasets have pointed to varied trends in abundance, including increases and decreases. However, these analyses have not fully accounted for spatial, temporal and phylogenetic structures in the data. Here, using a new statistical framework, we show across ten high-profile biodiversity datasets2,3,4,5,6,7,8,9,10,11 that increases and decreases under existing approaches vanish once spatial, temporal and phylogenetic structures are accounted for. This is a consequence of existing approaches severely underestimating trend uncertainty and sometimes misestimating the trend direction. Under our revised average abundance trends that appropriately recognize uncertainty, we failed to observe a single increasing or decreasing trend at 95% credible intervals in our ten datasets. This emphasizes how little is known about biodiversity change across vast spatial and taxonomic scales. Despite this uncertainty at vast scales, we reveal improved local-scale prediction accuracy by accounting for spatial, temporal and phylogenetic structures. Improved prediction offers hope of estimating biodiversity change at policy-relevant scales, guiding adaptive conservation responses

Investigating signal properties of UHE particles using in-ice radar for the RET experiment

The Radar Echo Telescope (RET) experiment plans to use the radar technique to detect Ultra-High Energy (UHE) cosmic rays and neutrinos in the polar ice sheets. Whenever an UHE particle collides with an ice molecule, it produces a shower of relativistic particles, which leaves behind an ionization trail. Radio waves can be reflected off this trail and be detected in antennas. It is critical to understand such a radar signal's key properties as that will allow us to do vertex, angular and energy reconstruction of the primary UHE particle. We will discuss various simulation methods, which will fundamentally rely on ray tracing, to recreate the radar signal and test our reconstruction methods

The Antarctic Impulsive Transient Antenna Ultra-high Energy Neutrino Detector Design, Performance, and Sensitivity for 2006-2007 Balloon Flight

We present a detailed report on the experimental details of the Antarctic Impulsive Transient Antenna (ANITA) long duration balloon payload, including the design philosophy and realization, physics simulations, performance of the instrument during its first Antarctic flight completed in January of 2007, and expectations for the limiting neutrino detection sensitivity. Neutrino physics results will be reported separately.Comment: 50 pages, 49 figures, in preparation for PR

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.Peer Reviewe