Neutrino vertex reconstruction with in-ice radio detectors using surface reflections and implications for the neutrino energy resolution

Anker, A.; Barwick, S. W.; Bernhoff, Hans; Besson, D.; Bingefors, N.; García-Fernández, Daniel; Gaswint, Geoffrey; Gläser, Christian; Hallgren, A.; Hanson, Jordan C.; Klein, S. R.; Kleinfelder, S.; Lahmann, R.; Latif, Uzair Abdul; Nam, J. W.; Novikov, Alexander; Nelles, A.; Paul, M. P.; Persichilli, Christopher; Plaisier, Ilse; Prakash, T.; Shively, Savannah; Tatar, J.; Unger, E.; Wang, S. H.; Welling, Christoph; Zierke, S.

doi:10.1088/1475-7516/2019/11/030

Cited by 43 publications

(94 citation statements)

References 30 publications

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“…5 (bottom) where the uncertainty of the reconstructed shower energy determines how each bin should be smeared to account for experimental uncertainties and translate the plot from true shower energy to measured shower energy. We also note that for neutrinos, the shower energy is relatively close to the neutrino energy [62], which allows for a quick first-order estimation of the background as the function of neutrino energy and energy resolution.…”

Section: Consequences For Neutrino Detectionmentioning

confidence: 84%

Signatures of secondary leptons in radio-neutrino detectors in ice

2020

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The detection of the radio emission following a neutrino interaction in ice is a promising technique to obtain significant sensitivities to neutrinos with energies above Petaelectronvolts (10 15 eV). The detectable radio emission stems from particle showers in the ice. So far, detector simulations have considered only the radio emission from the primary interaction of the neutrino. For this study, existing simulation tools have been extended to cover secondary interactions from muons and taus. We find that secondary interactions of both leptons add up to 25% to the effective volume of neutrino detectors. Also, muon and tau neutrinos can create several detectable showers, with the result that double signatures do not constitute an exclusive signature for tau neutrinos. We also find that the background of atmospheric muons from cosmic rays is non-negligible for in-ice arrays and that an air shower veto should be considered helpful for radio detectors.

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Section: Consequences For Neutrino Detectionmentioning

confidence: 84%

Signatures of secondary leptons in radio-neutrino detectors in ice

2020

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“…This aids the reconstruction of the viewing angle by mapping out the Cherenkov cone. The time difference between these DnR pulses is also an estimator of the distance to the neutrino vertex and enables resolving the shower energy with an accuracy well below the intrinsic fluctuations from the unknown inelasticity of the interaction which amounts to a factor of two [24].…”

Section: Pos(icrc2021)1183mentioning

confidence: 99%

Sensitivity studies for the IceCube-Gen2 radio array

Hallmann¹,

Abbasi²,

Ackermann³

et al. 2021

Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)

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The IceCube Neutrino Observatory at the South Pole has measured the diffuse astrophysical neutrino flux up to ∼PeV energies and is starting to identify first point source candidates. The next generation facility, IceCube-Gen2, aims at extending the accessible energy range to EeV in order to measure the continuation of the astrophysical spectrum, to identify neutrino sources, and to search for a cosmogenic neutrino flux. As part of IceCube-Gen2, a radio array is foreseen that is sensitive to detect Askaryan emission of neutrinos beyond ∼30 PeV. Surface and deep antenna stations have different benefits in terms of effective area, resolution, and the capability to reject backgrounds from cosmic-ray air showers and may be combined to reach the best sensitivity. The optimal detector configuration is still to be identified. This contribution presents the full-array simulation efforts for a combination of deep and surface antennas, and compares different design options with respect to their sensitivity to fulfill the science goals of IceCube-Gen2.

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“…Therefore, we will train the deep neural network to determine the energy of the hadronic shower which has a deterministic relation to the observed signal. The amount of energy transferred from the neutrino into the hadronic shower is a stochastic process and can be estimated from theory [6]. The stochastic process also introduces a irreducible uncertainty on the conversion from hadronic shower energy back to the neutrino energy which amounts to a factor of two.…”

Section: Neutrino Energy Reconstructionmentioning

confidence: 99%

“…At this depth, the antenna will observe two signals, one from a direct path to the antenna, and another delayed signal from a reflection off the surface. The time difference between these two signals provides information about the distance to the neutrino interaction which is important to estimate the neutrino energy [6].…”

Section: Introductionmentioning

confidence: 99%

Deep learning reconstruction of the neutrino energy with a shallow Askaryan detector

Gläser¹,

McAleer²,

Baldi³

et al. 2021

Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)

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Cost effective in-ice radio detection of neutrinos above a few 10 16 eV has been explored successfully in pilot-arrays. A large radio detector is currently being constructed in Greenland with the potential to measure the first cosmogenic neutrino, and an order-of-magnitude more sensitive detector is being planned with IceCube-Gen2. We present the first end-to-end reconstruction of the neutrino energy from radio detector data. NuRadioMC was used to create a large data set of 40 million events of expected radio signals that are generated via the Askaryan effect following a neutrino interaction in the ice for a broad range of neutrino energies between 100 PeV and 10 EeV. We simulated the voltage traces that would be measured by the five antennas of a shallow detector station in the presence of noise. We designed and trained a deep neural network to determine the shower energy directly from the simulated experimental data and achieve a resolution better than a factor of two (STD < 0.3 in log10(E)) which is below the irreducible uncertainty from inelasticity fluctuations. We present the model architecture and study the dependence of the resolution on event parameters. This method will enable Askaryan detectors to measure the neutrino energy.

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Neutrino vertex reconstruction with in-ice radio detectors using surface reflections and implications for the neutrino energy resolution

Cited by 43 publications

References 30 publications

Signatures of secondary leptons in radio-neutrino detectors in ice

Signatures of secondary leptons in radio-neutrino detectors in ice

Sensitivity studies for the IceCube-Gen2 radio array

Deep learning reconstruction of the neutrino energy with a shallow Askaryan detector

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