Multi-time-over-threshold technique for photomultiplier signal processing: Description and characterization of the SCOTT ASIC

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Detection potential of the KM3NeT detector for high-energy neutrinos from the Fermi bubbles

A recent analysis of the Fermi Large Area Telescope data provided evidence for a high-intensity emission of high-energy gamma rays with a E 2 spectrum from two large areas, spanning 50 above and below the Galactic centre (the ‘‘Fermi bubbles’’). A hadronic mechanism was proposed for this gamma-ray emission making the Fermi bubbles promising source candidates of high-energy neutrino emission. In this work Monte Carlo simulations regarding the detectability of high-energy neutrinos from the Fermi bubbles with the future multi-km3 neutrino telescope KM3NeT in the Mediterranean Sea are presented. Under the hypothesis that the gamma-ray emission is completely due to hadronic processes, the results indicate that neutrinos from the bubbles could be discovered in about one year of operation, for a neutrino spectrum with a cutoff at 100 TeV and a detector with about 6 km3 of instrumented volume. The effect of a possible lower cutoff is also considered.Published7–141.8. Osservazioni di geofisica ambientaleJCR Journalrestricte

Expansion cone for the 3-inch PMTs of the KM3NeT optical modules

[EN] Detection of high-energy neutrinos from distant astrophysical sources will open a new window on the Universe. The detection principle exploits the measurement of Cherenkov light emitted by charged particles resulting from neutrino interactions in the matter containing the telescope. A novel multi-PMT digital optical module (DOM) was developed to contain 31 3-inch photomultiplier tubes (PMTs). In order to maximize the detector sensitivity, each PMT will be surrounded by an expansion cone which collects photons that would otherwise miss the photocathode. Results for various angles of incidence with respect to the PMT surface indicate an increase in collection efficiency by 30% on average for angles up to 45 degrees with respect to the perpendicular. Ray-tracing calculations could reproduce the measurements, allowing to estimate an increase in the overall photocathode sensitivity, integrated over all angles of incidence, by 27% (for a single PMT). Prototype DOMs, being built by the KM3NeT consortium, will be equipped with these expansion cones.This work is supported through the EU, FP6 Contract no. 011937, FP7 grant agreement no. 212252, and the Dutch Ministry of Education, Culture and Science.Adrián Martínez, S.; Ageron, M.; Aguilar, JA.; Aharonian, F.; Aiello, S.; Albert, A.; Alexandri, M.... (2013). Expansion cone for the 3-inch PMTs of the KM3NeT optical modules. Journal of Instrumentation. 8(3):1-19. https://doi.org/10.1088/1748-0221/8/03/T03006S1198

An optical sensor for the alignment of the Atlas Muon Spectrometer

Optical sensor for the alignment of the Atlas muon spectrometer was discussed. This system uses praxial sensor for tha alignment. In this spectrometer the alignment system controls spatial position of the muon chambers with an accuracy of 30 mum and 200 murad for a range of plus or minus 5 mm and plus or minus 10 mrad. (Edited abstract) 3 Refs

Enhancing geophysical flow machine learning performance via scale separation

International audienceRecent advances in statistical and machine learning have opened the possibility of forecasting the behaviour of chaotic systems using recurrent neural networks. In this article we investigate the applicability of such a framework to geophysical flows, known to involve multiple scales in length, time and energy and to feature intermittency. We show that both multiscale dynamics and intermittency introduce severe limitations to the applicability of recurrent neural networks, both for short-term forecasts as well as for the reconstruction of the underlying attractor. We suggest that possible strategies to overcome such limitations should be based on separating the smooth large-scale dynamics from the intermittent/small-scale features. We test these ideas on global sea-level pressure data for the past 40 years, a proxy of the atmospheric circulation dynamics. Better short-and longterm forecasts of sea-level pressure data can be obtained with an optimal choice of spatial coarse graining and time filtering