4 research outputs found
Event reconstruction for KM3NeT/ORCA using convolutional neural networks
The authors acknowledge the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris Ile-de-France Region, France; Shota Rustaveli National Science Foundation of Georgia (SRNSFG, FR-18-1268), Georgia; Deutsche Forschungsgemeinschaft (DFG), Germany; The General Secretariat of Research and Technology (GSRT), Greece; Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell'Universita e della Ricerca (MUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education, Scientific Research and Professional Training, Morocco; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; The National Science Centre, Poland (2015/18/E/ST2/00758); National Authority for Scientific Research (ANCS), Romania; Ministerio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento (refs. PGC2018-096663-B-C41, -A-C42, -B-C43, -B-C44) (MCIU/FEDER), Severo Ochoa Centre of Excellence and MultiDark Consolider (MCIU), Junta de Andalucia (ref. SOMM17/6104/UGR), Generalitat Valenciana: Grisolia (ref. GRISOLIA/2018/119) and GenT (ref. CIDEGENT/2018/034) programs, La Caixa Foundation (ref. LCF/BQ/IN17/11620019), EU: MSC program (ref. 713673), Spain.The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.French National Research Agency (ANR)
ANR-15-CE31-0020Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund)European Union (EU)Institut Universitaire de France (IUF)LabEx UnivEarthS
ANR-10-LABX-0023
ANR-18-IDEX-0001Shota Rustaveli National Science Foundation of Georgia
FR-18-1268German Research Foundation (DFG)Greek Ministry of Development-GSRTIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Universities and Research (MIUR)
Research Projects of National Relevance (PRIN)Ministry of Higher Education, Scientific Research and Professional Training, MoroccoNetherlands Organization for Scientific Research (NWO)National Science Centre, Poland
2015/18/E/ST2/00758National Authority for Scientific Research (ANCS), RomaniaMinisterio de Ciencia, Innovacion, Investigacion y Universidades
PGC2018-096663-B-C41
A-C42
B-C43
B-C44Severo Ochoa Centre of ExcellenceJunta de Andalucia
SOMM17/6104/UGRGeneralitat Valenciana: Grisolia
GRISOLIA/2018/119
CIDEGENT/2018/034La Caixa Foundation
LCF/BQ/IN17/11620019EU: MSC program
71367
Ultrahigh energy neutrinos at the Pierre Auger observatory
The observation of ultrahigh energy neutrinos (UHEνs) has become a priority in experimental astroparticle physics. UHEνs can be detected with a variety of techniques. In particular, neutrinos can interact in the atmosphere (downward-going ν) or in the Earth crust (Earth-skimming ν), producing air showers that can be observed with arrays of detectors at the ground. With the surface detector array of the Pierre Auger Observatory we can detect these types of cascades. The distinguishing signature for neutrino events is the presence of very inclined showers produced close to the ground (i.e., after having traversed a large amount of atmosphere). In this work we review the procedure and criteria established to search for UHEνs in the data collected with the ground array of the Pierre Auger Observatory. This includes Earth-skimming as well as downward-going neutrinos. No neutrino candidates have been found, which allows us to place competitive limits to the diffuse flux of UHEνs in the EeV range and above.P. Abreu ... K. B. Barber ... J. A. Bellido ... R. W. Clay ... M. J. Cooper ... B. R. Dawson ... T. A. Harrison ... A. E. Herve ... V. C. Holmes ... J. Sorokin ... P. Wahrlich ... B. J. Whelan ... et al
Search for photons with energies above 1018eV using the hybrid detector of the Pierre Auger Observatory
A search for ultra-high energy photons with energies above 1EeV is performed
using nine years of data collected by the Pierre Auger Observatory in hybrid operation mode.
An unprecedented separation power between photon and hadron primaries is achieved by
combining measurements of the longitudinal air-shower development with the particle content
at ground measured by the fluorescence and surface detectors, respectively. Only three photon
candidates at energies 1\u20132EeV are found, which is compatible with the expected hadron induced
background. Upper limits on the integral flux of ultra-high energy photons of 0.027,
0.009, 0.008, 0.008 and 0.007 km 122 sr 121 yr 121 are derived at 95% C.L. for energy thresholds of
1, 2, 3, 5 and 10EeV. These limits bound the fractions of photons in the all-particle integral
flux below 0.1%, 0.15%, 0.33%, 0.85% and 2.7%. For the first time the photon fraction at EeV
energies is constrained at the sub-percent level. The improved limits are below the flux of
diffuse photons predicted by some astrophysical scenarios for cosmogenic photon production.
The new results rule-out the early top-down models 12 in which ultra-high energy cosmic rays
are produced by, e.g., the decay of super-massive particles 12 and challenge the most recent
super-heavy dark matter model
Search for ultrarelativistic magnetic monopoles with the Pierre Auger Observatory
We present a search for ultrarelativistic magnetic monopoles with the Pierre Auger observatory. Such
particles, possibly a relic of phase transitions in the early Universe, would deposit a large amount of energy
along their path through the atmosphere, comparable to that of ultrahigh-energy cosmic rays (UHECRs).
The air-shower profile of a magnetic monopole can be effectively distinguished by the fluorescence
detector from that of standard UHECRs. No candidate was found in the data collected between 2004 and
2012, with an expected background of less than 0.1 event from UHECRs. The corresponding
90% confidence level (C.L.) upper limits on the flux of ultrarelativistic magnetic monopoles range from
10^ 1219(cm2 sr s)^ 121 for a Lorentz factor \u3b3 = 10^9 to 2.5
7 10 1221(cm2 sr s)^ 121 for \u3b3 = 10^12. These results\u2014the
first obtained with a UHECR detector\u2014improve previously published limits by up to an order of
magnitude