toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Salesa Greus, F.; Sanchez Losa, A. url  doi
openurl 
  Title Multimessenger Astronomy with Neutrinos Type Journal Article
  Year 2021 Publication Universe Abbreviated Journal Universe  
  Volume 7 Issue 11 Pages 397 - 11pp  
  Keywords multimessenger astronomy; astroparticle physics; neutrinos  
  Abstract Multimessenger astronomy is arguably the branch of the astroparticle physics field that has seen the most significant developments in recent years. In this manuscript, we will review the state-of-the-art, the recent observations, and the prospects and challenges for the near future. We will give special emphasis to the observation carried out with neutrino telescopes.  
  Address [Salesa Greus, Francisco; Sanchez Losa, Agustin] Univ Valencia, CSIC, IFIC Inst Fis Corpuscular, C Catedratico Jose Beltran 2, E-46980 Paterna, Spain, Email: sagreus@ific.uv.es;  
  Corporate Author Thesis  
  Publisher Mdpi Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000724957500001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5036  
Permanent link to this record
 

 
Author Hernandez-Rey, J.J.; Ardid, M.; Bou Cabo, M.; Calvo, D.; Diaz, A.F.; Gozzini, S.R.; Martinez-Mora, J.A.; Navas, S.; Real, D.; Salesa Greus, F.; Sanchez Losa, A.; Zornoza, J.D.; Zuñiga, J. doi  openurl
  Title Science with Neutrino Telescopes in Spain Type Journal Article
  Year 2022 Publication Universe Abbreviated Journal Universe  
  Volume 8 Issue 2 Pages 89 - 25pp  
  Keywords neutrino; neutrino telescopes; neutrino astrophysics; neutrino properties; sea science  
  Abstract The primary scientific goal of neutrino telescopes is the detection and study of cosmic neutrino signals. However, the range of physics topics that these instruments can tackle is exceedingly wide and diverse. Neutrinos coming from outside the Earth, in association with other messengers, can contribute to clarify the question of the mechanisms that power the astrophysical accelerators which are known to exist from the observation of high-energy cosmic and gamma rays. Cosmic neutrinos can also be used to bring relevant information about the nature of dark matter, to study the intrinsic properties of neutrinos and to look for physics beyond the Standard Model. Likewise, atmospheric neutrinos can be used to study an ample variety of particle physics issues, such as neutrino oscillation phenomena, the determination of the neutrino mass ordering, non-standard neutrino interactions, neutrino decays and a diversity of other physics topics. In this article, we review a selected number of these topics, chosen on the basis of their scientific relevance and the involvement in their study of the Spanish physics community working in the KM3NeT and ANTARES neutrino telescopes.  
  Address [Hernandez-Rey, Juan Jose; Calvo, David; Gozzini, Sara Rebecca; Real, Diego; Greus, Francisco Salesa; Losa, Agustin Sanchez; Zornoza, Juan de Dios; Zuniga, Juan] Univ Valencia, IFIC Inst Fis Corpuscular, C Catedratico Jose Beltran 2, Paterna 46980, Spain, Email: juan.j.hernandez@ific.uv.es;  
  Corporate Author Thesis  
  Publisher Mdpi Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000762321400001 Approved no  
  Is ISI yes International Collaboration no  
  Call Number IFIC @ pastor @ Serial 5145  
Permanent link to this record
 

 
Author Calefice, L.; Hennequin, A.; Henry, L.; Jashal, B.K.; Mendoza, D.; Oyanguren, A.; Sanderswood, I.; Sierra, C.V.; Zhuo, J.H. doi  openurl
  Title Effect of the high-level trigger for detecting long-lived particles at LHCb Type Journal Article
  Year 2022 Publication Frontiers in Big Data Abbreviated Journal Front. Big Data  
  Volume 5 Issue Pages 1008737 - 13pp  
  Keywords LHCb; trigger; real time analysis; long-lived particles; GPU; SciFi; beyond standard physics  
  Abstract Long-lived particles (LLPs) show up in many extensions of the Standard Model, but they are challenging to search for with current detectors, due to their very displaced vertices. This study evaluated the ability of the trigger algorithms used in the Large Hadron Collider beauty (LHCb) experiment to detect long-lived particles and attempted to adapt them to enhance the sensitivity of this experiment to undiscovered long-lived particles. A model with a Higgs portal to a dark sector is tested, and the sensitivity reach is discussed. In the LHCb tracking system, the farthest tracking station from the collision point is the scintillating fiber tracker, the SciFi detector. One of the challenges in the track reconstruction is to deal with the large amount of and combinatorics of hits in the LHCb detector. A dedicated algorithm has been developed to cope with the large data output. When fully implemented, this algorithm would greatly increase the available statistics for any long-lived particle search in the forward region and would additionally improve the sensitivity of analyses dealing with Standard Model particles of large lifetime, such as KS0 or Lambda (0) hadrons.  
  Address [Calefice, Lukas] Sorbonne Univ, Lab Phys Nucl & Hautes Energies, CNRS, IN2P3, Paris, France, Email: arantza.oyanguren@ific.uv.es  
  Corporate Author Thesis  
  Publisher Frontiers Media Sa Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000889005000001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5423  
Permanent link to this record
 

 
Author Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. url  doi
openurl 
  Title Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge Type Journal Article
  Year 2021 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.  
  Volume 656 Issue Pages A62 - 18pp  
  Keywords catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing  
  Abstract Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.  
  Address [Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com  
  Corporate Author Thesis  
  Publisher Edp Sciences S A Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000725877600001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5053  
Permanent link to this record
 

 
Author Trotta, R.; Johannesson, G.; Moskalenko, I.V.; Porter, T.A.; Ruiz de Austri, R.; Strong, A.W. url  doi
openurl 
  Title Constraints on Cosmic-Ray Propagation Models from a Global Bayesian Analysis Type Journal Article
  Year 2011 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.  
  Volume 729 Issue 2 Pages 106 - 16pp  
  Keywords astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical  
  Abstract Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP.  
  Address [Trotta, R.] Univ London Imperial Coll Sci Technol & Med, Astrophys Grp, Blackett Lab, London SW7 2AZ, England  
  Corporate Author Thesis  
  Publisher Iop Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) 0004-637x ISBN Medium  
  Area Expedition Conference  
  Notes ISI:000288608700029 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 541  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records:
ific federMinisterio de Ciencia e InnovaciĆ³nAgencia Estatal de Investigaciongva