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Author Ortiz Arciniega, J.L.; Carrio, F.; Valero, A. url  doi
openurl 
  Title FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions Type Journal Article
  Year 2019 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.  
  Volume 14 Issue Pages P09002 - 13pp  
  Keywords Data processing methods; Pattern recognition; cluster finding; calibration and fitting methods; Simulation methods and programs  
  Abstract The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions since the signal pulse shape gets distorted. In addition, this type of experiments produces a high rate of collisions, which requires high throughput data acquisitions systems. In order to cope with these harsh requirements, new read-out electronics systems are based on high-performance FPGAs, which permit the utilization of more advanced real-time signal reconstruction algorithms. In this paper, a deep learning method is proposed for real-time signal reconstruction in high pileup particle detectors. The performance of the new method has been studied using simulated data and the results are compared with a classical FIR filter method. In particular, the signals and FIR filter used in the ATLAS Tile Calorimeter are used as benchmark. The implementation, resources usage and performance of the proposed Neural Network algorithm in FPGA are also presented.  
  Address [Ortiz Arciniega, J. L.] Univ Valencia, Avinguda Univ S-N, Burjassot, Spain, Email: orarjo@alumni.uv.es  
  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 1748-0221 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000486990000002 Approved no  
  Is ISI yes International Collaboration (up) no  
  Call Number IFIC @ pastor @ Serial 4150  
Permanent link to this record
 

 
Author Gammaldi, V.; Zaldivar, B.; Sanchez-Conde, M.A.; Coronado-Blazquez, J. url  doi
openurl 
  Title A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning Type Journal Article
  Year 2023 Publication Monthly Notices of the Royal Astronomical Society Abbreviated Journal Mon. Not. Roy. Astron. Soc.  
  Volume 520 Issue 1 Pages 1348-1361  
  Keywords astroparticle physics – methods; data analysis – methods; observational – methods; statistical – dark matter – gamma-rays; general  
  Abstract Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs.  
  Address [Gammaldi, V; Sanchez-Conde, M. A.; Coronado-Blazquez, J.] Univ Autonoma Madrid, Departamentode Fis Teor, E-28049 Madrid, Spain, Email: viviana.gammaldi@uam.es;  
  Corporate Author Thesis  
  Publisher Oxford Univ Press Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0035-8711 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000937053400014 Approved no  
  Is ISI yes International Collaboration (up) no  
  Call Number IFIC @ pastor @ Serial 5489  
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Author Ferreira, M.N.; Papavassiliou, J. url  doi
openurl 
  Title Gauge Sector Dynamics in QCD Type Journal Article
  Year 2023 Publication Particles Abbreviated Journal Particles  
  Volume 6 Issue 1 Pages 312-363  
  Keywords continuum Schwinger function methods; emergence of hadron mass; gluon mass generation; lattice QCD; non-perturbative quantum field theory; quantum chromodynamics; Schwinger-Dyson equations; Schwinger mechanism  
  Abstract The dynamics of the QCD gauge sector give rise to non-perturbative phenomena that are crucial for the internal consistency of the theory; most notably, they account for the generation of a gluon mass through the action of the Schwinger mechanism, the taming of the Landau pole, the ensuing stabilization of the gauge coupling, and the infrared suppression of the three-gluon vertex. In the present work, we review some key advances in the ongoing investigation of this sector within the framework of the continuum Schwinger function methods, supplemented by results obtained from lattice simulations.  
  Address [Ferreira, Mauricio Narciso; Papavassiliou, Joannis] Univ Valencia, Dept Theoret Phys, E-46100 Valencia, Spain, Email: ansonar@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 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000959126400001 Approved no  
  Is ISI yes International Collaboration (up) no  
  Call Number IFIC @ pastor @ Serial 5504  
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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 0004-637x ISBN Medium  
  Area Expedition Conference  
  Notes ISI:000288608700029 Approved no  
  Is ISI yes International Collaboration (up) yes  
  Call Number IFIC @ pastor @ Serial 541  
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Author Rivard, M.J.; Granero, D.; Perez-Calatayud, J.; Ballester, F. doi  openurl
  Title Influence of photon energy spectra from brachytherapy sources on Monte Carlo simulations of kerma and dose rates in water and air Type Journal Article
  Year 2010 Publication Medical Physics Abbreviated Journal Med. Phys.  
  Volume 37 Issue 2 Pages 869-876  
  Keywords biomedical materials; brachytherapy; dosimetry; iodine; iridium; Monte Carlo methods; palladium; radioisotopes  
  Abstract Methods: For Ir-192, I-125, and Pd-103, the authors considered from two to five published spectra. Spherical sources approximating common brachytherapy sources were assessed. Kerma and dose results from GEANT4, MCNP5, and PENELOPE-2008 were compared for water and air. The dosimetric influence of Ir-192, I-125, and Pd-103 spectral choice was determined. Results: For the spectra considered, there were no statistically significant differences between kerma or dose results based on Monte Carlo code choice when using the same spectrum. Water-kerma differences of about 2%, 2%, and 0.7% were observed due to spectrum choice for Ir-192, I-125, and Pd-103, respectively (independent of radial distance), when accounting for photon yield per Bq. Similar differences were observed for air-kerma rate. However, their ratio (as used in the dose-rate constant) did not significantly change when the various photon spectra were selected because the differences compensated each other when dividing dose rate by air-kerma strength. Conclusions: Given the standardization of radionuclide data available from the National Nuclear Data Center (NNDC) and the rigorous infrastructure for performing and maintaining the data set evaluations, NNDC spectra are suggested for brachytherapy simulations in medical physics applications.  
  Address [Rivard, Mark J.] Tufts Univ, Sch Med, Dept Radiat Oncol, Boston, MA 02111 USA, Email: mrivard@tuftsmedicalcenter.org  
  Corporate Author Thesis  
  Publisher Amer Assoc Physicists Medicine Amer Inst Physics Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0094-2405 ISBN Medium  
  Area Expedition Conference  
  Notes ISI:000274075600048 Approved no  
  Is ISI yes International Collaboration (up) yes  
  Call Number IFIC @ elepoucu @ Serial 504  
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