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Author Gammaldi, V.; Zaldivar, B.; Sanchez-Conde, M.A.; Coronado-Blazquez, J.
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 (up) 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 no
Call Number IFIC @ pastor @ Serial 5489
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Author de los Rios, M.; Petac, M.; Zaldivar, B.; Bonaventura, N.R.; Calore, F.; Iocco, F.
Title Determining the dark matter distribution in simulated galaxies with deep learning Type Journal Article
Year 2023 Publication Monthly Notices of the Royal Astronomical Society Abbreviated Journal (up) Mon. Not. Roy. Astron. Soc.
Volume 525 Issue 4 Pages 6015-6035
Keywords methods: data analysis; software: simulations; galaxies: general; galaxies: haloes; dark matter
Abstract We present a novel method of inferring the dark matter (DM) content and spatial distribution within galaxies, using convolutional neural networks (CNNs) trained within state-of-the-art hydrodynamical simulations (Illustris-TNG100). Within the controlled environment of the simulation, the framework we have developed is capable of inferring the DM mass distribution within galaxies of mass similar to 10(11)-10(13)M(circle dot) from the gravitationally baryon-dominated internal regions to the DM-rich, baryon-depleted outskirts of the galaxies, with a mean absolute error always below approximate to 0.25 when using photometrical and spectroscopic information. With respect to traditional methods, the one presented here also possesses the advantages of not relying on a pre-assigned shape for the DM distribution, to be applicable to galaxies not necessarily in isolation, and to perform very well even in the absence of spectroscopic observations.
Address [de los Rios, Martin] Univ Estadual Paulista, ICTP South Amer Inst Fundamental Res, Inst Fis Teor, BR-01140070 Sao Paulo, SP, Brazil, Email: fabio.iocco.astro@gmail.com
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:001072112100006 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5707
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Author Ferreira, M.N.; Papavassiliou, J.
Title Gauge Sector Dynamics in QCD Type Journal Article
Year 2023 Publication Particles Abbreviated Journal (up) 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 no
Call Number IFIC @ pastor @ Serial 5504
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Author Binosi, D.; Chang, L.; Ding, M.H.; Gao, F.; Papavassiliou, J.; Roberts, C.D.
Title Distribution amplitudes of heavy-light mesons Type Journal Article
Year 2019 Publication Physics Letters B Abbreviated Journal (up) Phys. Lett. B
Volume 790 Issue Pages 257-262
Keywords B-meson decays; Heavy-light mesons; Nonperturbative continuum methods in quantum field theory; Parton distribution amplitudes; Quantum chromodynamics
Abstract A symmetry-preserving approach to the continuum bound-state problem in quantum field theory is used to calculate the masses, leptonic decay constants and light-front distribution amplitudes of empirically accessible heavy-light mesons. The inverse moment of the B-meson distribution is particularly important in treatments of exclusive B-decays using effective field theory and the factorisation formalism; and its value is therefore computed: lambda(B) = (zeta = 2GeV) = 0.54(3) GeV. As an example and in anticipation of precision measurements at new-generation B-factories, the branching fraction for the rare B -> gamma (E-gamma)l nu(l) radiative decay is also calculated, retaining 1/m(B)(2), and 1/E-gamma(2) corrections to the differential decay width, with the result Gamma(B -> gamma l nu l) /Gamma(B) = 0.47 (15) on E-gamma > 1.5 GeV.
Address [Binosi, Daniele; Ding, Minghui] European Ctr Theoret Studies Nucl Phys & Related, Str Tabarelle 286, I-38123 Villazzano, TN, Italy, Email: binosi@ectstar.eu;
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0370-2693 ISBN Medium
Area Expedition Conference
Notes WOS:000460118200030 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 3934
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Author Aguilar, A.C.; De Soto, F.; Ferreira, M.N.; Papavassiliou, J.; Pinto-Gomez, F.; Roberts, C.D.; Rodriguez-Quintero, J.
Title Schwinger mechanism for gluons from lattice QCD Type Journal Article
Year 2023 Publication Physics Letters B Abbreviated Journal (up) Phys. Lett. B
Volume 841 Issue Pages 137906 - 8pp
Keywords Continuum Schwinger function methods; Emergence of mass; Gluons; Lattice Schwinger function methods; Quantum chromodynamics; Schwinger mechanism of gauge boson mass; generation
Abstract Continuum and lattice analyses have revealed the existence of a mass-scale in the gluon two-point Schwinger function. It has long been conjectured that this expresses the action of a Schwinger mechanism for gauge boson mass generation in quantum chromodynamics (QCD). For such to be true, it is necessary and sufficient that a dynamically-generated, massless, colour-carrying, scalar gluon+gluon correlation emerges as a feature of the dressed three-gluon vertex. Working with results on elementary Schwinger functions obtained via the numerical simulation of lattice-regularised QCD, we establish with an extremely high level of confidence that just such a feature appears; hence, confirm the conjectured origin of the gluon mass scale.
Address [Aguilar, A. C.] Univ Estadual Campinas, Inst Phys Gleb Wataghin, UNICAMP, BR-13083859 Campinas, SP, Brazil, Email: cristina.aguilar@unicamp.br;
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0370-2693 ISBN Medium
Area Expedition Conference
Notes WOS:000984221700001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5530
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Author Ortega, P.G.; Torres-Espallardo, I.; Cerutti, F.; Ferrari, A.; Gillam, J.E.; Lacasta, C.; Llosa, G.; Oliver, J.F.; Sala, P.R.; Solevi, P.; Rafecas, M.
Title Noise evaluation of Compton camera imaging for proton therapy Type Journal Article
Year 2015 Publication Physics in Medicine and Biology Abbreviated Journal (up) Phys. Med. Biol.
Volume 60 Issue 5 Pages 1845-1863
Keywords proton therapy; Compton camera; Monte Carlo methods; FLUKA; prompt gamma; range verification; MLEM
Abstract Compton Cameras emerged as an alternative for real-time dose monitoring techniques for Particle Therapy (PT), based on the detection of prompt-gammas. As a consequence of the Compton scattering process, the gamma origin point can be restricted onto the surface of a cone (Compton cone). Through image reconstruction techniques, the distribution of the gamma emitters can be estimated, using cone-surfaces backprojections of the Compton cones through the image space, along with more sophisticated statistical methods to improve the image quality. To calculate the Compton cone required for image reconstruction, either two interactions, the last being photoelectric absorption, or three scatter interactions are needed. Because of the high energy of the photons in PT the first option might not be adequate, as the photon is not absorbed in general. However, the second option is less efficient. That is the reason to resort to spectral reconstructions, where the incoming. energy is considered as a variable in the reconstruction inverse problem. Jointly with prompt gamma, secondary neutrons and scattered photons, not strongly correlated with the dose map, can also reach the imaging detector and produce false events. These events deteriorate the image quality. Also, high intensity beams can produce particle accumulation in the camera, which lead to an increase of random coincidences, meaning events which gather measurements from different incoming particles. The noise scenario is expected to be different if double or triple events are used, and consequently, the reconstructed images can be affected differently by spurious data. The aim of the present work is to study the effect of false events in the reconstructed image, evaluating their impact in the determination of the beam particle ranges. A simulation study that includes misidentified events (neutrons and random coincidences) in the final image of a Compton Telescope for PT monitoring is presented. The complete chain of detection, from the beam particle entering a phantom to the event classification, is simulated using FLUKA. The range determination is later estimated from the reconstructed image obtained from a two and three-event algorithm based on Maximum Likelihood Expectation Maximization. The neutron background and random coincidences due to a therapeutic-like time structure are analyzed for mono-energetic proton beams. The time structure of the beam is included in the simulations, which will affect the rate of particles entering the detector.
Address [Ortega, P. G.; Cerutti, F.; Ferrari, A.] CERN European Org Nucl Res, CH-1217 Meyrin, Switzerland, Email: pgarciao@cern.ch
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 0031-9155 ISBN Medium
Area Expedition Conference
Notes WOS:000349530700009 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 2115
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Author Kasieczka, G. et al; Sanz, V.
Title The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics Type Journal Article
Year 2021 Publication Reports on Progress in Physics Abbreviated Journal (up) Rep. Prog. Phys.
Volume 84 Issue 12 Pages 124201 - 64pp
Keywords anomaly detection; machine learning; unsupervised learning; weakly supervised learning; semisupervised learning; beyond the standard model; model-agnostic methods
Abstract A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.
Address [Kasieczka, Gregor] Univ Hamburg, Inst Expt Phys, Hamburg, Germany, Email: gregor.kasieczka@uni-hamburg.de;
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 0034-4885 ISBN Medium
Area Expedition Conference
Notes WOS:000727698500001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5039
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