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Author |
de los Rios, M.; Petac, M.; Zaldivar, B.; Bonaventura, N.R.; Calore, F.; Iocco, F. |
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Title |
Determining the dark matter distribution in simulated galaxies with deep learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
525 |
Issue |
4 |
Pages |
6015-6035 |
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Keywords |
methods: data analysis; software: simulations; galaxies: general; galaxies: haloes; dark matter |
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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. |
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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 |
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Publisher |
Oxford Univ Press |
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Language |
English |
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ISSN |
0035-8711 |
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Conference |
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Notes |
WOS:001072112100006 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5707 |
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Author |
Double Chooz collaboration (Abrahao, T. et al); Novella, P. |
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Title |
Novel event classification based on spectral analysis of scintillation waveforms in Double Chooz |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
13 |
Issue |
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Pages |
P01031 - 26pp |
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Keywords |
Digital signal processing (DSP); Particle identification methods; Scintillators, scintillation and light emission processes (solid, gas and liquid scintillators); Neutrino detectors |
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Abstract |
Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in large detectors. This paper describes a novel approach for a pulse shape based event classification developed in the context of the Double Chooz reactor antineutrino experiment. Unlike previous implementations, this method uses the Fourier power spectra of the scintillation pulse shapes to obtain event-wise information. A classification variable built from spectral information was able to achieve an unprecedented performance, despite the lack of optimization at the detector design level. Several examples of event classification are provided, ranging from differentiation between the detector volumes and an efficient rejection of instrumental light noise, to some sensitivity to the particle type, such as stopping muons, ortho-positronium formation, alpha particles as well as electrons and positrons. In combination with other techniques the method is expected to allow for a versatile and more efficient background rejection in the future, especially if detector optimization is taken into account at the design level. |
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Address |
[Abrahao, T.; dos Anjos, J. C.; Lima, H.; Pepe, I.; Wagner, S.] Ctr Brasileiro Pesquisas Fis, BR-22290180 Rio De Janeiro, Brazil, Email: stefan.wagner@apc.in2p3.fr |
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Publisher |
Iop Publishing Ltd |
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Language |
English |
Summary Language |
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Edition |
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ISSN |
1748-0221 |
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Conference |
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Notes |
WOS:000423783800003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3466 |
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Author |
DUNE Collaboration (Abud, A.A. et al); Amedo, P.; Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Garcia-Peris, M.A.; Martin-Albo, J.; Martinez-Mirave, P.; Mena, O.; Molina Bueno, L.; Novella, P.; Pompa, F.; Rocabado Rocha, J.L.; Sorel, M.; Tortola, M.; Tuzi, M.; Valle, J.W.F.; Yahlali, N. |
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Title |
Highly-parallelized simulation of a pixelated LArTPC on a GPU |
Type |
Journal Article |
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Year |
2023 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
18 |
Issue |
4 |
Pages |
P04034 - 35pp |
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Keywords |
Detector modelling and simulations II (electric fields, charge transport, multiplication, and induction, pulse formation, electron emission, etc); Simulation methods and programs; Nobleliquid detectors (scintillation, ionization, double-phase); Time projection Chambers (TPC) |
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Abstract |
The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 103 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype. |
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Address |
[Isenhower, L.] Abilene Christian Univ, Abilene, TX 79601 USA, Email: roberto@lbl.gov |
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Publisher |
IOP Publishing Ltd |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
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Expedition |
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Conference |
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Notes |
WOS:000986658100009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5551 |
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Author |
Ferreira, M.N.; Papavassiliou, J. |
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Title |
Gauge Sector Dynamics in QCD |
Type |
Journal Article |
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Year |
2023 |
Publication |
Particles |
Abbreviated Journal |
Particles |
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Volume |
6 |
Issue |
1 |
Pages |
312-363 |
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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 |
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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. |
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Address |
[Ferreira, Mauricio Narciso; Papavassiliou, Joannis] Univ Valencia, Dept Theoret Phys, E-46100 Valencia, Spain, Email: ansonar@uv.es; |
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Corporate Author |
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Publisher |
Mdpi |
Place of Publication |
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Language |
English |
Summary Language |
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Expedition |
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Conference |
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Notes |
WOS:000959126400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5504 |
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Author |
Gammaldi, V.; Zaldivar, B.; Sanchez-Conde, M.A.; Coronado-Blazquez, J. |
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Title |
A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
520 |
Issue |
1 |
Pages |
1348-1361 |
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Keywords |
astroparticle physics – methods; data analysis – methods; observational – methods; statistical – dark matter – gamma-rays; general |
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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. |
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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; |
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Corporate Author |
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Thesis |
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Publisher |
Oxford Univ Press |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0035-8711 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000937053400014 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5489 |
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