| Records |
| Author |
Jueid, A.; Kip, J.; Ruiz de Austri, R.; Skands, P. |
| Title |
Impact of QCD uncertainties on antiproton spectra from dark-matter annihilation |
Type |
Journal Article |
| Year |
2023 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
| Volume |
04 |
Issue  |
4 |
Pages |
068 - 15pp |
| Keywords |
cosmic ray theory; dark matter simulations; cosmic ray experiments; Frequentist statistics |
| Abstract |
Dark-matter particles that annihilate or decay can undergo complex sequences of processes, including strong and electromagnetic radiation, hadronisation, and hadron de-cays, before particles that are stable on astrophysical time scales are produced. Antiprotons produced in this way may leave footprints in experiments such as AMS-02. Several groups have reported an excess of events in the antiproton flux in the rigidity range of 10-20 GV. However, the theoretical modeling of baryon production is not straightforward and relies in part on phenomenological models in Monte Carlo event generators. In this work, we assess the impact of QCD uncertainties on the spectra of antiprotons from dark-matter annihila-tion. As a proof-of-principle, we show that for a two-parameter model that depends only on the thermally-averaged annihilation cross section ((o -v)) and the dark-matter mass (Mx), QCD uncertainties can affect the best-fit mass by up to ti 14% (with large uncertainties for large DM masses), depending on the choice of Mx and the annihilation channel (bb over bar or W+W-), and (o -v) by up to ti 10%. For comparison, changes to the underlying diffusion parameters are found to be within 1%-5%, and the results are also quite resilient to the choice of cosmic-ray propagation model. These findings indicate that QCD uncertainties need to be included in future DM analyses. To facilitate full-fledged analyses, we provide the spectra in tabulated form including QCD uncertainties and code snippets to perform mass interpolations and quick DM fits. The code can be found in this GitHub [1] repository. |
| Address |
[Jueid, Adil] Inst Basic Sci IBS, Ctr Theoret Phys Universe, Daejeon 34126, South Korea, Email: adiljueid@ibs.re.kr; |
| Corporate Author |
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Thesis |
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| Publisher |
IOP Publishing Ltd |
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 |
1475-7516 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000985779900007 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5532 |
| Permanent link to this record |
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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. |
| Title |
Highly-parallelized simulation of a pixelated LArTPC on a GPU |
Type |
Journal Article |
| Year |
2023 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
18 |
Issue |
4 |
Pages |
P04034 - 35pp |
| 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) |
| 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. |
| Address |
[Isenhower, L.] Abilene Christian Univ, Abilene, TX 79601 USA, Email: roberto@lbl.gov |
| Corporate Author |
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Thesis |
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| Publisher |
IOP Publishing Ltd |
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 Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1748-0221 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000986658100009 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5551 |
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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 |
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 |
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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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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:001072112100006 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5707 |
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| Author |
Caron, S.; Gomez-Vargas, G.A.; Hendriks, L.; Ruiz de Austri, R. |
| Title |
Analyzing gamma rays of the Galactic Center with deep learning |
Type |
Journal Article |
| Year |
2018 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
| Volume |
05 |
Issue |
5 |
Pages |
058 - 24pp |
| Keywords |
gamma ray experiments; dark matter simulations |
| Abstract |
We present the application of convolutional neural networks to a particular problem in gamma ray astronomy. Explicitly, we use this method to investigate the origin of an excess emission of GeV gamma rays in the direction of the Galactic Center, reported by several groups by analyzing Fermi-LAT data. Interpretations of this excess include gamma rays created by the annihilation of dark matter particles and gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. We train and test convolutional neural networks with simulated Fermi-LAT images based on point and diffuse emission models of the Galactic Center tuned to measured gamma ray data. Our new method allows precise measurements of the contribution and properties of an unresolved population of gamma ray point sources in the interstellar diffuse emission model. The current model predicts the fraction of unresolved point sources with an error of up to 10% and this is expected to decrease with future work. |
| Address |
[Caron, Sascha; Hendriks, Luc] Radboud Univ Nijmegen, Fac Sci, Inst Math Astrophys & Particle Phys, Mailbox 79,POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: scaron@cern.ch; |
| Corporate Author |
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Thesis |
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| Publisher |
Iop Publishing Ltd |
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 |
1475-7516 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000432869300005 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
3582 |
| Permanent link to this record |
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| Author |
Amoroso, S.; Caron, S.; Jueid, A.; Ruiz de Austri, R.; Skands, P. |
| Title |
Estimating QCD uncertainties in Monte Carlo event generators for gamma-ray dark matter searches |
Type |
Journal Article |
| Year |
2019 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
| Volume |
05 |
Issue |
5 |
Pages |
007 - 44pp |
| Keywords |
dark matter simulations; dark matter theory; gamma ray theory |
| Abstract |
Motivated by the recent galactic center gamma-ray excess identified in the Fermi-LAT data, we perform a detailed study of QCD fragmentation uncertainties in the modeling of the energy spectra of gamma-rays from Dark-Matter (DM) annihilation. When Dark-Matter particles annihilate to coloured final states, either directly or via decays such as W(*) -> qq-', photons are produced from a complex sequence of shower, hadronisation and hadron decays. In phenomenological studies their energy spectra are typically computed using Monte Carlo event generators. These results have however intrinsic uncertainties due to the specific model used and the choice of model parameters, which are difficult to asses and which are typically neglected. We derive a new set of hadronisation parameters (tunes) for the PYTHIA 8.2 Monte Carlo generator from a fit to LEP and SLD data at the Z peak. For the first time we also derive a conservative set of uncertainties on the shower and hadronisation model parameters. Their impact on the gamma-ray energy spectra is evaluated and discussed for a range of DM masses and annihilation channels. The spectra and their uncertainties are also provided in tabulated form for future use. The fragmentation-parameter uncertainties may be useful for collider studies as well. |
| Address |
[Amoroso, Simone] DESY, Notkestr 85, D-22607 Hamburg, Germany, Email: simone.amoroso@desy.de; |
| Corporate Author |
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Thesis |
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| Publisher |
Iop Publishing Ltd |
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 |
1475-7516 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000467288200002 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
4006 |
| Permanent link to this record |
