| Records |
| Author |
Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
| 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 |
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Thesis |
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| Publisher |
Edp Sciences S A |
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 |
0004-6361 |
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:000725877600001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5053 |
| Permanent link to this record |
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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 |
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 |
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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 |
0031-9155 |
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:000349530700009 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
2115 |
| Permanent link to this record |
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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 |
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 |
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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:000937053400014 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
no |
| Call Number |
IFIC @ pastor @ |
Serial |
5489 |
| Permanent link to this record |
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| Author |
Yepes, H. |
| Title |
The ANTARES neutrino detector instrumentation |
Type |
Journal Article |
| Year |
2012 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
7 |
Issue |
|
Pages |
C01022 - 9pp |
| Keywords |
Large detector-systems performance; Performance of High Energy Physics Detectors; Detector alignment and calibration methods (lasers, sources, particle-beams) |
| Abstract |
ANTARES is actually the fully operational and the largest neutrino telescope in the Northern hemisphere. Located in the Mediterranean Sea, it consists of a 3D array of 885 photomultiplier tubes (PMTs) arranged in 12 detection lines (25 storeys each), able to detect the Cherenkov light induced by upgoing relativistic muons produced in the interaction of high energy cosmic neutrinos with the detector surroundings. Among its physics goals, the search for neutrino astrophysical sources and the indirect detection of dark matter particles coming from the sun are of particular interest. To reach these goals, good accuracy in track reconstruction is mandatory, so several calibration systems for timing and positioning have been developed. In this contribution we will present the design of the detector, calibration systems, associated equipment and its performance on track reconstruction. |
| Address |
Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, E-46071 Valencia, Spain, Email: Harold.Yepes@ific.uv.es |
| 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 |
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:000303806200022 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
no |
| Call Number |
IFIC @ pastor @ |
Serial |
1041 |
| Permanent link to this record |
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| Author |
LHCb Collaboration (Aaij, R. et al); Martinez-Vidal, F.; Oyanguren, A.; Ruiz Valls, P.; Sanchez Mayordomo, C. |
| Title |
B flavour tagging using charm decays at the LHCb experiment |
Type |
Journal Article |
| Year |
2015 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
10 |
Issue |
|
Pages |
P10005 - 16pp |
| Keywords |
Performance of High Energy Physics Detectors; Analysis and statistical methods |
| Abstract |
An algorithm is described for tagging the flavour content at production of neutral B mesons in the LHCb experiment. The algorithm exploits the correlation of the flavour of a B meson with the charge of a reconstructed secondary charm hadron from the decay of the other b hadron produced in the proton-proton collision. Charm hadron candidates are identified in a number of fully or partially reconstructed Cabibbo-favoured decay modes. The algorithm is calibrated on the self-tagged decay modes B+ -> J/psi K+ and B-0 -> J/psi K*(0) using 3.0fb(-1) of data collected by the LHCb experiment at pp centre-of-mass energies of 7TeV and 8TeV. Its tagging power on these samples of B -> J/psi X decays is (0.30 +/- 0.01 +/- 0.01) %. |
| Address |
[Bediaga, I.; De Miranda, J. M.; Ferreira Rodrigues, F.; Gomes, A.; Massafferri, A.; Osorio Rodrigues, B.; dos Reis, A. C.; Rodrigues, A. B.] CBPF, Rio De Janeiro, Brazil, Email: jwimberl@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 |
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:000367674700007 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
2519 |
| Permanent link to this record |
