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Author |
Olleros, P.; Caballero, L.; Domingo-Pardo, C.; Babiano, V.; Ladarescu, I.; Calvo, D.; Gramage, P.; Nacher, E.; Tain, J.L.; Tolosa, A. |
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Title |
On the performance of large monolithic LaCl3(Ce) crystals coupled to pixelated silicon photosensors |
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 |
P03014 - 17pp |
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Keywords |
Compton imaging; Detector modelling and simulations I (interaction of radiation with matter interaction of photons with matter interaction of hadrons with matter etc); Gamma detectors (scintillators CZT HPG HgI etc); Instrumentation and methods for time-of-flight (TOF); spectroscopy |
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Abstract |
We investigate the performance of large area radiation detectors, with high energy-and spatial-resolution, intended for the development of a Total Energy Detector with gamma-ray imaging capability, so-called i-TED. This new development aims for an enhancement in detection sensitivity in time-of-flight neutron capture measurements, versus the commonly used C6D6 liquid scintillation total-energy detectors. In this work, we study in detail the impact of the readout photosensor on the energy response of large area (50 x 50 mm(2)) monolithic LaCl3(Ce) crystals, in particular when replacing a conventional mono-cathode photomultiplier tube by an 8 x 8 pixelated silicon photomultiplier. Using the largest commercially available monolithic SiPM array (25 cm(2)), with a pixel size of 6 x 6 mm(2), we have measured an average energy resolution of 3.92% FWHM at 662 keV for crystal thick-nesses of 10, 20 and 30 mm. The results are confronted with detailed Monte Carlo (MC) calculations, where optical processes and properties have been included for the reliable tracking of the scintillation photons. After the experimental validation of the MC model, we use our MC code to explore the impact of a smaller photosensor segmentation on the energy resolution. Our optical MC simulations predict only a marginal deterioration of the spectroscopic performance for pixels of 3 x 3 mm(2). |
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Address  |
[Olleros, P.; Caballero, L.; Domingo-Pardo, C.; Babiano, V.; Ladarescu, I.; Calvo, D.; Gramage, P.; Tain, J. L.; Tolosa, A.] Univ Valencia, CSIC, Inst Fis Corpuscular, C Catedrat Jose Beltran 2, Paterna 46980, Spain, Email: Luis.Caballero@ific.uv.es |
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Iop Publishing Ltd |
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English |
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ISSN |
1748-0221 |
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Notes |
WOS:000428146300004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3542 |
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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. |
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Title |
Noise evaluation of Compton camera imaging for proton therapy |
Type |
Journal Article |
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Year |
2015 |
Publication |
Physics in Medicine and Biology |
Abbreviated Journal |
Phys. Med. Biol. |
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Volume |
60 |
Issue |
5 |
Pages |
1845-1863 |
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Keywords |
proton therapy; Compton camera; Monte Carlo methods; FLUKA; prompt gamma; range verification; MLEM |
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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. |
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Address |
[Ortega, P. G.; Cerutti, F.; Ferrari, A.] CERN European Org Nucl Res, CH-1217 Meyrin, Switzerland, Email: pgarciao@cern.ch |
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Publisher |
Iop Publishing Ltd |
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English |
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Edition |
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ISSN |
0031-9155 |
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Expedition |
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Conference |
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Notes |
WOS:000349530700009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2115 |
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Author |
Ortiz Arciniega, J.L.; Carrio, F.; Valero, A. |
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Title |
FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions |
Type |
Journal Article |
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Year |
2019 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
14 |
Issue |
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Pages |
P09002 - 13pp |
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Keywords |
Data processing methods; Pattern recognition; cluster finding; calibration and fitting methods; Simulation methods and programs |
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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. |
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Address |
[Ortiz Arciniega, J. L.] Univ Valencia, Avinguda Univ S-N, Burjassot, Spain, Email: orarjo@alumni.uv.es |
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Corporate Author |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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English |
Summary Language |
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Original 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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Area |
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Expedition |
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Conference |
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Notes |
WOS:000486990000002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4150 |
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Author |
Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
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Title |
Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge |
Type |
Journal Article |
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Year |
2021 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
656 |
Issue |
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Pages |
A62 - 18pp |
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Keywords |
catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing |
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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. |
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Address |
[Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com |
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Publisher |
Edp Sciences S A |
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Language |
English |
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Original Title |
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ISSN |
0004-6361 |
ISBN |
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Conference |
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Notes |
WOS:000725877600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5053 |
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Author |
ANTARES and HESS Collaborations (Petroff, E. et al); Barrios-Marti, J.; Hernandez-Rey, J.J.; Illuminati, G.; Lotze, M.; Tönnis, C.; Zornoza, J.D.; Zuñiga, J. |
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Title |
A polarized fast radio burst at low Galactic latitude |
Type |
Journal Article |
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Year |
2017 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
469 |
Issue |
4 |
Pages |
4465-4482 |
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Keywords |
polarization; methods: data analysis; surveys; ISM: structure |
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Abstract |
We report on the discovery of a new fast radio burst (FRB), FRB 150215, with the Parkes radio telescope on 2015 February 15. The burst was detected in real time with a dispersion measure (DM) of 1105.6 +/- 0.8 pc cm(-3), a pulse duration of 2.8(-0.5)(+1.2) ms, and a measured peak flux density assuming that the burst was at beam centre of 0.7(-0.1)(+0.2) Jy. The FRB originated at a Galactic longitude and latitude of 24.66 degrees, 5.28 degrees and 25 degrees away from the Galactic Center. The burst was found to be 43 +/- 5 per cent linearly polarized with a rotation measure (RM) in the range -9 < RM < 12 rad m(-2) (95 per cent confidence level), consistent with zero. The burst was followed up with 11 telescopes to search for radio, optical, X-ray, gamma-ray and neutrino emission. Neither transient nor variable emission was found to be associated with the burst and no repeat pulses have been observed in 17.25 h of observing. The sightline to the burst is close to the Galactic plane and the observed physical properties of FRB 150215 demonstrate the existence of sight lines of anomalously low RM for a given electron column density. The Galactic RM foreground may approach a null value due to magnetic field reversals along the line of sight, a decreased total electron column density from the Milky Way, or some combination of these effects. A lower Galactic DM contribution might explain why this burst was detectable whereas previous searches at low latitude have had lower detection rates than those out of the plane. |
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Address |
[Petroff, E.; Rowlinson, A.] Netherlands Inst Radio Astron, ASTRON, Postbus 2, NL-7990 AA Dwingeloo, Netherlands |
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Publisher |
Oxford Univ Press |
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English |
Summary Language |
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ISSN |
0035-8711 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000406837900051 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3241 |
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Author |
Renner, J.; Cervera-Villanueva, A.; Hernando, J.A.; Izmaylov, A.; Monrabal, F.; Muñoz, J.; Nygren, D.; Gomez-Cadenas, J.J. |
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Title |
Improved background rejection in neutrinoless double beta decay experiments using a magnetic field in a high pressure xenon TPC |
Type |
Journal Article |
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Year |
2015 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
10 |
Issue |
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Pages |
P12020 - 19pp |
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Keywords |
Pattern recognition, cluster finding, calibration and fitting methods; Double-beta decay detectors; Time projection chambers; Particle tracking detectors (Gaseous detectors) |
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Abstract |
We demonstrate that the application of an external magnetic field could lead to an improved background rejection in neutrinoless double-beta (0 nu beta beta) decay experiments using a high-pressure xenon (HPXe) TPC. HPXe chambers are capable of imaging electron tracks, a feature that enhances the separation between signal events (the two electrons emitted in the 0 nu beta beta decay of Xe-136) and background events, arising chiefly from single electrons of kinetic energy compatible with the end-point of the 0 nu beta beta decay (Q(beta beta)). Applying an external magnetic field of sufficiently high intensity (in the range of 0.5-1 Tesla for operating pressures in the range of 5-15 atmospheres) causes the electrons to produce helical tracks. Assuming the tracks can be properly reconstructed, the sign of the curvature can be determined at several points along these tracks, and such information can be used to separate signal (0 nu beta beta) events containing two electrons producing a track with two different directions of curvature from background (single-electron) events producing a track that should spiral in a single direction. Due to electron multiple scattering, this strategy is not perfectly efficient on an event-by-event basis, but a statistical estimator can be constructed which can be used to reject background events by one order of magnitude at a moderate cost (about 30%) in signal efficiency. Combining this estimator with the excellent energy resolution and topological signature identification characteristic of the HPXe TPC, it is possible to reach a background rate of less than one count per ton-year of exposure. Such a low background rate is an essential feature of the next generation of 0 nu beta beta experiments, aiming to fully explore the inverse hierarchy of neutrino masses. |
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Address |
[Renner, J.; Imzaylov, A.; Monrabal, F.; Munoz, J.; Gomez-Cadenas, J. J.] CSIC, Inst Fis Corpuscular IFIC, Calle Catedrat Jose Beltran 2, Valencia 46980, Spain, Email: jrenner@ific.uv.es |
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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:000369998500053 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2549 |
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Author |
NEXT Collaboration (Renner, J. et al); Benlloch-Rodriguez, J.; Botas, A.; Ferrario, P.; Gomez-Cadenas, J.J.; Alvarez, V.; Carcel, S.; Carrion, J.V.; Cervera-Villanueva, A.; Diaz, J.; Laing, A.; Liubarsky, I.; Lopez-March, N.; Lorca, D.; Martinez, A.; Monrabal, F.; Muñoz Vidal, J.; Nebot-Guinot, M.; Novella, P.; Palmeiro, B.; Querol, M.; Rodriguez, J.; Serra, L.; Simon, A.; Sorel, M.; Yahlali, N. |
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Title |
Background rejection in NEXT using deep neural networks |
Type |
Journal Article |
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Year |
2017 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
12 |
Issue |
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Pages |
T01004 - 21pp |
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Keywords |
Analysis and statistical methods; Pattern recognition; cluster finding; calibration and fitting methods; Double-beta decay detectors; Time projection chambers |
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Abstract |
We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement. |
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Address |
[Renner, J.; Munoz Vidal, J.; Benlloch-Rodriguez, J. M.; Botas, A.; Ferrario, P.; Gomez-Cadenas, J. J.; Alvarez, V.; Carcel, S.; Carrion, J. V.; Cervera, A.; Diaz, J.; Laing, A.; Liubarsky, I.; Lopez-March, N.; Lorca, D.; Martinez, A.; Monrabal, F.; Nebot-Guinot, M.; Novella, P.; Palmeiro, B.; Querol, M.; Rodriguez, J.; Serra, L.; Simon, A.; Sorel, M.; Yahlali, N.] CSIC, Inst Fis Corpuscular IFIC, Calle Catedrat Jose Beltran 2, Valencia 46980, Spain, Email: jrenner@ific.uv.es |
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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:000395770200004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2995 |
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Author |
Rivard, M.J.; Granero, D.; Perez-Calatayud, J.; Ballester, F. |
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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. |
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Volume |
37 |
Issue |
2 |
Pages |
869-876 |
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Keywords |
biomedical materials; brachytherapy; dosimetry; iodine; iridium; Monte Carlo methods; palladium; radioisotopes |
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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. |
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Address |
[Rivard, Mark J.] Tufts Univ, Sch Med, Dept Radiat Oncol, Boston, MA 02111 USA, Email: mrivard@tuftsmedicalcenter.org |
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Thesis |
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Publisher |
Amer Assoc Physicists Medicine Amer Inst Physics |
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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 |
0094-2405 |
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 |
ISI:000274075600048 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ elepoucu @ |
Serial |
504 |
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| Permanent link to this record |
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Author |
NEXT Collaboration (Simon, A. et al); Gomez-Cadenas, J. J.; Alvarez, V.; Benlloch-Rodriguez, J. M.; Botas, A.; Carcel, S.; Carrion, J.V.; Diaz, J.; Felkai, R.; Ferrario, P.; Laing, A.; Liubarsky, I.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Muñoz Vidal, J.; Musti, M.; Nebot-Guinot, M.; Novella, P.; Palmeiro, B.; Perez, J.; Querol, M.; Renner, J.; Rodriguez, J.; Sorel, M.; Torrent, J.; Yahlali, N. |
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Title |
Application and performance of an ML-EM algorithm in NEXT |
Type |
Journal Article |
| |
Year |
2017 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
12 |
Issue |
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Pages |
P08009 - 22pp |
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Keywords |
Gaseous imaging and tracking detectors; Image reconstruction in medical imaging; Time projection Chambers (TPC); Medical-image reconstruction methods and algorithms; computer-aided software |
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Abstract |
The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC. |
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[Simon, A.; Gomez-Cadenas, J. J.; Alvarez, V.; Benlloch-Rodriguez, J. M.; Botas, A.; Carcel, S.; Carrion, J. V.; Diaz, J.; Felkai, R.; Ferrario, P.; Laing, A.; Liubarsky, I.; Lopez-March, N.; Martin-Albo, J.; Martinez, A.; Munoz Vidal, J.; Musti, M.; Nebot-Guinot, M.; Novella, P.; Palmeiro, B.; Perez, J.; Querol, M.; Renner, J.; Rodriguez, J.; Sorel, M.; Torrent, J.; Yahlali, N.] CSIC, Inst Fis Corpuscular IFIC, Calle Catedrat Jose Beltran 2, Valencia 46980, Spain, Email: ander.simon@ific.uv.es |
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Iop Publishing Ltd |
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English |
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1748-0221 |
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WOS:000414159500009 |
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no |
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yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3358 |
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Author |
Stoppa, F.; Bhattacharyya, S.; Ruiz de Austri, R.; Vreeswijk, P.; Caron, S.; Zaharijas, G.; Bloemen, S.; Principe, G.; Malyshev, D.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information |
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Journal Article |
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2023 |
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Astronomy & Astrophysics |
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Astron. Astrophys. |
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680 |
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A109 - 16pp |
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methods: data analysis; techniques: image processing; astronomical databases: miscellaneous; stars: imaging; Galaxies: statistics |
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Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy. |
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[Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl |
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Edp Sciences S A |
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English |
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0004-6361 |
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WOS:001131898100001 |
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no |
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yes |
International Collaboration |
yes |
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IFIC @ pastor @ |
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5888 |
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