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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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Edp Sciences S A |
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0004-6361 |
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Notes |
WOS:000725877600001 |
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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 |
Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Bhattacharyya, S.; Caron, S.; Johannesson, G.; Ruiz de Austri, R.; van den Oetelaar, C.; Zaharijas, G.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian |
Type |
Journal Article |
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Year |
2022 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
662 |
Issue |
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Pages |
A109 - 8pp |
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Keywords |
astronomical databases; miscellaneous; methods; data analysis; stars; imaging; techniques; image processing |
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Abstract |
Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available. |
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Address |
[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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0004-6361 |
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Notes |
WOS:000818665600009 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5291 |
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| Permanent link to this record |
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Author |
Stoppa, F.; Ruiz de Austri, R.; Vreeswijk, P.; Bhattacharyya, S.; Caron, S.; Bloemen, S.; Zaharijas, G.; Principe, G.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. |
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Title |
AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation |
Type |
Journal Article |
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Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
680 |
Issue |
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Pages |
A108 - 14pp |
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Keywords |
astronomical databases: miscellaneous; methods: data analysis; stars: imaging; techniques: image processing |
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Abstract |
Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities. |
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Address |
[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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Conference |
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Notes |
WOS:001131898100003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5887 |
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| Permanent link to this record |
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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 |
Type |
Journal Article |
| |
Year |
2023 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
680 |
Issue |
|
Pages |
A109 - 16pp |
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Keywords |
methods: data analysis; techniques: image processing; astronomical databases: miscellaneous; stars: imaging; Galaxies: statistics |
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Abstract |
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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Address |
[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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ISSN |
0004-6361 |
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Conference |
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Notes |
WOS:001131898100001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5888 |
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| Permanent link to this record |
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Author |
Mendoza, S.; Olmo, G.J. |
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Title |
Astrophysical constraints and insights on extended relativistic gravity |
Type |
Journal Article |
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Year |
2015 |
Publication |
Astrophysics and Space Science |
Abbreviated Journal |
Astrophys. Space Sci. |
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Volume |
357 |
Issue |
2 |
Pages |
133 - 6pp |
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Keywords |
Gravitation; Relativistic processes; Gravitational lensing: weak |
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Abstract |
We give precise details to support that observations of gravitational lensing at scales of individual, groups and clusters of galaxies can be understood in terms of nonNewtonian gravitational interactions with a relativistic structure compatible with the Einstein Equivalence Principle. This result is derived on very general grounds without knowing the underlying structure of the gravitational field equations. As such, any developed gravitational theory built to deal with these astrophysical scales needs to reproduce the obtained results of this article. |
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Address |
[Mendoza, S.] Univ Nacl Autonoma Mexico, Inst Astron, Mexico City 04510, DF, Mexico, Email: sergio@astro.unam.mx; |
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Publisher |
Springer |
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English |
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ISSN |
0004-640x |
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Area |
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Notes |
WOS:000354392900038 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
2234 |
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Author |
Bazeia, D.; Losano, L.; Olmo, G.J.; Rubiera-Garcia, D. |
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Title |
Geodesically complete BTZ-type solutions of 2+1 Born-Infeld gravity |
Type |
Journal Article |
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Year |
2017 |
Publication |
Classical and Quantum Gravity |
Abbreviated Journal |
Class. Quantum Gravity |
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Volume |
34 |
Issue |
4 |
Pages |
045006 - 21pp |
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Keywords |
Born-Infeld gravity; BTZ; wormholes; nonsingular solutions; geodesic completeness |
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Abstract |
We study Born-Infeld gravity coupled to a static, non-rotating electric field in 2 + 1 dimensions and find exact analytical solutions. Two families of such solutions represent geodesically complete, and hence nonsingular, spacetimes. Another family represents a point-like charge with a singularity at the center. Despite the absence of rotation, these solutions resemble the charged, rotating BTZ solution of general relativity but with a richer structure in terms of horizons. The nonsingular character of the first two families turn out to be attached to the emergence of a wormhole structure on their innermost region. This seems to be a generic prediction of extensions of general relativity formulated in metric-affine (or Palatini) spaces, where metric and connection are regarded as independent degrees of freedom. |
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Address |
[Bazeia, D.; Losano, L.; Olmo, Gonzalo J.] Univ Fed Paraiba, Dept Fis, BR-58051900 Joao Pessoa, Paraiba, Brazil, Email: bazeia@fisica.ufpb.br; |
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Publisher |
Iop Publishing Ltd |
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English |
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ISSN |
0264-9381 |
ISBN |
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Area |
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Conference |
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Notes |
WOS:000395398800002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3013 |
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Author |
de Salas, P.F.; Gariazzo, S.; Mena, O.; Ternes, C.A.; Tortola, M. |
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Title |
Neutrino Mass Ordering From Oscillations and Beyond: 2018 Status and Future Prospects |
Type |
Journal Article |
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Year |
2018 |
Publication |
Frontiers in Astronomy and Space Sciences |
Abbreviated Journal |
Front. Astron. Space Sci. |
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Volume |
5 |
Issue |
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Pages |
36 - 50pp |
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Keywords |
neutrino mass ordering; neutrino oscillations; neutrinoless double beta (0v beta beta) decay; large scale structure formation; cosmic microwave Background (CMB); neutrino masses and flavor mixing |
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Abstract |
The ordering of the neutrino masses is a crucial input for a deep understanding of flavor physics, and its determination may provide the key to establish the relationship among the lepton masses and mixings and their analogous properties in the quark sector. The extraction of the neutrino mass ordering is a data-driven field expected to evolve very rapidly in the next decade. In this review, we both analyse the present status and describe the physics of subsequent prospects. Firstly, the different current available tools to measure the neutrino mass ordering are described. Namely, reactor, long-baseline (accelerator and atmospheric) neutrino beams, laboratory searches for beta and neutrinoless double beta decays and observations of the cosmic background radiation and the large scale structure of the universe are carefully reviewed. Secondly, the results from an up-to-date comprehensive global fit are reported: the Bayesian analysis to the 2018 publicly available oscillation and cosmological data sets provides strong evidence for the normal neutrino mass ordering vs. the inverted scenario, with a significance of 3.5 standard deviations. This preference for the normal neutrino mass ordering is mostly due to neutrino oscillation measurements. Finally, we shall also emphasize the future perspectives for unveiling the neutrinomass ordering. In this regard, apart from describing the expectations from the aforementioned probes, we also focus on those arising from alternative and novel methods, as 21 cm cosmology, core-collapse supernova neutrinos and the direct detection of relic neutrinos. |
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Address |
[de Salas, Pablo F.; Gariazzo, Stefano; Mena, Olga; Ternes, Christoph A.; Tortola, Mariam] Univ Valencia, CSIC, Inst Fis Corpuscular, Valencia, Spain, Email: omena@ific.uv.es |
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Frontiers Media Sa |
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English |
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ISSN |
2296-987x |
ISBN |
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Conference |
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Notes |
WOS:000446788500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3755 |
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Author |
Aliaga, R.J. |
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Title |
Real-Time Estimation of Zero Crossings of Sampled Signals for Timing Using Cubic Spline Interpolation |
Type |
Journal Article |
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Year |
2017 |
Publication |
IEEE Transactions on Nuclear Science |
Abbreviated Journal |
IEEE Trans. Nucl. Sci. |
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Volume |
64 |
Issue |
8 |
Pages |
2414-2422 |
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Keywords |
Digital arithmetic; digital circuits; digital timing; field-programmable gate array (FPGA); interpolation; signal processing algorithms; splines time estimation; time resolution |
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Abstract |
A scheme is proposed for hardware estimation of the location of zero crossings of sampled signals with subsample resolution for timing applications, which consists of interpolating the signal with a cubic spline near the zero crossing and then finding the root of the resulting polynomial. An iterative algorithm based on the bisection method is presented that obtains one bit of the result per step and admits an efficient digital implementation using fixed-point representation. In particular, the root estimation iteration involves only two additions, and the initial values can be obtained from finite impulse response (FIR) filters with certain symmetry properties. It is shown that this allows online real-time estimation of timestamps in free-running sampling detector systems with improved accuracy with respect to the more common linear interpolation. The method is evaluated with simulations using ideal and real timing signals, and estimates are given for the resource usage and speed of its implementation. |
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Address |
[Aliaga, Ramon J.] Inst Fis Corpuscular, Paterna 46980, Spain, Email: raalva@upvnet.upv.es |
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Publisher |
Ieee-Inst Electrical Electronics Engineers Inc |
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English |
Summary Language |
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Series Editor |
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ISSN |
0018-9499 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000411027700008 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
3301 |
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Author |
Carrio, F. |
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Title |
The Data Acquisition System for the ATLAS Tile Calorimeter Phase-II Upgrade Demonstrator |
Type |
Journal Article |
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Year |
2022 |
Publication |
IEEE Transactions on Nuclear Science |
Abbreviated Journal |
IEEE Trans. Nucl. Sci. |
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Volume |
69 |
Issue |
4 |
Pages |
687-695 |
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Keywords |
Large Hadron Collider; Data acquisition; Field programmable gate arrays; Clocks; Detectors; Computer architecture; Microprocessors; ATLAS tile calorimeter (TileCal); data acquisition (DAQ) systems; field-programmable gate array (FPGA); high energy physics; high-speed electronics |
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Abstract |
The tile calorimeter (TileCal) is the central hadronic calorimeter of the ATLAS experiment at the large hadron collider (LHC). In 2025, the LHC will be upgraded leading to the high luminosity LHC (HL-LHC). The HL-LHC will deliver an instantaneous luminosity up to seven times larger than the LHC nominal luminosity. The ATLAS Phase-II upgrade (2025-2027) will accommodate the subdetectors to the HL-LHC requirements. As part of this upgrade, the majority of the TileCal on-detector and off-detector electronics will be replaced using a new readout strategy, where the on-detector electronics will digitize and transmit digitized detector data to the off-detector electronics at the bunch crossing frequency (40 MHz). In the counting rooms, the off-detector electronics will compute reconstructed trigger objects for the first-level trigger and will store the digitized samples in pipelined buffers until the reception of a trigger acceptance signal. The off-detector electronics will also distribute the LHC clock to the on-detector electronics embedded within the digital data stream. The TileCal Phase-II upgrade project has undertaken an extensive research and development program that includes the development of a Demonstrator module to evaluate the performance of the new clock and readout architecture envisaged for the HL-LHC. The Demonstrator module equipped with the latest version of the on-detector electronics was built and inserted into the ATLAS experiment. The Demonstrator module is operated and read out using a Tile PreProcessor (TilePPr) Demonstrator which enables backward compatibility with the present ATLAS Trigger and Data AcQuisition (TDAQ), and the timing, trigger, and command (TTC) systems. This article describes in detail the main hardware and firmware components of the clock distribution and data acquisition systems for the Demonstrator module, focusing on the TilePPr Demonstrator. |
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Address |
[Carrio, F.] Inst Fis Corpuscular CSIC UV, Paterna 46980, Spain, Email: fernando.carrio@cern.ch |
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Ieee-Inst Electrical Electronics Engineers Inc |
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English |
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0018-9499 |
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Notes |
WOS:000803113800016 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5244 |
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Author |
Araujo Filho, A.A.; Reis, J.A.A.S.; Ghosh, S. |
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Title |
Quantum gases on a torus |
Type |
Journal Article |
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Year |
2023 |
Publication |
International Journal of Geometric Methods in Modern Physics |
Abbreviated Journal |
Int. J. Geom. Methods Mod. Phys. |
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Volume |
20 |
Issue |
10 |
Pages |
2350178 - 19pp |
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Keywords |
Thermodynamic properties; non-Cartesian geometries; grand canonical ensemble; noninteracting and interacting quantum gases; spinless; bosons and fermion particles |
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Abstract |
This paper is aimed at studying the thermodynamic properties of quantum gases confined to a torus. To do that, we consider noninteracting gases within the grand canonical ensemble formalism. In this context, fermions and bosons are taken into account and the calculations are properly provided in both analytical and numerical manners. In particular, the system turns out to be sensitive to the topological parameter under consideration: the winding number. Furthermore, we also derive a model in order to take into account interacting quantum gases. To corroborate our results, we implement such a method for two different scenarios: a ring and a torus. |
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Address |
[Araujo Filho, A. A.] Univ Fed Ceara UFC, Dept Fis, Campus Pici,CP 6030, BR-60455760 Fortaleza, CE, Brazil, Email: dilto@fisica.ufc.br; |
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Corporate Author |
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Thesis |
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Publisher |
World Scientific Publ Co Pte 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 |
0219-8878 |
ISBN |
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Medium |
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Conference |
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Notes |
WOS:000988814200003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5553 |
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