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Author |
Plenter, J.; Rodrigo, G. |
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Title  |
Asymptotic expansions through the loop-tree duality |
Type |
Journal Article |
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Year |
2021 |
Publication |
European Physical Journal C |
Abbreviated Journal |
Eur. Phys. J. C |
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Volume |
81 |
Issue |
4 |
Pages |
320 - 13pp |
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Keywords |
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Abstract |
Asymptotic expansions of Feynman amplitudes in the loop-tree duality formalism are implemented at integrand-level in the Euclidean space of the loop three-momentum, where the hierarchies among internal and external scales are well-defined. The ultraviolet behaviour of the individual contributions to the asymptotic expansion emerges only in the first terms of the expansion and is renormalized locally in four space-time dimensions. These two properties represent an advantage over the method of Expansion by Regions. We explore different approaches in different kinematical limits, and derive explicit asymptotic expressions for several benchmark configurations. |
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Address |
[Plenter, Judith; Rodrigo, German] Univ Valencia, Inst Fis Corpuscular, CSIC, Parc Cient, Valencia 46980, Spain, Email: plenter@ific.uv.es; |
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Publisher |
Springer |
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English |
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ISSN |
1434-6044 |
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Conference |
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Notes |
WOS:000641475900003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4810 |
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Author |
ATLAS Collaboration (Aad, G. et al); Alvarez Piqueras, D.; Aparisi Pozo, J.A.; Bailey, A.J.; Cabrera Urban, S.; Castillo, F.L.; Castillo Gimenez, V.; Cerda Alberich, L.; Costa, M.J.; Escobar, C.; Estrada Pastor, O.; Ferrer, A.; Fiorini, L.; Fullana Torregrosa, E.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Gonzalvo Rodriguez, G.R.; Guerrero Rojas, J.G.R.; Higon-Rodriguez, E.; Lacasta, C.; Lozano Bahilo, J.J.; Madaffari, D.; Mamuzic, J.; Marti-Garcia, S.; Melini, D.; Miñano, M.; Mitsou, V.A.; Rodriguez Bosca, S.; Rodriguez Rodriguez, D.; Ruiz-Martinez, A.; Salt, J.; Santra, A.; Soldevila, U.; Sanchez, J.; Valero, A.; Valls Ferrer, J.A.; Vos, M. |
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Title |
ATLAS b-jet identification performance and efficiency measurement with t(t)over-bar events in pp collisions at root s=13 TeV |
Type |
Journal Article |
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Year |
2019 |
Publication |
European Physical Journal C |
Abbreviated Journal |
Eur. Phys. J. C |
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Volume |
79 |
Issue |
11 |
Pages |
970 - 36pp |
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Keywords |
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Abstract |
The algorithms used by the ATLAS Collaboration during Run 2 of the Large Hadron Collider to identify jets containing b-hadrons are presented. The performance of the algorithms is evaluated in the simulation and the efficiency with which these algorithms identify jets containing b-hadrons is measured in collision data. The measurement uses a likelihood-based method in a sample highly enriched in t (t) over bar events. The topology of the t -> Wb decays is exploited to simultaneously measure both the jet flavour composition of the sample and the efficiency in a transverse momentum range from 20 to 600 GeV. The efficiency measurement is subsequently compared with that predicted by the simulation. The data used in this measurement, corresponding to a total integrated luminosity of 80.5 fb(-1), were collected in proton-proton collisions during the years 2015-2017 at a centre-of-mass energy root s = 13 TeV. By simultaneously extracting both the efficiency and jet flavour composition, this measurement significantly improves the precision compared to previous results, with uncertainties ranging from 1 to 8% depending on the jet transverse momentum. |
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Address |
[Deliot, F.; Duvnjak, D.; Jackson, P.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia |
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Publisher |
Springer |
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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 |
1434-6044 |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000505550300004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4251 |
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Author |
ATLAS Collaboration (Aad, G. et al); Aparisi Pozo, J.A.; Bailey, A.J.; Barranco Navarro, L.; Cabrera Urban, S.; Castillo, F.L.; Castillo Gimenez, V.; Cerda Alberich, L.; Costa, M.J.; Escobar, C.; Estrada Pastor, O.; Ferrer, A.; Fiorini, L.; Fullana Torregrosa, E.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Gonzalvo Rodriguez, G.R.; Guerrero Rojas, J.G.; Higon-Rodriguez, E.; Jimenez Pena, J.; Lacasta, C.; Lozano Bahilo, J.J.; Madaffari, D.; Mamuzic, J.; Marti-Garcia, S.; Melini, D.; Miñano, M.; Mitsou, V.A.; Moreno Llacer, M.; Rodriguez Bosca, S.; Rodriguez Rodriguez, D.; Ruiz-Martinez, A.; Salt, J.; Santra, A.; Soldevila, U.; Sanchez, J.; Valero, A.; Valls Ferrer, J.A.; Vos, M. |
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Title |
ATLAS data quality operations and performance for 2015-2018 data-taking |
Type |
Journal Article |
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Year |
2020 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
15 |
Issue |
4 |
Pages |
P04003 - 43pp |
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Keywords |
Large detector systems for particle and astroparticle physics; Large detector-systems performance |
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Abstract |
The ATLAS detector at the Large Hadron Collider reads out particle collision data from over 100 million electronic channels at a rate of approximately 100 kHz, with a recording rate for physics events of approximately 1 kHz. Before being certified for physics analysis at computer centres worldwide, the data must be scrutinised to ensure they are clean from any hardware or software related issues that may compromise their integrity. Prompt identification of these issues permits fast action to investigate, correct and potentially prevent future such problems that could render the data unusable. This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain. This paper presents the monitoring and assessment procedures in place at ATLAS during 2015-2018 data-taking. Through the continuous improvement of operational procedures, ATLAS achieved a high data quality efficiency, with 95.6% of the recorded proton-proton collision data collected at root s = 13 TeV certified for physics analysis. |
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Address |
[Banerjee, S.; Dang, N. P.; Duvnjak, D.; Jackson, P.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia |
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Publisher |
Iop Publishing Ltd |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000534740000003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4402 |
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Author |
ATLAS Collaboration (Aad, G. et al); Amos, K.R.; Aparisi Pozo, J.A.; Bailey, A.J.; Bouchhar, N.; Cabrera Urban, S.; Cantero, J.; Cardillo, F.; Castillo Gimenez, V.; Chitishvili, M.; Costa, M.J.; Didenko,, M.; Escobar, C.; Fiorini, L.; Fullana Torregrosa, E.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gomez Delegido, A.J.; Gonzalez de la Hoz, S.; Gonzalvo Rodriguez, G.R.; Guerrero Rojas, J.G.R.; Lacasta, C.; Lozano Bahilo, J.J.; Marti-Garcia, S.; Martinez Agullo, P.; Miralles Lopez, M.; Mitsou, V.A.; Monsonis Romero, L.; Moreno Llacer, M.; Munoz Perez, D.; Navarro-Gonzalez, J.; Poveda, J.; Prades Ibañez, A.; Rubio Jimenez, A.; Ruiz-Martinez, A.; Sabatini, P.; Salt, J.; Sanchez Sebastian, V.; Sayago Galvan, I.; Senthilkumar, V.; Soldevila, U.; Sanchez, J.; Torro Pastor, E.; Valero, A.; Valls Ferrer, J.A.; Varriale, L.; Villaplana Perez, M.; Vos, M. |
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Title |
ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset |
Type |
Journal Article |
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Year |
2023 |
Publication |
European Physical Journal C |
Abbreviated Journal |
Eur. Phys. J. C |
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Volume |
83 |
Issue |
7 |
Pages |
681 - 37pp |
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Keywords |
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Abstract |
The flavour-tagging algorithms developed by the AvTLAS Collaboration and used to analyse its dataset of root s = 13 TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% b-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model t (t) over bar events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained. |
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Address |
[Filmer, E. K.; Jackson, P.; Kong, A. X. Y.; Potti, H.; Ruggeri, T. A.; Ting, E. X. L.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia |
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Thesis |
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Publisher |
Springer |
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 |
1434-6044 |
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:001062397400001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5675 |
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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 |
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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 |
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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Corporate Author |
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Thesis |
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Publisher |
Edp Sciences S A |
Place of Publication |
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Language |
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 |
0004-6361 |
ISBN |
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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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