| Records |
| Author |
LHCb Collaboration (Aaij, R. et al); Jaimes Elles, S.J.; Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Rebollo De Miguel, M.; Sanderswood, I.; Zhuo, J. |
| Title |
Curvature-bias corrections using a pseudomass method |
Type |
Journal Article |
| Year |
2024 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
19 |
Issue |
3 |
Pages |
P03010 - 22pp |
Keywords  |
Analysis and statistical methods; Detector alignment and calibration methods (lasers, sources, particle-beams); Large detector-systems performance; Performance of High Energy Physics Detectors |
| Abstract |
Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additional approaches are therefore required to understand and correct for these effects. In this paper the curvature biases present at the LHCb detector are studied using the pseudomass method in proton-proton collision data recorded at centre of mass energy root s = 13 TeV during 2016, 2017 and 2018. The biases are determined using Z -> mu(+)mu(-) decays in intervals defined by the data-taking period, magnet polarity and muon direction. Correcting for these biases, which are typically at the 10(-4) GeV-1 level, improves the Z -> mu(+)mu(-) mass resolution by roughly 18% and eliminates several pathological trends in the kinematic-dependence of the mean dimuon invariant mass. |
| Address |
[Egede, U.; Fujii, Y.; Hadavizadeh, T.; Henderson, R. D. L.; Lane, J. J.; Monk, M.; Song, R.; Walton, E. J.; Ward, J. A.] Monash Univ, Sch Phys & Astron, Melbourne, Vic, Australia, Email: seophine.stanislaus@cern.ch |
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Thesis |
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| Publisher |
IOP Publishing Ltd |
Place of Publication |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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| Series 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:001190907900003 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
6057 |
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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.; 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.; Higon-Rodriguez, E.; 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. |
| Title |
Tools for estimating fake/non-prompt lepton backgrounds with the ATLAS detector at the LHC |
Type |
Journal Article |
| Year |
2023 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
18 |
Issue |
11 |
Pages |
T11004 - 61pp |
| Keywords |
Analysis and statistical methods; Particle identification methods |
| Abstract |
Measurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to 'fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance. |
| Address |
[Amerl, M.; 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 |
IOP Publishing Ltd |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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| Series 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:001116977400001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5884 |
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| Author |
LHCb Collaboration (Aaij, R. et al); Martinez-Vidal, F.; Oyanguren, A.; Ruiz Valls, P.; Sanchez Mayordomo, C. |
| Title |
A new algorithm for identifying the flavour of B-s(0) mesons at LHCb |
Type |
Journal Article |
| Year |
2016 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
| Volume |
11 |
Issue |
|
Pages |
P05010 - 23pp |
| Keywords |
Analysis and statistical methods; Particle identification methods; Pattern recognition; cluster finding; calibration and fitting methods |
| Abstract |
A new algorithm for the determination of the initial flavour of B-s(0) mesons is presented. The algorithm is based on two neural networks and exploits the b hadron production mechanism at a hadron collider. The first network is trained to select charged kaons produced in association with the B-s(0) meson. The second network combines the kaon charges to assign the B-s(0) flavour and estimates the probability of a wrong assignment. The algorithm is calibrated using data corresponding to an integrated luminosity of 3 fb(-1) collected by the LHCb experiment in proton-proton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the B-s(0)-B-s(0) flavour oscillations in B-s(0) -> D-s(-)pi(+) decays, and by analysing flavour-specific B-s2*(5840)(0) -> B+K- decays. The tagging power measured in B-s(0) -> D-s(-)pi(+) decays is found to be (1.80 +/- 0.19 ( stat) +/- 0.18 (syst))%, which is an improvement of about 50% compared to a similar algorithm previously used in the LHCb experiment. |
| Address |
[Bediaga, I.; De Miranda, J. M.; Rodrigues, F. Ferreira; Gomes, A.; Massafferri, A.; Rodrigues, B. Osorio; dos Reis, A. C.; Rodrigues, A. B.] CBPF, Rio De Janeiro, Brazil, Email: mirco.dorigo@cern.ch |
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Thesis |
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| Publisher |
Iop Publishing Ltd |
Place of Publication |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1748-0221 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
WOS:000377851700033 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
2731 |
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| Author |
Hirn, J.; Garcia, J.E.; Montesinos-Navarro, A.; Sanchez-Martin, R.; Sanz, V.; Verdu, M. |
| Title |
A deep Generative Artificial Intelligence system to predict species coexistence patterns |
Type |
Journal Article |
| Year |
2022 |
Publication |
Methods in Ecology and Evolution |
Abbreviated Journal |
Methods Ecol. Evol. |
| Volume |
13 |
Issue |
|
Pages |
1052-1061 |
| Keywords |
artificial intelligence; direct interactions; generative adversarial networks; indirect interactions; species coexistence; variational AutoEncoders |
| Abstract |
Predicting coexistence patterns is a current challenge to understand diversity maintenance, especially in rich communities where these patterns' complexity is magnified through indirect interactions that prevent their approximation with classical experimental approaches. We explore cutting-edge Machine Learning techniques called Generative Artificial Intelligence (GenAI) to predict species coexistence patterns in vegetation patches, training generative adversarial networks (GAN) and variational AutoEncoders (VAE) that are then used to unravel some of the mechanisms behind community assemblage. The GAN accurately reproduces real patches' species composition and plant species' affinity to different soil types, and the VAE also reaches a high level of accuracy, above 99%. Using the artificially generated patches, we found that high-order interactions tend to suppress the positive effects of low-order interactions. Finally, by reconstructing successional trajectories, we could identify the pioneer species with larger potential to generate a high diversity of distinct patches in terms of species composition. Understanding the complexity of species coexistence patterns in diverse ecological communities requires new approaches beyond heuristic rules. Generative Artificial Intelligence can be a powerful tool to this end as it allows to overcome the inherent dimensionality of this challenge. |
| Address |
[Hirn, Johannes; Enrique Garcia, Jose; Sanz, Veronica] Univ Valencia, CSIC, Inst Fis Corpuscular IFIC, Valencia, Spain, Email: miguel.verdu@ext.uv.es |
| Corporate Author |
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Thesis |
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| Publisher |
Wiley |
Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
2041-210x |
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:000765239700001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5155 |
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| Author |
Capra, S.; Mengoni, D.; Dueñas, J.A.; John, P.R.; Gadea, A.; Aliaga, R.J.; Dormard, J.J.; Assie, M.; Pullia, A. |
| Title |
Performance of the new integrated front-end electronics of the TRACE array commissioned with an early silicon detector prototype |
Type |
Journal Article |
| Year |
2019 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
| Volume |
935 |
Issue |
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Pages |
178-184 |
| Keywords |
ASIC; Charge-sensitive preamplifier; Low-noise applications; Particle spectrometry; Dead time; Silicon detector |
| Abstract |
The spectroscopic performances of the new integrated ASIC (Application-Specific Integrated Circuit) preamplifiers for highly segmented silicon detectors have been evaluated with an early silicon detector prototype of the TRacking Array for light Charged Ejectiles (TRACE). The ASICS were mounted on a custom-designed PCB (Printed Circuit Board) and the detector plugged on it. Energy resolution tests, performed on the same detector before and after irradiation, yielded a resolution of 21 keV and 33 keV FWHM respectively. The output signals were acquired with an array of commercial 100-MHz 14-bit digitizers. The preamplifier chip is equipped with an innovative Fast-Reset device that has two functions: it reduces dramatically the dead time of the preamplifier in case of saturation (from milliseconds to microseconds) and extends the spectroscopic dynamic range of the preamplifier by more than one order of magnitude. Other key points of the device are the low noise and the wide bandwidth. |
| Address |
[Capra, S.; Pullia, A.] Univ Milan, Dipartimento Fis, Via Celoria 16, IT-20133 Milan, Italy, Email: stefano.capra@unimi.it |
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Thesis |
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| Publisher |
Elsevier Science Bv |
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 |
0168-9002 |
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:000470063800026 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
4042 |
| Permanent link to this record |
