Records |
Author |
Binosi, D.; Chang, L.; Ding, M.H.; Gao, F.; Papavassiliou, J.; Roberts, C.D. |
Title |
Distribution amplitudes of heavy-light mesons |
Type |
Journal Article |
Year |
2019 |
Publication |
Physics Letters B |
Abbreviated Journal |
Phys. Lett. B |
Volume |
790 |
Issue |
|
Pages |
257-262 |
Keywords |
B-meson decays; Heavy-light mesons; Nonperturbative continuum methods in quantum field theory; Parton distribution amplitudes; Quantum chromodynamics |
Abstract ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
A symmetry-preserving approach to the continuum bound-state problem in quantum field theory is used to calculate the masses, leptonic decay constants and light-front distribution amplitudes of empirically accessible heavy-light mesons. The inverse moment of the B-meson distribution is particularly important in treatments of exclusive B-decays using effective field theory and the factorisation formalism; and its value is therefore computed: lambda(B) = (zeta = 2GeV) = 0.54(3) GeV. As an example and in anticipation of precision measurements at new-generation B-factories, the branching fraction for the rare B -> gamma (E-gamma)l nu(l) radiative decay is also calculated, retaining 1/m(B)(2), and 1/E-gamma(2) corrections to the differential decay width, with the result Gamma(B -> gamma l nu l) /Gamma(B) = 0.47 (15) on E-gamma > 1.5 GeV. |
Address |
[Binosi, Daniele; Ding, Minghui] European Ctr Theoret Studies Nucl Phys & Related, Str Tabarelle 286, I-38123 Villazzano, TN, Italy, Email: binosi@ectstar.eu; |
Corporate Author |
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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 |
0370-2693 |
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:000460118200030 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
3934 |
Permanent link to this record |
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Author |
Kasieczka, G. et al; Sanz, V. |
Title |
The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics |
Type |
Journal Article |
Year |
2021 |
Publication |
Reports on Progress in Physics |
Abbreviated Journal |
Rep. Prog. Phys. |
Volume |
84 |
Issue |
12 |
Pages |
124201 - 64pp |
Keywords |
anomaly detection; machine learning; unsupervised learning; weakly supervised learning; semisupervised learning; beyond the standard model; model-agnostic methods |
Abstract ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders. |
Address |
[Kasieczka, Gregor] Univ Hamburg, Inst Expt Phys, Hamburg, Germany, Email: gregor.kasieczka@uni-hamburg.de; |
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 |
0034-4885 |
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:000727698500001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5039 |
Permanent link to this record |
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Author |
ATLAS Collaboration (Abat, E. et al); Bernabeu Verdu, J.; Castillo Gimenez, V.; Costa, M.J.; Escobar, C.; Ferrer, A.; Garcia, C.; Gonzalez-Sevilla, S.; Higon-Rodriguez, E.; Lacasta, C.; Marti-Garcia, S.; Mitsou, V.A.; Ruiz, A.; Solans, C.; Valero, A.; Valls Ferrer, J.A. |
Title |
A layer correlation technique for pion energy calibration at the 2004 ATLAS Combined Beam Test |
Type |
Journal Article |
Year |
2011 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
Volume |
6 |
Issue |
|
Pages |
P06001 - 35pp |
Keywords |
Calorimeter methods; Pattern recognition, cluster finding, calibration and fitting methods; Calorimeters; Detector modelling and simulations I (interaction of radiation with matter, interaction of photons with matter, interaction of hadrons with matter, etc) |
Abstract ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
A new method for calibrating the hadron response of a segmented calorimeter is developed and successfully applied to beam test data. It is based on a principal component analysis of energy deposits in the calorimeter layers, exploiting longitudinal shower development information to improve the measured energy resolution. Corrections for invisible hadronic energy and energy lost in dead material in front of and between the calorimeters of the ATLAS experiment were calculated with simulated Geant4 Monte Carlo events and used to reconstruct the energy of pions impinging on the calorimeters during the 2004 Barrel Combined Beam Test at the CERN H8 area. For pion beams with energies between 20 GeV and 180 GeV, the particle energy is reconstructed within 3% and the energy resolution is improved by between 11% and 25% compared to the resolution at the electromagnetic scale. |
Address |
[Wheeler, S] Univ Alberta, Dept Phys, Ctr Particle Phys, Edmonton, AB T6G 2G7, Canada[Bernabeu, J; Castillo, MV; Costa, MJ; Escobar, C; Ferrer, A; Garcia, C; Gonzalez-Sevilla, S; Higon, E; Lacasta, C; Garcia, SMI; Mitsou, VA; Ruiz, A; Solans, C; Valero, A; Valls, JA] Ctr Mixto UVEG CSIC, Inst Fis Corpuscular IFIC, ES-46071 Valencia, Spain, Email: kjg@particle.kth.se |
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 |
|
Notes |
WOS:000294492600001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ elepoucu @ |
Serial |
744 |
Permanent link to this record |
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Author |
LHCb Collaboration (Aaij, R. et al); Martinez-Vidal, F.; Oyanguren, A.; Ruiz Valls, P.; Sanchez Mayordomo, C. |
Title |
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 ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
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 |
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:000377851700033 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
2731 |
Permanent link to this record |
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Author |
CALICE Collaboration (Lai, S. et al); Irles, A. |
Title |
Software compensation for highly granular calorimeters using machine learning |
Type |
Journal Article |
Year |
2024 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
Volume |
19 |
Issue |
4 |
Pages |
P04037 - 28pp |
Keywords |
Large detector-systems performance; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors |
Abstract ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied. |
Address |
[Lai, S.; Utehs, J.; Wilhahn, A.] Georg August Univ Gottingen, Phys Inst 2, Friedrich Hund Pl 1, D-37077 Gottingen, Germany, Email: jack.rolph@desy.de |
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:001230094600001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
6128 |
Permanent link to this record |