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ATLAS Collaboration (Aad, G. et al); Alvarez Piqueras, D.; 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.; 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.; 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  |
A search for the Z gamma decay mode of the Higgs boson in pp collisions at root s=13 TeV with the ATLAS detector |
Type |
Journal Article |
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Year |
2020 |
Publication |
Physics Letters B |
Abbreviated Journal |
Phys. Lett. B |
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Volume |
809 |
Issue |
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Pages |
135754 - 21pp |
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Abstract |
A search for the Z gamma decay of the Higgs boson, with Z boson decays into pairs of electrons or muons is presented. The analysis uses proton-proton collision data at root s = 13 TeV corresponding to an integrated luminosity of 139 fb(-1) recorded by the ATLAS detector at the Large Hadron Collider. The observed data are consistent with the expected background with a p-value of 1.3%. An upper limit at 95% confidence level on the production cross-section times the branching ratio for pp -> H -> Z gamma is set at 3.6 times the Standard Model prediction while 2.6 times is expected in the presence of the Standard Model Higgs boson. The best-fit value for the signal yield normalised to the Standard Model prediction is 2.0(-0.9)(+1.0) where the statistical component of the uncertainty is dominant. |
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Address |
[Duvnjak, D.; Jackson, P.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia, Email: atlas.publications@cern.ch |
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Elsevier |
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English |
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ISSN |
0370-2693 |
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Notes |
WOS:000581871500054 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4600 |
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Author |
LHCb Collaboration (Aaij, R. et al); Garcia Martin, L.M.; Henry, L.; Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J.; Sanchez Mayordomo, C. |
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Title |
A search for Xi(++)(cc) -> D(+)pK(-)pi(+) decays |
Type |
Journal Article |
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Year |
2019 |
Publication |
Journal of High Energy Physics |
Abbreviated Journal |
J. High Energy Phys. |
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Volume |
10 |
Issue |
10 |
Pages |
124 - 21pp |
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Keywords |
Branching fraction; Charm physics; Hadron-Hadron scattering (experiments) |
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Abstract |
A search for the Xi(++)(cc) baryon through the Xi(++)(cc) -> D(+)pK(-)pi(+) decay is performed with a data sample corresponding to an integrated luminosity of 1.7 fb(-1) recorded by the LHCb experiment in pp collisions at a centre-of-mass energy of 13 TeV. No significant signal is observed in the mass range from the kinematic threshold of the decay to 3800 MeV/c(2). An upper limit is set on the ratio of branching fractions R = B(Xi(++)(cc) -> D(+)pK(-)pi(+))/B(Xi(++)(cc) -> A(c)(+) K- pi(+)pi(+)) with R < 1.7 (2.1) x 10(-2) at the 90% (95%) confidence level at the known mass of the Xi(++)(cc) state. |
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Address |
[Bediaga, I.; Cruz Torres, M.; De Miranda, J. M.; Gomes, A.; Massafferri, A.; dos Reis, A. C.; Soares Lavra, l.; Jadallah Aoude, R. Tourinho] Ctr Brasileiro Pesquisas Fis CBPF, Rio De Janeiro, Brazil, Email: alberto.correa.dos.reis@cern.ch |
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Springer |
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English |
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ISSN |
1029-8479 |
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Notes |
WOS:000509341600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4290 |
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Author |
n_TOF Collaboration (Alcayne, V. et al); Balibrea-Correa, J.; Domingo-Pardo, C.; Lerendegui-Marco, J.; Babiano-Suarez, V.; Ladarescu, I. |
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Title |
A Segmented Total Energy Detector (sTED) optimized for (n,γ) cross-section measurements at n_TOF EAR2 |
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Journal Article |
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Year |
2024 |
Publication |
Radiation Physics and Chemistry |
Abbreviated Journal |
Radiat. Phys. Chem. |
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Volume |
217 |
Issue |
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Pages |
11pp |
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Keywords |
Neutron capture; PHWT; Scintillation detectors; Monte Carlo simulation |
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Abstract |
The neutron time-of-flight facility nTOF at CERN is a spallation source dedicated to measurements of neutroninduced reaction cross-sections of interest in nuclear technologies, astrophysics, and other applications. Since 2014, Experimental ARea 2 (EAR2) is operational and delivers a neutron fluence of similar to 4 center dot 10(7) neutrons per nominal proton pulse, which is similar to 50 times higher than the one of Experimental ARea 1 (EAR1) of similar to 8 center dot 10(5) neutrons per pulse. The high neutron flux at EAR2 results in high counting rates in the detectors that challenged the previously existing capture detection systems. For this reason, a Segmented Total Energy Detector (sTED) has been developed to overcome the limitations in the detector's response, by reducing the active volume per module and by using a photo-multiplier (PMT) optimized for high counting rates. This paper presents the main characteristics of the sTED, including energy and time resolution, response to gamma-rays, and provides as well details of the use of the Pulse Height Weighting Technique (PHWT) with this detector. The sTED has been validated to perform neutron-capture cross-section measurements in EAR2 in the neutron energy range from thermal up to at least 400 keV. The detector has already been successfully used in several measurements at nTOF EAR2. |
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Address |
[Alcayne, V.; Cano-Ott, D.; Garcia, J.; Gonzalez-Romero, E.; Martinez, T.; de Rada, A. Perez; Plaza, J.; Sanchez-Caballero, A.; Mendoza, E.] Ctr Invest Energet Medioambient & Tecnol CIEMAT, Madrid, Spain, Email: victor.alcayne@ciemat.es |
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Pergamon-Elsevier Science Ltd |
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English |
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ISSN |
0969-806x |
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Notes |
WOS:001185584800001 |
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no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5999 |
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Author |
Herrero-Garcia, J.; Patrick, R.; Scaffidi, A. |
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Title |
A semi-supervised approach to dark matter searches in direct detection data with machine learning |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
02 |
Issue |
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Pages |
039 - 19pp |
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Abstract |
The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods. |
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Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5495 |
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Author |
Khosa, C.K.; Sanz, V.; Soughton, M. |
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Title |
A simple guide from machine learning outputs to statistical criteria in particle physics |
Type |
Journal Article |
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Year |
2022 |
Publication |
Scipost Physics Core |
Abbreviated Journal |
SciPost Phys. Core |
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Volume |
5 |
Issue |
4 |
Pages |
050 - 31pp |
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Abstract |
In this paper we propose ways to incorporate Machine Learning training outputs into a study of statistical significance. We describe these methods in supervised classification tasks using a CNN and a DNN output, and unsupervised learning based on a VAE. As use cases, we consider two physical situations where Machine Learning are often used: high-pT hadronic activity, and boosted Higgs in association with a massive vector boson. |
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Address |
[Khosa, Charanjit Kaur] Univ Bristol, HH Wills Phys Lab, Tyndall Ave, Bristol BS8 1TL, Avon, England, Email: Charanjit.Kaur@bristol.ac.uk; |
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Scipost Foundation |
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English |
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WOS:000929724800002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5475 |
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