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Gammaldi, V., Zaldivar, B., Sanchez-Conde, M. A., & Coronado-Blazquez, J. (2023). A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning. Mon. Not. Roy. Astron. Soc., 520(1), 1348–1361.
Abstract: Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cantero, J., et al. (2023). A search for heavy Higgs bosons decaying into vector bosons in same-sign two-lepton final states in pp collisions at root s=13 TeV with the ATLAS detector. J. High Energy Phys., 07(7), 200–51pp.
Abstract: A search for heavy Higgs bosons produced in association with a vector boson and decaying into a pair of vector bosons is performed in final states with two leptons (electrons or muons) of the same electric charge, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb(-1). The observed data are in agreement with Standard Model background expectations. The results are interpreted using higher-dimensional operators in an effective field theory. Upper limits on the production cross-section are calculated at 95% confidence level as a function of the heavy Higgs boson's mass and coupling strengths to vector bosons. Limits are set in the Higgs boson mass range from 300 to 1500 GeV, and depend on the assumed couplings. The highest excluded mass for a heavy Higgs boson with the coupling combinations explored is 900 GeV. Limits on coupling strengths are also provided.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). A search for new resonances in multiple final states with a high transverse momentum Z boson in root s = 13 TeV pp collisions with the ATLAS detector. J. High Energy Phys., 06(6), 036–56pp.
Abstract: A generic search for resonances is performed with events containing a Z boson with transverse momentum greater than 100 GeV, decaying into e+e− or μ+μ−. The analysed data collected with the ATLAS detector in proton-proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider correspond to an integrated luminosity of 139 fb−1. Two invariant mass distributions are examined for a localised excess relative to the expected Standard Model background in six independent event categories (and their inclusive sum) to increase the sensitivity. No significant excess is observed. Exclusion limits at 95% confidence level are derived for two cases: a model-independent interpretation of Gaussian-shaped resonances with the mass width between 3% and 10% of the resonance mass, and a specific heavy vector triplet model with the decay mode W′ → ZW → ℓℓqq.
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LHCb Collaboration(Aaij, R. et al), Jaimes Elles, S. J., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Rebollo De Miguel, M., et al. (2024). A search for rare B → D μ+ μ- decays. J. High Energy Phys., 02(2), 032–23pp.
Abstract: A search for rare B. D mu+ mu- decays is performed using proton-proton collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb-1. No significant signals are observed in the non-resonant mu+ mu- modes, and upper limits of B -> B0. D0 mu+ mu- < 5.1 x 10-8, B B+. D+ s mu+ mu- -> < 3.2 x 10-8, B -> B0 s. D0 mu+ mu--> < 1.6 x 10-7 and fc/fu center dot B B+ c. D+ s mu+ mu--> < 9.6 x 10-8 are set at the 95% confidence level, where fc and fu are the fragmentation fractions of a B meson with a c and u quark respectively in proton-proton collisions. Each result is either the first such measurement or an improvement by three orders of magnitude on an existing limit. Separate upper limits are calculated when the muon pair originates from a J/.. mu+ mu- decay. The branching fraction of B+ c. D+ s J/. multiplied by the fragmentation-fraction ratio is measured to be fc fu center dot B -> B+ c. D+ s J/.-> = (1.63 +/- 0.15 +/- 0.13) x 10-5, where the first uncertainty is statistical and the second systematic.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., Castillo, F. L., et al. (2021). A search for the decays of stopped long-lived particles at root s=13 TeV with the ATLAS detector. J. High Energy Phys., 07(7), 173–49pp.
Abstract: A search for long-lived particles, which have come to rest within the ATLAS detector, is presented. The subsequent decays of these particles can produce high-momentum jets, resulting in large out-of-time energy deposits in the ATLAS calorimeters. These decays are detected using data collected during periods in the LHC bunch structure when collisions are absent. The analysed dataset is composed of events from proton-proton collisions produced by the Large Hadron Collider at a centre-of-mass energy of root s = 13TeV and recorded by the ATLAS experiment during 2017 and 2018. The dataset used for this search corresponds to a total live time of 579 hours. The results of this search are used to derive lower limits on the mass of gluino R-hadrons, assuming a branching fraction B((g) over tilde -> q (q) over bar(chi) over tilde (0)(1)) = 100%, with masses of up to 1.4TeV excluded for gluino lifetimes of 10(-5) to 10(3) s.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., Castillo, F. L., et al. (2021). A search for the dimuon decay of the Standard Model Higgs boson with the ATLAS detector. Phys. Lett. B, 812, 135980–24pp.
Abstract: A search for the dimuon decay of the Standard Model (SM) Higgs boson is performed using data corresponding to an integrated luminosity of 139 fb(-1) collected with the ATLAS detector in Run 2 pp collisions at root s = 13 TeV at the Large Hadron Collider. The observed (expected) significance over the background-only hypothesis for a Higgs boson with a mass of 125.09 GeV is 2.0 sigma (1.7 sigma). The observed upper limit on the cross section times branching ratio for pp -> H -> μμis 2.2 times the SM prediction at 95% confidence level, while the expected limit on a H -> μμsignal assuming the absence (presence) of a SM signal is 1.1(2.0). The best-fit value of the signal strength parameter, defined as the ratio of the observed signal yield to the one expected in the SM, is μ= 1.2 +/- 0.6.
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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., et al. (2020). A search for the Z gamma decay mode of the Higgs boson in pp collisions at root s=13 TeV with the ATLAS detector. Phys. Lett. B, 809, 135754–21pp.
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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LHCb Collaboration(Aaij, R. et al), Garcia Martin, L. M., Henry, L., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., et al. (2019). A search for Xi(++)(cc) -> D(+)pK(-)pi(+) decays. J. High Energy Phys., 10(10), 124–21pp.
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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n_TOF Collaboration(Alcayne, V. et al), Balibrea-Correa, J., Domingo-Pardo, C., Lerendegui-Marco, J., Babiano-Suarez, V., & Ladarescu, I. (2024). A Segmented Total Energy Detector (sTED) optimized for (n,γ) cross-section measurements at n_TOF EAR2. Radiat. Phys. Chem., 217, 11pp.
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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Herrero-Garcia, J., Patrick, R., & Scaffidi, A. (2022). A semi-supervised approach to dark matter searches in direct detection data with machine learning. J. Cosmol. Astropart. Phys., 02, 039–19pp.
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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