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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). Measurement of Suppression of Large-Radius Jets and Its Dependence on Substructure in Pb plus Pb Collisions at √sNN=5.02 TeV with the ATLAS Detector. Phys. Rev. Lett., 131(17), 172301–22pp.
Abstract: This letter presents a measurement of the nuclear modification factor of large-radius jets in root s(NN) = 5.02 TeV Pb thorn Pb collisions by the ATLAS experiment. The measurement is performed using 1.72 nb(-1) and 257 pb(-1) of Pb thorn Pb and pp data, respectively. The large-radius jets are reconstructed with the anti-kt algorithm using a radius parameter of R = 1.0, by reclustering anti-k(t) R = 0.2 jets, and are measured over the transverse momentum (p(T)) kinematic range of 158 < p(T) < 1000 GeV and absolute pseudorapidity |y| < 2.0. The large-radius jet constituents are further reclustered using the k(t) algorithm in order to obtain the splitting parameters, root d(12) and Delta R-12, which characterize the transverse momentum scale and angular separation for the hardest splitting in the jet, respectively. The nuclear modification factor, R-AA, obtained by comparing the Pb thorn Pb jet yields to those in pp collisions, is measured as a function of jet transverse momentum (p(T)) and root d(12) or Delta R-12. A significant difference in the quenching of large-radius jets having single subjet and those with more complex substructure is observed. Systematic comparison of jet suppression in terms of R-AA for different jet definitions is also provided. Presented results support the hypothesis that jets with hard internal splittings lose more energy through quenching and provide a new perspective for understanding the role of jet structure in jet suppression.
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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. (2023). Search for Rare Decays of D0 Mesons into Two Muons. Phys. Rev. Lett., 131(4), 041804–13pp.
Abstract: A search for the very rare D-0 -> mu(+)mu(-) decay is performed using data collected by the LHCb experiment in proton-proton collisions at root s = 7, 8, and 13 TeV, corresponding to an integrated luminosity of 9 fb(-1). The search is optimized for D-0 mesons from D*(+) -> D-0 pi(+) decays but is also sensitive to D-0 mesons from other sources. No evidence for an excess of events over the expected background is observed. An upper limit on the branching fraction of this decay is set at B(D-0 -> mu(+)mu(-)) < 3.1 x 10(-9) at a 90% C.L. This represents the world's most stringent limit, constraining models of physics beyond the standard model.
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Borja-Lloret, M., Barrientos, L., Bernabeu, J., Lacasta, C., Muñoz, E., Ros, A., et al. (2023). Influence of the background in Compton camera images for proton therapy treatment monitoring. Phys. Med. Biol., 68(14), 144001–16pp.
Abstract: Objective. Background events are one of the most relevant contributions to image degradation in Compton camera imaging for hadron therapy treatment monitoring. A study of the background and its contribution to image degradation is important to define future strategies to reduce the background in the system. Approach. In this simulation study, the percentage of different kinds of events and their contribution to the reconstructed image in a two-layer Compton camera have been evaluated. To this end, GATE v8.2 simulations of a proton beam impinging on a PMMA phantom have been carried out, for different proton beam energies and at different beam intensities. Main results. For a simulated Compton camera made of Lanthanum (III) Bromide monolithic crystals, coincidences caused by neutrons arriving from the phantom are the most common type of background produced by secondary radiations in the Compton camera, causing between 13% and 33% of the detected coincidences, depending on the beam energy. Results also show that random coincidences are a significant cause of image degradation at high beam intensities, and their influence in the reconstructed images is studied for values of the time coincidence windows from 500 ps to 100 ns. Significance. Results indicate the timing capabilities required to retrieve the fall-off position with good precision. Still, the noise observed in the image when no randoms are considered make us consider further background rejection methods.
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Brzezinski, K. et al. (2023). Detection of range shifts in proton beam therapy using the J-PET scanner: a patient simulation study. Phys. Med. Biol., 68(14), 145016–17pp.
Abstract: Objective. The Jagiellonian positron emission tomography (J-PET) technology, based on plastic scintillators, has been proposed as a cost effective tool for detecting range deviations during proton therapy. This study investigates the feasibility of using J-PET for range monitoring by means of a detailed Monte Carlo simulation study of 95 patients who underwent proton therapy at the Cyclotron Centre Bronowice (CCB) in Krakow, Poland. Approach. Discrepancies between prescribed and delivered treatments were artificially introduced in the simulations by means of shifts in patient positioning and in the Hounsfield unit to the relative proton stopping power calibration curve. A dual-layer, cylindrical J-PET geometry was simulated in an in-room monitoring scenario and a triple-layer, dual-head geometry in an in-beam protocol. The distribution of range shifts in reconstructed PET activity was visualized in the beam's eye view. Linear prediction models were constructed from all patients in the cohort, using the mean shift in reconstructed PET activity as a predictor of the mean proton range deviation. Main results. Maps of deviations in the range of reconstructed PET distributions showed agreement with those of deviations in dose range in most patients. The linear prediction model showed a good fit, with coefficient of determination r (2) = 0.84 (in-room) and 0.75 (in-beam). Residual standard error was below 1 mm: 0.33 mm (in-room) and 0.23 mm (in-beam). Significance. The precision of the proposed prediction models shows the sensitivity of the proposed J-PET scanners to shifts in proton range for a wide range of clinical treatment plans. Furthermore, it motivates the use of such models as a tool for predicting proton range deviations and opens up new prospects for investigations into the use of intra-treatment PET images for predicting clinical metrics that aid in the assessment of the quality of delivered treatment.
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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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