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Phong, V. H. et al, Agramunt, J., Algora, A., Domingo-Pardo, C., Morales, A. I., Rubio, B., et al. (2022). Beta-Delayed One and Two Neutron Emission Probabilities South-East of Sn-132 and the Odd-Even Systematics in r-Process Nuclide Abundances. Phys. Rev. Lett., 129(18), 172701–7pp.
Abstract: The beta-delayed one- and two-neutron emission probabilities (P-1n and P-2n) of 20 neutron-rich nuclei with N >= 82 have been measured at the RIBF facility of the RIKEN Nishina Center. P-1n of Ag-130;131, Cd-133;134, In-135;136, and (138;13)9Sn were determined for the first time, and stringent upper limits were placed on P-2n for nearly all cases. beta-delayed two-neutron emission (beta 2n) was unambiguously identified in Cd-133 and In-135;136, and their P-2n were measured. Weak beta 2n was also detected from Sn-137;138. Our results highlight the effect of the N = 82 and Z = 50 shell closures on beta-delayed neutron emission probability and provide stringent benchmarks for newly developed macroscopic-microscopic and self-consistent global models with the inclusion of a statistical treatment of neutron and. emission. The impact of our measurements on r-process nucleosynthesis was studied in a neutron star merger scenario. Our P-1n and P-2n have a direct impact on the
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Analysis of Neutral B-Meson Decays into Two Muons. Phys. Rev. Lett., 128(4), 041801–13pp.
Abstract: The branching fraction B(B-s(0)->mu(+)mu(-)) = (3.09(-0.43-0.11)(+0.46+0.15)) x 10(-9) and the effective lifetime to tau(B-s(0) -> mu(+)mu(-)) = 2.07 +/- 0.29 +/- 0.03 ps are measured, where the first uncertainty is statistical and the second systematic. No significant signal for B-0 ->mu(+)mu(-)gamma) and B-s(0)->mu(+)mu(-)gamma decays is found and upper limits B(B(B-0 ->mu(+)mu(-)) < 2.6 x 10(-10) and B(B-s(0) -> mu(+)mu(-)gamma) < 2.0 x 10(-9) at the 95% C.L. are determined, where the latter is limited to the range m(mu mu) > 4.9 GeV/c(2). The results are in agreement with the standard model expectations.Branching fraction and effective lifetime measurements of the rare decay B-s(0) -> mu(+)mu(-) and searches for the decays B-0 -> mu(+)mu(-) and B-s(0) -> mu(+)mu(-)gamma are reported using proton-proton collision data collected with the LHCb detector at center-of-mass energies of 7, 8, and 13 TeV, corresponding to a luminosity of 9 fb(-1).
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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2022). Centrality determination in heavy-ion collisions with the LHCb detector. J. Instrum., 17(5), P05009–31pp.
Abstract: The centrality of heavy-ion collisions is directly related to the created medium in these interactions. A procedure to determine the centrality of collisions with the LHCb detector is implemented for lead-lead collisions root s(NN) = 5 TeV and lead-neon fixed-target collisions at root s(NN) = 69 GeV. The energy deposits in the electromagnetic calorimeter are used to determine and define the centrality classes. The correspondence between the number of participants and the centrality for the lead-lead collisions is in good agreement with the correspondence found in other experiments, and the centrality measurements for the lead-neon collisions presented here are performed for the first time in fixed-target collisions at the LHC.
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Barenboim, G. (2022). Some Aspects About Pushing the CPT and Lorentz Invariance Frontier With Neutrinos. Front. Physics, 10, 813753–7pp.
Abstract: The CPT symmetry, which combines Charge Conjugation, Parity, and Time Reversal, is a cornerstone of our model-building method, and its probable violation will endanger the most extended tool we presently utilize to explain physics, namely local relativistic quantum fields. However, the kaon system's conservation constraints appear to be rather severe. We will show in this paper that neutrino oscillation experiments can enhance this limit by many orders of magnitude, making them an excellent instrument for investigating the basis of our understanding of Nature. As a result, verifying CPT invariance does not evaluate a specific model, but rather the entire paradigm. Therefore, as the CPT's status in the neutrino sector, linked or not to Lorentz invariance violation, will be assessed at an unprecedented level by current and future long baseline experiments, distinguishing it from comparable experimental fingerprints coming from non-standard interactions is critical. Whether the entire paradigm or simply the conventional model of neutrinos is at jeopardy is significantly dependent on this.
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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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