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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Garcia Soto, A., et al. (2022). Combined sensitivity of JUNO and KM3NeT/ORCA to the neutrino mass ordering. J. High Energy Phys., 03(3), 055–31pp.
Abstract: This article presents the potential of a combined analysis of the JUNO and KM3NeT/ORCA experiments to determine the neutrino mass ordering. This combination is particularly interesting as it significantly boosts the potential of either detector, beyond simply adding their neutrino mass ordering sensitivities, by removing a degeneracy in the determination of Delta M-31(2) between the two experiments when assuming the wrong ordering. The study is based on the latest projected performances for JUNO, and on simulation tools using a full Monte Carlo approach to the KM3NeT/ORCA response with a careful assessment of its energy systematics. From this analysis, a 5 sigma determination of the neutrino mass ordering is expected after 6 years of joint data taking for any value of the oscillation parameters. This sensitivity would be achieved after only 2 years of joint data taking assuming the current global best-fit values for those parameters for normal ordering.
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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). Observation of Lambda b(0) -> D(+)p pi(-)pi(-) and Lambda b(0) -> D-*+p pi(-)pi(-) decays. J. High Energy Phys., 03(3), 153–30pp.
Abstract: The multihadron decays Lambda(0)(b) -> D(+)p pi(-)pi(-) and Lambda(0 )(b)-> D-*+p pi(-)pi(-) are observed in data corresponding to an integrated luminosity of 3fb(-1), collected in proton-proton collisions at centre-of-mass energies of 7 and 8 TeV by the LHCb detector. Using the decay Lambda(0)(b) -> Lambda(+)(c)pi(+)pi(-)pi(-) as a normalisation channel, the ratio of branching fractions is measured to be B(Lambda(0)(b) -> D(+)p pi(-)pi(-))/B(Lambda(0)(b) -> Lambda(+)(c)pi(+)pi(-)pi(-)) x B(D+ -> K-pi(+)pi(+))/B(Lambda(+)(c)-> pK(-)pi(+)) = (5.35 +/- 0.21 +/- 0.16) %, where the first uncertainty is statistical and the second systematic. The ratio of branching fractions for the Lambda(0)(b)-> D-*+p pi(-)pi(-) and Lambda(0)(b) -> D(+)p pi(-)pi(-) decays is found to be B(Lambda(0)(b)-> D-*+p pi(-)pi(-))/B(Lambda(0)(b) -> D(+)p pi(-)pi(-)) x (B(D-*+-> D+pi(0)) + B(D (*)+-> D- (+)gamma)) = (61.3 +/- 4.3 +/- 4.0) %.
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Afonso, V. I., Mora-Perez, G., Olmo, G. J., Orazi, E., & Rubiera-Garcia, D. (2022). An infinite class of exact rotating black hole metrics of modified gravity. J. Cosmol. Astropart. Phys., 03(3), 052–14pp.
Abstract: We build an infinite class of exact axisymmetric solutions of a metric-affine gravity theory, namely, Eddington-inspired Born-Infeld gravity, coupled to an anisotropic fluid as a matter source. The solution-generating method employed is not unique of this theory but can be extended to other Ricci-Based Gravity theories (RBGs), a class of theories built out of contractions of the Ricci tensor with the metric. This method exploits a correspondence between the space of solutions of General Relativity and that of RBGs, and is independent of the symmetries of the problem. For the particular case in which the fluid is identified with non-linear electromagnetic fields we explicitly derive the corresponding axisymmetric solutions. Finally, we use this result to work out the counterpart of the Kerr-Newman black hole when Maxwell electrodynamics is set on the metric-affine side. Our results open up an exciting new avenue for testing new gravitational phenomenology in the fields of gravitational waves and shadows out of rotating black holes.
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Abbar, S., & Capozzi, F. (2022). Suppression of fast neutrino flavor conversions occurring at large distances in core-collapse supernovae. J. Cosmol. Astropart. Phys., 03(3), 051–13pp.
Abstract: Neutrinos propagating in dense neutrino media such as core-collapse supernovae and neutron star merger remnants can experience the so-called fast flavor conversions on scales much shorter than those expected in vacuum. A very generic class of fast flavor instabilities is the ones which are produced by the backward scattering of neutrinos off the nuclei at relatively large distances from the supernova core. In this study we demonstrate that despite their ubiquity, such fast instabilities are unlikely to cause significant flavor conversions if the population of neutrinos in the backward direction is not large enough. Indeed, the scattering-induced instabilities can mostly impact the neutrinos traveling in the backward direction, which represent only a small fraction of neutrinos at large radii. We show that this can be explained by the shape of the unstable flavor eigenstates, which can be extremely peaked at the backward angles.
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Caron, S., Ruiz de Austri, R., & Zhang, Z. Y. (2023). Mixture-of-Theories training: can we find new physics and anomalies better by mixing physical theories? J. High Energy Phys., 03(3), 004–37pp.
Abstract: Model-independent search strategies have been increasingly proposed in recent years because on the one hand there has been no clear signal for new physics and on the other hand there is a lack of a highly probable and parameter-free extension of the standard model. For these reasons, there is no simple search target so far. In this work, we try to take a new direction and ask the question: bearing in mind that we have a large number of new physics theories that go beyond the Standard Model and may contain a grain of truth, can we improve our search strategy for unknown signals by using them “in combination”? In particular, we show that a signal hypothesis based on a large, intermingled set of many different theoretical signal models can be a superior approach to find an unknown BSM signal. Applied to a recent data challenge, we show that “mixture-of-theories training” outperforms strategies that optimize signal regions with a single BSM model as well as most unsupervised strategies. Applications of this work include anomaly detection and the definition of signal regions in the search for signals of new physics.
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