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ANTARES and IceCube Collaborations(Albert, A. et al), Colomer, M., Gozzini, R., Hernandez-Rey, J. J., Illuminati, G., Khan-Chowdhury, N. R., et al. (2020). Combined search for neutrinos from dark matter self-annihilation in the Galactic Center with ANTARES and IceCube. Phys. Rev. D, 102(8), 082002–13pp.
Abstract: We present the results of the first combined dark matter search targeting the Galactic Center using the ANTARES and IceCube neutrino telescopes. For dark matter particles with masses from 50 to 1000 GeV, the sensitivities on the self-annihilation cross section set by ANTARES and IceCube are comparable, making this mass range particularly interesting for a joint analysis. Dark matter self-annihilation through the tau(+)tau(-) , mu(+)mu(-) , b (b) over bar, and W+W- channels is considered for both the Navarro-Frenk-White and Burkert halo profiles. In the combination of 2101.6 days of ANTARES data and 1007 days of IceCube data, no excess over the expected background is observed. Limits on the thermally averaged dark matter annihilation cross section <sigma(A)upsilon > are set. These limits present an improvement of up to a factor of 2 in the studied dark matter mass range with respect to the individual limits published by both collaborations. When considering dark matter particles with a mass of 200 GeV annihilating through the tau(+)tau(-)channel, the value obtained for the limit is 7.44 x 10(-24) cm(3) s(-1 )for the Navarro-Frenk-White halo profile. For the purpose of this joint analysis, the model parameters and the likelihood are unified, providing a benchmark for forthcoming dark matter searches performed by neutrino telescopes.
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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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Ikeno, N., Bayar, M., & Oset, E. (2021). Combined theoretical study of the D+ -> pi(+) eta eta and D+ -> pi(+)pi(0) eta reactions. Eur. Phys. J. C, 81(4), 377–10pp.
Abstract: We study the D+ -> pi(+) eta eta and D+ -> pi(+)pi(0) eta reactions, which are single Cabibbo suppressed and can proceed both through internal and external emission. The primary mechanisms at quark level are considered, followed by hadronization to produce three mesons in the D+ decay, and after that the final state interaction of these mesons leads to the production of the a(0)(980) resonance, seen in the pi(+)eta, pi(0)eta mass distributions. The theory has three unknown parameters to determine the shape of the distributions and the ratio between the D+ -> pi(+) eta eta and D+ -> pi(+)pi(0) eta rates. This ratio restricts much the sets of parameters but there is still much freedom leading to different shapes in the mass distributions. We call for a measurement of these mass distributions that will settle the reaction mechanism, while at the same time provide relevant information on the way that the a(0)(980) resonance is produced in the reactions.
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Coleiro, A., Colomer, M., Dornic, D., Lincetto, M., & Kulikovskiy, V. (2020). Combining neutrino experimental light-curves for pointing to the next galactic core-collapse supernova. Eur. Phys. J. C, 80(9), 856–12pp.
Abstract: The multi-messenger observation of the next galactic core-collapse supernova will shed light on the different physical processes involved in these energetic explosions. Good timing and pointing capabilities of neutrino detectors would help in the search for an electromagnetic or gravitational-wave counterparts. An approach for the determination of the arrival time delay of the neutrino signal at different experiments using a direct detected neutrino light-curve matching is discussed. A simplified supernova model and detector simulation are used for its application. The arrival time delay and its uncertainty between two neutrino detectors are estimated with chi-square and cross-correlation methods. The direct comparison of the detected light-curves offers the advantage to be model-independent. Millisecond time resolution on the arrival time delay at two different detectors is needed. Using the computed time delay between different combinations of currently operational and future detectors, a triangulation method is used to infer the supernova localisation in the sky. The combination of IceCube, Hyper-Kamiokande, JUNO and KM3NeT/ARCA provides a 90% confidence area of 140 +/- 20 deg(2). These low-latency analysis methods can be implemented in the SNEWS alert system.
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van Beekveld, M., Caron, S., Hendriks, L., Jackson, P., Leinweber, A., Otten, S., et al. (2021). Combining outlier analysis algorithms to identify new physics at the LHC. J. High Energy Phys., 09(9), 024–33pp.
Abstract: The lack of evidence for new physics at the Large Hadron Collider so far has prompted the development of model-independent search techniques. In this study, we compare the anomaly scores of a variety of anomaly detection techniques: an isolation forest, a Gaussian mixture model, a static autoencoder, and a beta-variational autoencoder (VAE), where we define the reconstruction loss of the latter as a weighted combination of regression and classification terms. We apply these algorithms to the 4-vectors of simulated LHC data, but also investigate the performance when the non-VAE algorithms are applied to the latent space variables created by the VAE. In addition, we assess the performance when the anomaly scores of these algorithms are combined in various ways. Using supersymmetric benchmark points, we find that the logical AND combination of the anomaly scores yielded from algorithms trained in the latent space of the VAE is the most effective discriminator of all methods tested.
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