Bhattacharya, S., Mondal, N., Roshan, R., & Vatsyayan, D. (2024). Leptogenesis, dark matter and gravitational waves from discrete symmetry breaking. J. Cosmol. Astropart. Phys., 06(6), 029–25pp.
Abstract: We analyse a model that connects the neutrino sector and the dark sector of the universe via a mediator 41., stabilised by a discrete Z4 symmetry that breaks to a remnant Z2 upon 41. acquiring a non -zero vacuum expectation value (v phi). The model accounts for the observed baryon asymmetry of the universe via additional contributions to the canonical Type -I leptogenesis. The Z4 symmetry breaking scale (v phi) in the model not only establishes a connection between the neutrino sector and the dark sector, but could also lead to gravitational wave signals that are within the reach of current and future experimental sensitivities.
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KM3NeT Collaboration(Adrian-Martinez, S. et al), Calvo Diaz-Aldagalan, D., Hernandez-Rey, J. J., Martinez-Mora, J. A., Real, D., Zornoza, J. D., et al. (2014). Deep sea tests of a prototype of the KM3NeT digital optical module. Eur. Phys. J. C, 74(9), 3056–8pp.
Abstract: The first prototype of a photo-detection unit of the future KM3NeT neutrino telescope has been deployed in the deepwaters of the Mediterranean Sea. This digital optical module has a novel design with a very large photocathode area segmented by the use of 31 three inch photomultiplier tubes. It has been integrated in the ANTARES detector for in-situ testing and validation. This paper reports on the first months of data taking and rate measurements. The analysis results highlight the capabilities of the new module design in terms of background suppression and signal recognition. The directionality of the optical module enables the recognition of multiple Cherenkov photons from the same (40)Kdecay and the localisation of bioluminescent activity in the neighbourhood. The single unit can cleanly identify atmospheric muons and provide sensitivity to the muon arrival directions.
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KM3NeT Collaboration(Adrian-Martinez, S. et al), Barrios-Marti, J., Calvo Diaz-Aldagalan, D., Hernandez-Rey, J. J., Real, D., Zornoza, J. D., et al. (2016). The prototype detection unit of the KM3NeT detector. Eur. Phys. J. C, 76(2), 54–12pp.
Abstract: A prototype detection unit of the KM3NeT deep-sea neutrino telescope has been installed at 3500m depth 80 km offshore the Italian coast. KM3NeT in its final configuration will contain several hundreds of detection units. Each detection unit is a mechanical structure anchored to the sea floor, held vertical by a submerged buoy and supporting optical modules for the detection of Cherenkov light emitted by charged secondary particles emerging from neutrino interactions. This prototype string implements three optical modules with 31 photomultiplier tubes each. These optical modules were developed by the KM3NeT Collaboration to enhance the detection capability of neutrino interactions. The prototype detection unit was operated since its deployment in May 2014 until its decommissioning in July 2015. Reconstruction of the particle trajectories from the data requires a nanosecond accuracy in the time calibration. A procedure for relative time calibration of the photomultiplier tubes contained in each optical module is described. This procedure is based on the measured coincidences produced in the sea by the K background light and can easily be expanded to a detector with several thousands of optical modules. The time offsets between the different optical modules are obtained using LED nanobeacons mounted inside them. A set of data corresponding to 600 h of livetime was analysed. The results show good agreement with Monte Carlo simulations of the expected optical background and the signal from atmospheric muons. An almost background-free sample of muons was selected by filtering the time correlated signals on all the three optical modules. The zenith angle of the selected muons was reconstructed with a precision of about 3 degrees.
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de Florian, D., Sborlini, G. F. R., & Rodrigo, G. (2016). QED corrections to the Altarelli-Parisi splitting functions. Eur. Phys. J. C, 76(5), 282–6pp.
Abstract: We discuss the combined effect of QED and QCD corrections to the evolution of parton distributions. We extend the available knowledge of the Altarelli-Parisi splitting functions to one order higher in QED, and we provide explicit expressions for the splitting kernels up to O(alpha alpha(S)). The results presented in this article allow one to perform a parton distribution function analysis reaching full NLO QCD-QED combined precision.
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Villanueva-Domingo, P., Villaescusa-Navarro, F., Angles-Alcazar, D., Genel, S., Marinacci, F., Spergel, D. N., et al. (2022). Inferring Halo Masses with Graph Neural Networks. Astrophys. J., 935(1), 30–15pp.
Abstract: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet).
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