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XENON Collaboration(Aprile, E. et al), & Orrigo, S. E. A. (2014). Conceptual design and simulation of a water Cherenkov muon veto for the XENON1T experiment. J. Instrum., 9, P11006–20pp.
Abstract: XENON is a dark matter direct detection project, consisting of a time projection chamber (TPC) filled with liquid xenon as detection medium. The construction of the next generation detector, XENON1T, is presently taking place at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It aims at a sensitivity to spin-independent cross sections of 2.10(47) cm(2) for WIMP masses around 50 GeV/c(2), which requires a background reduction by two orders of magnitude compared to XENON100, the current generation detector. An active system that is able to tag muons and muon-induced backgrounds is critical for this goal. A water Cherenkov detector of similar to 10m height and diameter has been therefore developed, equipped with 8 inch photomultipliers and cladded by a reflective foil. We present the design and optimization study for this detector, which has been carried out with a series of Monte Carlo simulations. The muon veto will reach very high detection efficiencies for muons (> 99.5%) and showers of secondary particles from muon interactions in the rock (> 70%). Similar efficiencies will be obtained for XENONnT, the upgrade of XENON1T, which will later improve the WIMP sensitivity by another order of magnitude. With the Cherenkov water shield studied here, the background from muon-induced neutrons in XENON1T is negligible.
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Athenodorou, A., Binosi, D., Boucaud, P., De Soto, F., Papavassiliou, J., Rodriguez-Quintero, J., et al. (2016). On the zero crossing of the three-gluon vertex. Phys. Lett. B, 761, 444–449.
Abstract: We report on new results on the infrared behavior of the three-gluon vertex in quenched Quantum Chromodynamics, obtained from large-volume lattice simulations. The main focus of our study is the appearance of the characteristic infrared feature known as 'zero crossing', the origin of which is intimately connected with the nonperturbative masslessness of the Faddeev-Popov ghost. The appearance of this effect is clearly visible in one of the two kinematic configurations analyzed, and its theoretical origin is discussed in the framework of Schwinger-Dyson equations. The effective coupling in the momentum subtraction scheme that corresponds to the three-gluon vertex is constructed, revealing the vanishing of the effective interaction at the exact location of the zero crossing.
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Caron, S., Gomez-Vargas, G. A., Hendriks, L., & Ruiz de Austri, R. (2018). Analyzing gamma rays of the Galactic Center with deep learning. J. Cosmol. Astropart. Phys., 05(5), 058–24pp.
Abstract: We present the application of convolutional neural networks to a particular problem in gamma ray astronomy. Explicitly, we use this method to investigate the origin of an excess emission of GeV gamma rays in the direction of the Galactic Center, reported by several groups by analyzing Fermi-LAT data. Interpretations of this excess include gamma rays created by the annihilation of dark matter particles and gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. We train and test convolutional neural networks with simulated Fermi-LAT images based on point and diffuse emission models of the Galactic Center tuned to measured gamma ray data. Our new method allows precise measurements of the contribution and properties of an unresolved population of gamma ray point sources in the interstellar diffuse emission model. The current model predicts the fraction of unresolved point sources with an error of up to 10% and this is expected to decrease with future work.
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Doncel, M., Cederwall, B., Martin, S., Quintana, B., Gadea, A., Farnea, E., et al. (2015). Conceptual design of a high resolution Ge array with tracking and imaging capabilities for the DESPEC (FAIR) experiment. J. Instrum., 10, P06010–15pp.
Abstract: We present results of Monte Carlo simulations for the conceptual design of the high-resolution DESPEC Germanium Array Spectrometer (DEGAS) proposed for the Facility for Ion and Antiproton Research (FAIR) under construction at Darmstadt, Germany. The project is carried out in three phases, although only results for the two first phases will be addressed in this work. The first phase will consist of a re-arrangement of the EUROBALL cluster detectors previously used in the RISING campaign at GSI. The second phase is based on coupling AGATA-type triple-cluster detectors with EUROBALL cluster detectors in a compact geometry around the active ion implantation target of DESPEC.
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de los Rios, M., Petac, M., Zaldivar, B., Bonaventura, N. R., Calore, F., & Iocco, F. (2023). Determining the dark matter distribution in simulated galaxies with deep learning. Mon. Not. Roy. Astron. Soc., 525(4), 6015–6035.
Abstract: We present a novel method of inferring the dark matter (DM) content and spatial distribution within galaxies, using convolutional neural networks (CNNs) trained within state-of-the-art hydrodynamical simulations (Illustris-TNG100). Within the controlled environment of the simulation, the framework we have developed is capable of inferring the DM mass distribution within galaxies of mass similar to 10(11)-10(13)M(circle dot) from the gravitationally baryon-dominated internal regions to the DM-rich, baryon-depleted outskirts of the galaxies, with a mean absolute error always below approximate to 0.25 when using photometrical and spectroscopic information. With respect to traditional methods, the one presented here also possesses the advantages of not relying on a pre-assigned shape for the DM distribution, to be applicable to galaxies not necessarily in isolation, and to perform very well even in the absence of spectroscopic observations.
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