Beacham, J. et al, & Martinez-Vidal, F. (2020). Physics beyond colliders at CERN: beyond the Standard Model working group report. J. Phys. G, 47(1), 010501–114pp.
Abstract: The Physics Beyond Colliders initiative is an exploratory study aimed at exploiting the full scientific potential of the CERN's accelerator complex and scientific infrastructures through projects complementary to the LHC and other possible future colliders. These projects will target fundamental physics questions in modern particle physics. This document presents the status of the proposals presented in the framework of the Beyond Standard Model physics working group, and explore their physics reach and the impact that CERN could have in the next 10-20 years on the international landscape.
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Villanueva-Domingo, P., & Villaescusa-Navarro, F. (2021). Removing Astrophysics in 21 cm Maps with Neural Networks. Astrophys. J., 907(1), 44–14pp.
Abstract: Measuring temperature fluctuations in the 21 cm signal from the epoch of reionization and the cosmic dawn is one of the most promising ways to study the universe at high redshifts. Unfortunately, the 21 cm signal is affected by both cosmology and astrophysics processes in a nontrivial manner. We run a suite of 1000 numerical simulations with different values of the main astrophysical parameters. From these simulations we produce tens of thousands of 21 cm maps at redshifts 10 <= z <= 20. We train a convolutional neural network to remove the effects of astrophysics from the 21 cm maps and output maps of the underlying matter field. We show that our model is able to generate 2D matter fields not only that resemble the true ones visually but whose statistical properties agree with the true ones within a few percent down to scales 2 Mpc(-1). We demonstrate that our neural network retains astrophysical information that can be used to constrain the value of the astrophysical parameters. Finally, we use saliency maps to try to understand which features of the 21 cm maps the network is using in order to determine the value of the astrophysical parameters.
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NEXT Collaboration(Kekic, M. et al), Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., et al. (2021). Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment. J. High Energy Phys., 01(1), 189–22pp.
Abstract: Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs for event classification in the NEXT experiment, which will search for neutrinoless double-beta decay in Xe-136. To do so, we demonstrate the usage of CNNs for the identification of electron-positron pair production events, which exhibit a topology similar to that of a neutrinoless double-beta decay event. These events were produced in the NEXT-White high-pressure xenon TPC using 2.6 MeV gamma rays from a Th-228 calibration source. We train a network on Monte Carlo-simulated events and show that, by applying on-the-fly data augmentation, the network can be made robust against differences between simulation and data. The use of CNNs offers significant improvement in signal efficiency and background rejection when compared to previous non-CNN-based analyses.
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Diaz-Morcillo, A., Barcelo, J. M. G., Guerrero, A. J. L., Navarro, P., Gimeno, B., Cuneáis, S. A., et al. (2022). Design of New Resonant Haloscopes in the Search for the Dark Matter Axion: A Review of the First Steps in the RADES Collaboration. Universe, 8(1), 5–22pp.
Abstract: With the increasing interest in dark matter axion detection through haloscopes, in which different international groups are currently involved, the RADES group was established in 2016 with the goal of developing very sensitive detection systems to be operated in dipole magnets. This review deals with the work developed by this collaboration during its first five years: from the first designs-based on the multi-cavity concept, aiming to increase the haloscope volume, and thereby improve sensitivity-to their evolution, data acquisition design, and finally, the first experimental run. Moreover, the envisaged work within RADES for both dipole and solenoid magnets in the short and medium term is also presented.
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Sierra, D. A., De Romeri, V., Flores, L. J., & Papoulias, D. K. (2022). Impact of COHERENT measurements, cross section uncertainties and new interactions on the neutrino floor. J. Cosmol. Astropart. Phys., 01(1), 055–26pp.
Abstract: We reconsider the discovery limit of multi-ton direct detection dark matter experiments in the light of recent measurements of the coherent elastic neutrino-nucleus scattering process. Assuming the cross section to be a parameter entirely determined by data, rather than using its Standard Model prediction, we use the COHERENT CsI and LAr data sets to determine WIMP discovery limits. Being based on a data-driven approach, the results are thus free from theoretical assumptions and fall within the WIMP mass regions where XENONnT and DARWIN have best expected sensitivities. We further determine the impact of subleading nuclear form factor and weak mixing angle uncertainties effects on WIMP discovery limits. We point out that these effects, albeit small, should be taken into account. Moreover, to quantify the impact of new physics effects in the neutrino background, we revisit WIMP discovery limits assuming light vector and scalar mediators as well as neutrino magnetic moments/transitions. We stress that the presence of new interactions in the neutrino sector, in general, tend to worsen the WIMP discovery limit.
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