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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). Tools for estimating fake/non-prompt lepton backgrounds with the ATLAS detector at the LHC. J. Instrum., 18(11), T11004–61pp.
Abstract: Measurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to 'fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.
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Karan, A., Sadhukhan, S., & Valle, J. W. F. (2023). Phenomenological profile of scotogenic fermionic dark matter. J. High Energy Phys., 12(12), 185–34pp.
Abstract: We consider the possibility that neutrino masses arise from the exchange of dark matter states. We examine in detail the phenomenology of fermionic dark matter in the singlet-triplet scotogenic model. We explore the case of singlet-like fermionic dark matter, taking into account all coannihilation effects relevant for determining its relic abundance, such as fermion-fermion and scalar-fermion coannihilation. Although this in principle allows for dark matter below 60 GeV, the latter is in conflict with charged lepton flavour violation (cLFV) and/or collider physics constraints. We examine the prospects for direct dark matter detection in upcoming experiments up to 10 TeV. Fermion-scalar coannihilation is needed to obtain viable fermionic dark matter in the 60-100 GeV mass range. Fermion-fermion and fermion-scalar coannihilation play complementary roles in different parameter regions above 100 GeV.
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Azevedo, C. D. R., Baeza, A., Chauveau, E., Corbacho, J. A., Diaz, J., Domange, J., et al. (2023). Development of a real-time tritium-in-water monitor. J. Instrum., 18(12), T12008–14pp.
Abstract: In this paper, we report the development and performance of a detector module envisaging a tritium-in-water real-time activity monitor. The monitor is based on modular detection units whose number can be chosen according to the required sensitivity. The full system is being designed to achieve a Minimum Detectable Activity (MDA) of 100 Bq/L of tritium-in-water activity which is the limit established by the E.U. Council Directive 2013/51/Euratom for water intended for human consumption. The same system can be used as a real-time pre-alert system for nuclear power plant regarding tritium-in water environmental surveillance. The first detector module was characterized, commissioned and installed immediately after the discharge channel of the Arrocampo dam (Almaraz nuclear power plant, Spain) on the Tagus river. Due to the high sensitivity of the single detection modules, the system requires radioactive background mitigation techniques through the use of active and passive shielding. We have extrapolated a MDA of 3.6 kBq/L for a single module being this value limited by the cosmic background. The obtained value for a single module is already compatible with a real-time environmental surveillance and pre-alert system. Further optimization of the single-module sensitivity will imply the reduction of the number of modules and the cost of the detector system.
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Ghoshal, A., Gouttenoire, Y., Heurtier, L., & Simakachorn, P. (2023). Primordial black hole archaeology with gravitational waves from cosmic strings. J. High Energy Phys., 08(8), 196–43pp.
Abstract: Light primordial black holes (PBHs) with masses smaller than 10(9) g (10(-24) M-circle dot) evaporate before the onset of Big-Bang nucleosynthesis, rendering their detection rather challenging. If efficiently produced, they may have dominated the universe energy density. We study how such an early matter-dominated era can be probed successfully using gravitational waves (GW) emitted by local and global cosmic strings. While previous studies showed that a matter era generates a single-step suppression of the GW spectrum, we instead find a double-step suppression for local-string GW whose spectral shape provides information on the duration of the matter era. The presence of the two steps in the GW spectrum originates from GW being produced through two events separated in time: loop formation and loop decay, taking place either before or after the matter era. The second step – called the knee – is a novel feature which is universal to any early matter-dominated era and is not only specific to PBHs. Detecting GWs from cosmic strings with LISA, ET, or BBO would set constraints on PBHs with masses between 10(6) and 10(9) g for local strings with tension G μ= 10(-11), and PBHs masses between 10(4) and 10(9) g for global strings with symmetry-breaking scale eta = 10(15) GeV. Effects from the spin of PBHs are discussed.
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Folgado, M. G., & Sanz, V. (2022). Exploring the political pulse of a country using data science tools. J. Comput. Soc. Sci., 5, 987–1000.
Abstract: In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train a Fully-Connected Neural Network (FCNN) to recognise the political affiliation of a tweet. The FCNN is able to predict the origin of the tweet with a precision in the range of 71-75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as an example of how to use Twitter data and different types of Data Science tools for a political analysis.
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