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LHCb Collaboration(Aaij, R. et al), Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Remon Alepuz, C., & Ruiz Vidal, J. (2021). Angular analysis of the rare decay B-s(0) -> phi mu(+)mu(-). J. High Energy Phys., 11(11), 043–45pp.
Abstract: An angular analysis of the rare decay B-s(0) -> phi mu(+)mu(-) is presented, using proton-proton collision data collected by the LHCb experiment at centre-of-mass energies of 7, 8 and 13TeV, corresponding to an integrated luminosity of 8.4 fb(-1). The observables describing the angular distributions of the decay B-s(0) -> phi mu(+)mu(-) are determined in regions of q(2), the square of the dimuon invariant mass. The results are consistent with Standard Model predictions.
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Aarrestad, T. et al, Mamuzic, J., & Ruiz de Austri, R. (2022). Benchmark data and model independent event classification for the large hadron collider. SciPost Phys., 12(1), 043–57pp.
Abstract: We describe the outcome of a data challenge conducted as part of the Dark Machines (https://www.darkmachines.org) initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged aims to detect signals of new physics at the Large Hadron Collider (LHC) using unsupervised machine learning algorithms. First, we propose how an anomaly score could be implemented to define model-independent signal regions in LHC searches. We define and describe a large benchmark dataset, consisting of > 1 billion simulated LHC events corresponding to 10 fb(-1) of proton-proton collisions at a center-of-mass energy of 13 TeV. We then review a wide range of anomaly detection and density estimation algorithms, developed in the context of the data challenge, and we measure their performance in a set of realistic analysis environments. We draw a number of useful conclusions that will aid the development of unsupervised new physics searches during the third run of the LHC, and provide our benchmark dataset for future studies at https://www.phenoMLdata.org. Code to reproduce the analysis is provided at https://github.com/bostdiek/DarkMachines-UnsupervisedChallenge.
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Afonso, V. I., Olmo, G. J., Orazi, E., & Rubiera-Garcia, D. (2019). New scalar compact objects in Ricci-based gravity theories. J. Cosmol. Astropart. Phys., 12(12), 044–20pp.
Abstract: Taking advantage of a previously developed method, which allows to map solutions of General Relativity into a broad family of theories of gravity based on the Ricci tensor (Ricci-based gravities), we find new exact analytical scalar field solutions by mapping the free-field static, spherically symmetric solution of General Relativity (GR) into quadratic f(R) gravity and the Eddington-inspired Born-Infeld gravity. The obtained solutions have some distinctive feature below the would-be Schwarzschild radius of a configuration with the same mass, though in this case no horizon is present. The compact objects found include wormholes, compact balls, shells of energy with no interior, and a new kind of object which acts as a kind of wormhole membrane. The latter object has Euclidean topology but connects antipodal points of its surface by transferring particles and null rays across its interior in virtually zero affine time. We point out the relevance of these results regarding the existence of compact scalar field objects beyond General Relativity that may effectively act as black hole mimickers.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Castillo, F. L., Castillo Gimenez, V., et al. (2020). Measurements of the production cross-section for a Z boson in association with b-jets in proton-proton collisions at root s=13 TeV with the ATLAS detector. J. High Energy Phys., 07(7), 044–58pp.
Abstract: This paper presents a measurement of the production cross-section of aZboson in association withb-jets, in proton-proton collisions at root s = 13 TeV with the ATLAS experiment at the Large Hadron Collider using data corresponding to an integrated luminosity of 35.6 fb(-1). Inclusive and differential cross-sections are measured for events containing aZboson decaying into electrons or muons and produced in association with at least one or at least two b-jets with transverse momentum p(T)>20 GeV and rapidity vertical bar y vertical bar <2.5. Predictions from several Monte Carlo generators based on leading-order (LO) or next-to-leading-order (NLO) matrix elements interfaced with a parton-shower simulation and testing different flavour schemes for the choice of initial-state partons are compared with measured cross-sections. The 5-flavour number scheme predictions at NLO accuracy agree better with data than 4-flavour number scheme ones. The 4-flavour number scheme predictions underestimate data in events with at least one b-jet.
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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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