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Caron, S., Kim, J. S., Rolbiecki, K., Ruiz de Austri, R., & Stienen, B. (2017). The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning. Eur. Phys. J. C, 77(4), 257–25pp.
Abstract: A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300,000 pMSSM model sets – each tested against 200 signal regions by ATLAS – have been used to train and validate SUSY-AI. The code is currently able to reproduce theATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/.
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ATLAS Collaboration(Aad, G. et al), Amoros, G., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Escobar, C., et al. (2010). The ATLAS Simulation Infrastructure. Eur. Phys. J. C, 70(3), 823–874.
Abstract: The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes.
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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., Castillo Gimenez, V., et al. (2022). The ATLAS inner detector trigger performance in pp collisions at 13 TeV during LHC Run 2. Eur. Phys. J. C, 82(3), 206–57pp.
Abstract: The design and performance of the inner detector trigger for the high level trigger of the ATLAS experiment at the Large Hadron Collider during the 2016-2018 data taking period is discussed. In 2016, 2017, and 2018 the ATLAS detector recorded 35.6 fb(-1), 46.9 fb(-1), and 60.6 fb(-1) respectively of proton-proton collision data at a centre-of-mass energy of 13TeV. In order to deal with the very high interaction multiplicities per bunch crossing expected with the 13TeV collisions the inner detector trigger was redesigned during the long shutdown of the Large Hadron Collider from 2013 until 2015. An overview of these developments is provided and the performance of the tracking in the trigger for the muon, electron, tau and b-jet signatures is discussed. The high performance of the inner detector trigger with these extreme interaction multiplicities demonstrates how the inner detector tracking continues to lie at the heart of the trigger performance and is essential in enabling the ATLAS physics programme.
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ATLAS Collaboration(Aad, G. et al), Amoros, G., Bernabeu Verdu, J., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., et al. (2010). The ATLAS Inner Detector commissioning and calibration. Eur. Phys. J. C, 70(3), 787–821.
Abstract: The ATLAS Inner Detector is a composite tracking system consisting of silicon pixels, silicon strips and straw tubes in a 2 T magnetic field. Its installation was completed in August 2008 and the detector took part in data-taking with single LHC beams and cosmic rays. The initial detector operation, hardware commissioning and in-situ calibrations are described. Tracking performance has been measured with 7.6 million cosmic-ray events, collected using a tracking trigger and reconstructed with modular pattern-recognition and fitting software. The intrinsic hit efficiency and tracking trigger efficiencies are close to 100%. Lorentz angle measurements for both electrons and holes, specific energy-loss calibration and transition radiation turn-on measurements have been performed. Different alignment techniques have been used to reconstruct the detector geometry. After the initial alignment, a transverse impact parameter resolution of 22.1 +/- 0.9 μm and a relative momentum resolution sigma (p) /p=(4.83 +/- 0.16)x10(-4) GeV(-1)xp (T) have been measured for high momentum tracks.
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Liang, W. H., & Oset, E. (2020). Testing the origin of the f1(1420) with the Kbar p -> Lambda(Sigma) K Kbar pi reaction. Eur. Phys. J. C, 80(5), 407–8pp.
Abstract: We study the K¯p→YKK¯π reactions with K¯=K¯0,K− and Y=Σ0,Σ+,Λ, in the region of KK¯π invariant masses of 1200−1550 MeV. The strong coupling of the f1(1285) resonance to K∗K¯ makes the mechanism based on K∗ exchange very efficient to produce this resonance observed in the KK¯π invariant mass distribution. In addition, in all the reactions one observes an associated peak at 1420 MeV which comes from the K∗K¯ decay mode of the f1(1285) when the K∗ is placed off shell at higher invariant masses. We claim this to be the reason for the peak of the K∗K¯ distribution seen in the experiments which has been associated to the “f1(1420)” resonance.
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