ATLAS Collaboration(Aad, G. et al), Amoros, G., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Escobar, C., et al. (2011). Search for massive long-lived highly ionising particles with the ATLAS detector at the LHC. Phys. Lett. B, 698(5), 353–370.
Abstract: A search is made for massive highly ionising particles with lifetimes in excess of 100 ns, with the ATLAS experiment at the Large Hadron Collider, using 3.1 pb(-1) of pp collision data taken at root s = 7 TeV. The signature of energy loss in the ATLAS inner detector and electromagnetic calorimeter is used. No such particles are found and limits on the production cross section for electric charges 6e <= vertical bar q vertical bar <= 17e and masses 200 GeV <= m <= 1000 GeV are set in the range 1-12 pb for different hypotheses on the production mechanism.
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ATLAS Collaboration(Aad, G. et al), Amoros, G., Cabrera Urban, S., Castillo Gimenez, V., Costa, M. J., Ferrer, A., et al. (2012). A study of the material in the ATLAS inner detector using secondary hadronic interactions. J. Instrum., 7, P01013–40pp.
Abstract: The ATLAS inner detector is used to reconstruct secondary vertices due to hadronic interactions of primary collision products, so probing the location and amount of material in the inner region of ATLAS. Data collected in 7 TeV pp collisions at the LHC, with a minimum bias trigger, are used for comparisons with simulated events. The reconstructed secondary vertices have spatial resolutions ranging from similar to 200 μm to 1 mm. The overall material description in the simulation is validated to within an experimental uncertainty of about 7%. This will lead to a better understanding of the reconstruction of various objects such as tracks, leptons, jets, and missing transverse momentum.
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AbdusSalam, S. S. et al, & Eberhardt, O. (2022). Simple and statistically sound recommendations for analysing physical theories. Rep. Prog. Phys., 85(5), 052201–11pp.
Abstract: Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Our examples can be reproduced with the code publicly available at Zenodo.
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Super-Kamiokande Collaboration(Abe, K. et al), & Molina Sedgwick, S. (2022). Neutron tagging following atmospheric neutrino events in a water Cherenkov detector. J. Instrum., 17(10), P10029–41pp.
Abstract: We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 +/- 9 μs.
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Double Chooz collaboration(Abrahao, T. et al), & Novella, P. (2018). Novel event classification based on spectral analysis of scintillation waveforms in Double Chooz. J. Instrum., 13, P01031–26pp.
Abstract: Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in large detectors. This paper describes a novel approach for a pulse shape based event classification developed in the context of the Double Chooz reactor antineutrino experiment. Unlike previous implementations, this method uses the Fourier power spectra of the scintillation pulse shapes to obtain event-wise information. A classification variable built from spectral information was able to achieve an unprecedented performance, despite the lack of optimization at the detector design level. Several examples of event classification are provided, ranging from differentiation between the detector volumes and an efficient rejection of instrumental light noise, to some sensitivity to the particle type, such as stopping muons, ortho-positronium formation, alpha particles as well as electrons and positrons. In combination with other techniques the method is expected to allow for a versatile and more efficient background rejection in the future, especially if detector optimization is taken into account at the design level.
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