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NEXT Collaboration(Adams, C. et al), Carcel, S., Carrion, J. V., Diaz, J., Felkai, R., Lopez-March, N., et al. (2021). Sensitivity of a tonne-scale NEXT detector for neutrinoless double-beta decay searches. J. High Energy Phys., 08(8), 164–24pp.
Abstract: The Neutrino Experiment with a Xenon TPC (NEXT) searches for the neutrinoless double-beta (0 nu beta beta) decay of Xe-136 using high-pressure xenon gas TPCs with electroluminescent amplification. A scaled-up version of this technology with about 1 tonne of enriched xenon could reach in less than 5 years of operation a sensitivity to the half-life of 0 nu beta beta decay better than 10(27) years, improving the current limits by at least one order of magnitude. This prediction is based on a well-understood background model dominated by radiogenic sources. The detector concept presented here represents a first step on a compelling path towards sensitivity to the parameter space defined by the inverted ordering of neutrino masses, and beyond.
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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. (2021). Jet energy scale and resolution measured in proton-proton collisions at root s = 13 TeV with the ATLAS detector. Eur. Phys. J. C, 81(8), 689–49pp.
Abstract: Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36-81 fb-1 of proton-proton collision data with a centre-of-mass energy of root s=13 TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti-kt jet algorithm with radius parameter R=0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets (|eta|<1.2) vary from 1% for a wide range of high-pT jets (250<pT<2000 GeV), to 5% at very low pT (20 GeV) and 3.5% at very high pT (>2.5 TeV). The relative jet energy resolution is measured and ranges from (24 +/- 1.5)% at 20 GeV to (6 +/- 0.5)% at 300 GeV.
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Cottin, G., Helo, J. C., Hirsch, M., Titov, A., & Wang, Z. S. (2021). Heavy neutral leptons in effective field theory and the high-luminosity LHC. J. High Energy Phys., 09(9), 039–34pp.
Abstract: Heavy neutral leptons (HNLs) with masses around the electroweak scale are expected to be rather long-lived particles, as a result of the observed smallness of the active neutrino masses. In this work, we study long-lived HNLs in NRSMEFT, a Standard Model (SM) extension with singlet fermions to which we add non-renormalizable operators up to dimension-6. Operators which contain two HNLs can lead to a sizable enhancement of the production cross sections, compared to the minimal case where HNLs are produced only via their mixing with the SM neutrinos. We calculate the expected sensitivities for the ATLAS detector and the future far-detector experiments: AL3X, ANUBIS, CODEX-b, FASER, MATHUSLA, and MoEDAL-MAPP in this setup. The sensitive ranges of the HNL mass and of the active-heavy mixing angle are much larger than those in the minimal case. We study both, Dirac and Majorana, HNLs and discuss how the two cases actually differ phenomenologically, for HNL masses above roughly 100 GeV.
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Ling, P., Dai, X. H., Du, M. L., & Wang, Q. (2021). Prompt production of the hidden charm pentaquarks in the LHC. Eur. Phys. J. C, 81(9), 819–15pp.
Abstract: Motivated by the observation of the first hidden charm pentaquarks by the LHCb collaboration in 2015 and the updated analysis with an order-of-magnitude larger data set in 2019, we estimate their cross sections for the prompt production as well as their heavy quark spin partners, in the Sigma(()(c)*()) (D) over bar (()*()) hadronic molecular picture, at the center-of-mass energy 7 TeV in the pp collision. Their cross sections are several nb and we would expect several tens hidden charm pentaquark events in the LHC based on its current integrated luminosity. The cross sections show a sizable deviation of the cross sections for hidden charm pentaquarks with the third isospin component Iz = + 1/2 (P-c(+)) from those with Iz = – 1/2 (P-c(0)). The cross sections decrease dramatically with the increasing transverse momentum. Our study can also tell where to search for the missing hidden charm pentaquarks. The confirmation of the complete hidden charm pentaquarks in the heavy quark symmetry would further verify their Sigma(()(c)*()) (D) over bar (()*()) molecular interpretation. In addition, the relative strength among these cross sections for pentaquarks can help us to identify the quantum numbers of the P-c(4440) and P-c(4457).
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van Beekveld, M., Caron, S., Hendriks, L., Jackson, P., Leinweber, A., Otten, S., et al. (2021). Combining outlier analysis algorithms to identify new physics at the LHC. J. High Energy Phys., 09(9), 024–33pp.
Abstract: The lack of evidence for new physics at the Large Hadron Collider so far has prompted the development of model-independent search techniques. In this study, we compare the anomaly scores of a variety of anomaly detection techniques: an isolation forest, a Gaussian mixture model, a static autoencoder, and a beta-variational autoencoder (VAE), where we define the reconstruction loss of the latter as a weighted combination of regression and classification terms. We apply these algorithms to the 4-vectors of simulated LHC data, but also investigate the performance when the non-VAE algorithms are applied to the latent space variables created by the VAE. In addition, we assess the performance when the anomaly scores of these algorithms are combined in various ways. Using supersymmetric benchmark points, we find that the logical AND combination of the anomaly scores yielded from algorithms trained in the latent space of the VAE is the most effective discriminator of all methods tested.
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