ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). Measurements of differential cross sections of Higgs boson production through gluon fusion in the H → WW *→ eνμν final state at √s=13 TeV with the ATLAS detector. Eur. Phys. J. C, 83(9), 774–40pp.
Abstract: Higgs boson production via gluon-gluon fusion is measured in the WW *-> e nu μnu decay channel. The dataset utilized corresponds to an integrated luminosity of 139 fb(-1) collected by the ATLAS detector from root s = 13TeV proton-proton collisions delivered by the Large Hadron Collider between 2015 and 2018. Differential cross sections are measured in a fiducial phase space restricted to the production of at most one additional jet. The results are consistent with Standard Model expectations, derived using different Monte Carlo generators.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cantero, J., et al. (2023). Search for a light charged Higgs boson in t → H±b decays, with H± → cb, in the lepton plus jets final state in proton-proton collisions at √s=13 TeV with the ATLAS detector. J. High Energy Phys., 09(9), 004–52pp.
Abstract: A search for a charged Higgs boson, H-+/-, produced in top-quark decays, t -> H(+/-)b, is presented. The search targets H-+/- decays into a bottom and a charm quark, H-+/- -> cb. The analysis focuses on a selection enriched in top-quark pair production, where one top quark decays into a leptonically decaying W boson and a bottom quark, and the other top quark decays into a charged Higgs boson and a bottom quark. This topology leads to a lepton-plus-jets final state, characterised by an isolated electron or muon and at least four jets. The search exploits the high multiplicity of jets containing b-hadrons, and deploys a neural network classifier that uses the kinematic differences between the signal and the background. The search uses a dataset of proton-proton collisions collected at a centre-of-mass energy root s = 13TeV between 2015 and 2018 with the ATLAS detector at CERN's Large Hadron Collider, amounting to an integrated luminosity of 139 fb(-1). Observed (expected) 95% confidence-level upper limits between 0.15% (0.09%) and 0.42% (0.25%) are derived for the product of branching fractions B( t -> H-+/- b) x B( H +/- -> cb) for charged Higgs boson masses between 60 and 160 GeV, assuming the SM production of the top-quark pairs.
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Wang, D. (2023). Pantheon plus tomography and Hubble tension. Eur. Phys. J. C, 83(9), 813–12pp.
Abstract: The recently released Type Ia supernovae (SNe Ia) sample, Pantheon+, is an updated version of Pantheon and has very important cosmological implications. To explore the origin of the enhanced constraining power and internal correlations of datasets in different redshifts, we perform a comprehensively tomographic analysis of the Pantheon+ sample without and with the Cepheid host distance calibration, respectively. Specifically, we take two binning methods to analyze the Pantheon+ sample, i.e., equal redshift interval and equal supernovae number for each bin. For the case of equal redshift interval, after dividing the sample to 10 bins, the first bin in the redshift range z is an element of [0.00122, 0.227235] dominates the constraining power of the whole sample. For the case of equal supernovae number, the first three low redshift bins prefer a large matter fraction Omega(m) and only the sixth bin gives a relatively low cosmic expansion rate H-0. For both binning methods, we find no obvious evidence of evolution of H-0 and Omega(m) at the 2 sigma confidence level. The inclusion of the SHOES calibration can significantly compress the parameter space of background dynamics of the universe in each bin. When not considering the calibration, combining the Pantheon+ sample with cosmic microwave background, baryon acoustic oscillations, cosmic chronometers, galaxy clustering and weak lensing data, we give the strongest 1 sigma constraint H-0 = 67.88 +/- 0.42kms(-1) Mpc(-1). However, the addition of the calibration leads to a global shift of the parameter space from the combined constraint and H-0 = 68.66 +/- 0.42 km s(-1) Mpc(-1), which is inconsistent with the Planck-2018 result at about 2 sigma confidence level.
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LHCb Collaboration(Aaij, R. et al), Jaimes Elles, S. J., Jashal, B. K., Martinez-Vidal, F., Oyanguren, A., Rebollo De Miguel, M., et al. (2023). Search for the doubly heavy baryon Ξbc+ decaying to J/ψΞc+. Chin. Phys. C, 47(9), 093001–13pp.
Abstract: A first search for the Xi(+)(bc) -> J/psi Xi c+ decay is performed by the LHCb experiment with a data sample of proton-proton collisions, corresponding to an integrated luminosity of 9 fb(-1) recorded at centre-of-mass energies of 7, 8, and 13 TeV. Two peaking structures are seen with a local (global) significance of and standard deviations at masses of 6571 and 6694 MeV/c(2), respectively. Upper limits are set on the Xi(+)(bc) baryon production cross-section times the branching fraction relative to that of the B-c(+) -> J/psi Xi(+)(c) decay at centre-of-mass energies of 8 and 13 TeV, in the Xi(+)(bc) and in the rapidity and transverse-momentum ranges from 2.0 to 4.5 and 0 to, respectively. Upper limits are presented as a function of the Xi(+)(bc) mass and lifetime.
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Amerio, A., Cuoco, A., & Fornengo, N. (2023). Extracting the gamma-ray source-count distribution below the Fermi-LAT detection limit with deep learning. J. Cosmol. Astropart. Phys., 09(9), 029–39pp.
Abstract: We reconstruct the extra-galactic gamma-ray source-count distribution, or dN/dS, of resolved and unresolved sources by adopting machine learning techniques. Specifically, we train a convolutional neural network on synthetic 2-dimensional sky-maps, which are built by varying parameters of underlying source-counts models and incorporate the FermiLAT instrumental response functions. The trained neural network is then applied to the Fermi-LAT data, from which we estimate the source count distribution down to flux levels a factor of 50 below the Fermi-LAT threshold. We perform our analysis using 14 years of data collected in the (1, 10) GeV energy range. The results we obtain show a source count distribution which, in the resolved regime, is in excellent agreement with the one derived from cataloged sources, and then extends as dN/dS " S-2 in the unresolved regime, down to fluxes of 5 center dot 10-12 cm-2 s-1. The neural network architecture and the devised methodology have the flexibility to enable future analyses to study the energy dependence of the source-count distribution.
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