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Pich, A., Platschorre, A., & Reig, M. (2023). Electroweak mass difference of mesons. Phys. Rev. D, 108(9), 094044–6pp.
Abstract: We consider electroweak gauge boson corrections to the masses of pseudoscalar mesons to next to leading order in alpha s and 1/NC. The pion mass shift induced by the Z boson is shown to be m pi +/- – m pi 0 = -0.00201(12) MeV. While being small compared to the electromagnetic mass shift, the prediction lies about a factor of similar to 4 above the precision of the current experimental measurement and a factor O(10) below the precision of current lattice calculations. This motivates future implementations of these electroweak gauge boson effects on the lattice. Finally, we consider beyond standard model contributions to the pion mass difference.
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Karan, A., Miralles, V., & Pich, A. (2024). Updated global fit of the aligned two-Higgs-doublet model with heavy scalars. Phys. Rev. D, 109(3), 035012–29pp.
Abstract: An updated global fit on the parameter-space of the aligned two-Higgs-doublet model is performed with the help of the open-source package HEPfit, assuming the Standard-Model Higgs to be the lightest scalar. No new sources of CP violation, other than the phase in the Cabibbo-Kobayashi-Maskawa matrix of the Standard Model, are considered. A similar global fit was previously performed by O. Eberhardt et al. [Global fits in the aligned two-Higgs-doublet model, J. High Energy Phys. 05 (2021) 005] with a slightly different set of parameters. Our updated fit incorporates improved analyses of the theoretical constraints required for the perturbative unitarity and boundedness of the scalar potential from below, additional flavor observables and updated data on direct searches for heavy scalars at the LHC, Higgs signal strengths, and electroweak precision observables. Although not included in the main fit, the implications of the CDF measurement of the W +/- mass are also discussed.
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ATLAS Collaboration(Aad, G. et al), Aikot, A., Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., et al. (2023). Pursuit of paired dijet resonances in the Run 2 dataset with ATLAS. Phys. Rev. D, 108(11), 112005–30pp.
Abstract: New particles with large masses that decay into hadronically interacting particles are predicted by many models of physics beyond the Standard Model. A search for a massive resonance that decays into pairs of dijet resonances is performed using 140 fb(-1) of proton-proton collisions at ffiffiffisp root s = 13 TeV recorded by the ATLAS detector during Run 2 of the Large Hadron Collider. Resonances are searched for in the invariant mass of the tetrajet system, and in the average invariant mass of the pair of dijet systems. A data-driven background estimate is obtained by fitting the tetrajet and dijet invariant mass distributions with a four-parameter dijet function and a search for local excesses from resonant production of dijet pairs is performed. No significant excess of events beyond the Standard Model expectation is observed, and upper limits are set on the production cross sections of new physics scenarios.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). Search for heavy Higgs bosons with flavour-violating couplings in multi-lepton plus b-jets final states in pp collisions at 13 TeV with the ATLAS detector. J. High Energy Phys., 12(12), 081–68pp.
Abstract: A search for new heavy scalars with flavour-violating decays in final states with multiple leptons and b-tagged jets is presented. The results are interpreted in terms of a general two-Higgs-doublet model involving an additional scalar with couplings to the top-quark and the three up-type quarks (rho(tt),rho(tc), and rho(tu)). The targeted signals lead to final states with either a same-sign top-quark pair, three top-quarks, or four top-quarks. The search is based on a data sample of proton-proton collisions at root s = 13TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb(-1). Events are categorised depending on the multiplicity of light charged leptons (electrons or muons), total lepton charge, and a deep-neural-network output to enhance the purity of each of the signals. Masses of an additional scalar boson mH between 200- 630 GeV with couplings rho(tt) = 0.4, rho(tc) = 0.2, and rho(tu) = 0.2 are excluded at 95% confidence level. Additional interpretations are provided in models of R-parity violating supersymmetry, motivated by the recent flavour and ( g – 2) (mu) anomalies.
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Stoppa, F., Bhattacharyya, S., Ruiz de Austri, R., Vreeswijk, P., Caron, S., Zaharijas, G., et al. (2023). AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information. Astron. Astrophys., 680, A109–16pp.
Abstract: Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.
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