Search for high-mass dilepton resonances using139 fb −1 of p p collision data collected at √ s = 13 TeV with the ATLAS detectorThe ATLAS Collaboration A search for high-mass dielectron and dimuon resonances in the mass range of 250 GeV to 6 TeV is presented. The data were recorded by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of √ s = 13 TeV during Run 2 of the Large Hadron Collider and correspond to an integrated luminosity of 139 fb −1 . A functional form is fitted to the dilepton invariant-mass distribution to model the contribution from background processes, and a generic signal shape is used to determine the significance of observed deviations from this background estimate. No significant deviation is observed and upper limits are placed at the 95% confidence level on the fiducial cross-section times branching ratio for various resonance width hypotheses. The derived limits are shown to be applicable to spin-0, spin-1 and spin-2 signal hypotheses. For a set of benchmark models, the limits are converted into lower limits on the resonance mass and reach 4.5 TeV for the E 6 -motivated Z ψ boson. Also presented are limits on Heavy Vector Triplet model couplings.ATLAS [14-16] is a multipurpose detector with a forward-backward symmetric cylindrical geometry with respect to the LHC beam axis.1 The innermost layers consist of tracking detectors in the pseudorapidity range |η| < 2.5. This inner detector (ID) is surrounded by a thin superconducting solenoid that provides a 1 ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and the z-axis along the beam pipe. The x-axis points from the IP to the centre of the LHC ring, and the y-axis points upwards. Cylindrical coordinates (r, φ) are used in the transverse plane, φ being the azimuthal angle around the z-axis. The pseudorapidity is defined in terms of the polar angle θ as η = − ln tan(θ/2). Angular distance is measured in units of ∆R ≡ (∆η) 2 + (∆φ) 2 .

We report first observations of deterministic phase- and resonance-controlled all-optical electromagnetically induced transparency in multiple coupled photonic crystal cavities. The full-range tuning of coherently coupled cavity-cavity phase and resonances allow observations of transparency resonance in dark states with lifetimes longer than incoherently summed individual cavities. Supported by theoretical analyses, our multipump beam approach allows arbitrary control in two and three coupled cavities, while the standing-wave wavelength-scale photon localization allows direct scalability for chip-scale optical pulse trapping and coupled-cavity QED.

This paper presents results of searches for the electroweak production of supersymmetric particles in models with compressed mass spectra. The searches use 139 fb −1 of ffiffi ffi s p ¼ 13 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events with missing transverse momentum and two same-flavor, oppositely charged, low-transverse-momentum leptons are selected, and are further categorized by the presence of hadronic activity from initial-state radiation or a topology compatible with vector-boson fusion processes. The data are found to be consistent with predictions from the Standard Model. The results are interpreted using simplified models of R-parity-conserving supersymmetry in which the lightest supersymmetric partner is a neutralino with a mass similar to the lightest chargino, the second-to-lightest neutralino, or the slepton. Lower limits on the masses of charginos in different simplified models range from 193 to 240 GeV for moderate mass splittings, and extend down to mass splittings of 1.5 to 2.4 GeV at the LEP chargino bounds (92.4 GeV). Similar lower limits on degenerate light-flavor sleptons extend up to masses of 251 GeV and down to mass splittings of 550 MeV. Constraints on vector-boson fusion production of electroweak SUSY states are also presented.

This paper presents the Neural Network Verification (NNV) software tool, a set-based verification framework for deep neural networks (DNNs) and learning-enabled cyber-physical systems (CPS). The crux of NNV is a collection of reachability algorithms that make use of a variety of set representations, such as polyhedra, star sets, zonotopes, and abstract-domain representations. NNV supports both exact (sound and complete) and over-approximate (sound) reachability algorithms for verifying safety and robustness properties of feed-forward neural networks (FFNNs) with various activation functions. For learning-enabled CPS, such as closed-loop control systems incorporating neural networks, NNV provides exact and over-approximate reachability analysis schemes for linear plant models and FFNN controllers with piecewise-linear activation functions, such as ReLUs. For similar neural network control systems (NNCS) that instead have nonlinear plant models, NNV supports overapproximate analysis by combining the star set analysis used for FFNN controllers with zonotope-based analysis for nonlinear plant dynamics building on CORA. We evaluate NNV using two real-world case studies: the first is safety verification of ACAS Xu networks, and the second deals with the safety verification of a deep learning-based adaptive cruise control system.

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