Abstract: This Letter describes a search for narrowly resonant new physics using a machine -learning anomaly detection procedure that does not rely on signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search A -> BC, for m(A) similar to O(TeV), m(B), m(C) similar to O(100 GeV) and B, C are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full run 2 root s = 13 TeV pp collision dataset of 139 fb(-1) recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV, Cross-section limits for narrow -width A, B, and C particles vary with m(A), m(B), and m(C). For example, when m(A) = 3 TeV and m(B) greater than or similar to 200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on m(C). For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that B and C are standard model bosons.

Abstract: The observation of forward proton scattering in association with lepton pairs (e(+)e(-) + p or mu(+)mu(-) + p) produced via photon fusion is presented. The scattered proton is detected by the ATLAS Forward Proton spectrometer, while the leptons are reconstructed by the central ATLAS detector. Proton-proton collision data recorded in 2017 at a center-of-mass energy of root s = 13 TeV are analyzed, corresponding to an integrated luminosity of 14.6 fb(-1). A total of 57 (123) candidates in the ee + p (mu μ+ p) final state arc selected, allowing the background-only hypothesis to be rejected with a significance exceeding 5 standard deviations in each channel. Proton-tagging techniques are introduced for cross-section measurements in the fiducial detector acceptance, corresponding to sigma(ee)(+p) = 11.0 +/- 2.6(stat) 1.2(syst) +/- 0.3(lumi) and sigma(mu)(mu+)(p) = 7.2 +/- 1.6(stat) +/- 0.9(syst) 0.2(lumi) fb in the dielectron and dimuon channel, respectively.

Abstract: A search is performed for delayed and nonpointing photons originating from the displaced decay of a neutral long-lived particle (LLP). The analysis uses the full run 2 dataset of proton-proton collisions delivered by the LHC at a center-of-mass energy of pffisffi 1/4 13 TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb-1. The capabilities of the ATLAS electromagnetic calorimeter are exploited to precisely measure the arrival times and trajectories of photons. The results are interpreted in a scenario where the LLPs are pair produced in exotic decays of the 125 GeV Higgs boson, and each LLP subsequently decays into a photon and a particle that escapes direct detection, giving rise to missing transverse momentum. No significant excess is observed above the expectation due to Standard Model background processes. The results are used to set upper limits on the branching ratio of the exotic decay of the Higgs boson. A model-independent limit is also set on the production of photons with large values of displacement and time delay.

Abstract: A search is presented for a heavy resonance Y decaying into a Standard Model Higgs boson H and a new particle X in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at root s =13 TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139 fb(-1). The search targets the high Y-mass region, where the H and X have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted X particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark X decay into two quarks, covering topologies where the X is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into bb, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section sigma(pp -> Y -> XH -> qqbb) for signals with m(Y) between 1.5 and 6 TeV and m(X) between 65 and 3000 GeV.

Abstract: A search for the charged-lepton-flavor-violating process Z -> e μis presented, using 139 fb(-1) of root s = 13 TeV pp collision data collected by the ATLAS experiment at the LHC. An excess in the e μinvariant mass spectrum near the Z boson mass would be a striking signature of new physics. No excess is observed, and an upper limit B(Z -> e mu) < 2.62 x 10(-7) is placed on the branching fraction at 95% confidence level, which is the most stringent limit to date.