Abstract: A Weyl structure is usually defined by an equivalence class of pairs (g, omega) related by Weyl transformations, which preserve the relation del g = omega circle times g, where g and omega denote the metric tensor and a 1-form field. An equivalent way of defining such a structure is as an equivalence class of conformally related metrics with a unique affine connection Gamma((omega)), which is invariant under Weyl transformations. In a standard Weyl structure, this unique connection is assumed to be torsion-free and have vectorial non-metricity. This second view allows us to present two different generalizations of standard Weyl structures. The first one relies on conformal symmetry while allowing for a general non-metricity tensor, and the other comes from extending the symmetry to arbitrary (disformal) transformations of the metric.

Abstract: We use a non-relativistic model to study the spectroscopy of a tetraquark composed of [cc][(c) over bar(c) over bar] in a diquark-antidiquark configuration. By numerically solving the Schrodinger equation with a Cornell-inspired potential, we separate the four-body problem into three two-body problems. Spin-dependent terms (spin-spin, spin-orbit and tensor) are used to describe the splitting structure of the c (c) over bar spectrum and are also extended to the interaction between diquarks. Recent experimental data on charmonium states are used to fix the parameters of the model and a satisfactory description of the spectrum is obtained. We find that the spin-dependent interaction is sizable in the diquark-antidiquark system, despite the heavy diquark mass, and also that the diquark has a finite size if treated in the same way as the c (c) over bar systems. We find that the lowest S-wave T-4c tetraquarks might be below their thresholds of spontaneous dissociation into low-lying charmonium pairs, while orbital and radial excitations would be mostly above the corresponding charmonium pair thresholds. Finally, we repeat the calculations without the confining part of the potential and obtain bound diquarks and bound tetraquarks. This might be relevant to the study of exotic charmonium in the quark-gluon plasma. The T4c states could be investigated in the forthcoming experiments at the LHC and Belle II.

Abstract: We analyze 7.3 yr of ANTARES high-energy neutrino and Fermi Large Area Telescope (LAT) gamma-ray data in search of cosmic neutrino + gamma-ray (nu + gamma) transient sources or source populations. Our analysis has the potential to detect either individual nu + gamma transient sources (durations delta t less than or similar to 1000 s), if they exhibit sufficient gamma-ray or neutrino multiplicity, or a statistical excess of nu + gamma transients of individually lower multiplicities. Individual high gamma-ray multiplicity events could be produced, for example, by a single ANTARES neutrino in coincidence with a LAT-detected gamma-ray burst. Treating ANTARES track and cascade event types separately, we establish detection thresholds by Monte Carlo scrambling of the neutrino data, and determine our analysis sensitivity by signal injection against these scrambled data sets. We find our analysis is sensitive to nu + gamma transient populations responsible for >5% of the observed gamma-coincident neutrinos in the track data at 90% confidence. Applying our analysis to the unscrambled data reveals no individual nu + gamma events of high significance; two ANTARES track + Fermi gamma-ray events are identified that exceed a once per decade false alarm rate threshold (p = 17%). No evidence for subthreshold nu + gamma source populations is found among the track (p = 39%) or cascade (p = 60%) events. Exploring a possible correlation of high-energy neutrino directions with Fermi gamma-ray sky brightness identified in previous work yields no added support for this correlation. While TXS.0506+056, a blazar and variable (nontransient) Fermi gamma-ray source, has recently been identified as the first source of high-energy neutrinos, the challenges in reconciling observations of the Fermi gamma-ray sky, the IceCube high-energy cosmic neutrinos, and ultrahigh-energy cosmic rays using only blazars suggest a significant contribution by other source populations. Searches for transient sources of high-energy neutrinos thus remain interesting, with the potential for either neutrino clustering or multimessenger coincidence searches to lead to discovery of the first nu + gamma transients.

Abstract: This paper describes a strategy for a general search used by the ATLAS Collaboration to find potential indications of new physics. Events are classified according to their final state into many event classes. For each event class an automated search algorithm tests whether the data are compatible with the Monte Carlo simulated expectation in several distributions sensitive to the effects of new physics. The significance of a deviation is quantified using pseudo-experiments. A data selection with a significant deviation defines a signal region for a dedicated follow-up analysis with an improved background expectation. The analysis of the data-derived signal regions on a new dataset allows a statistical interpretation without the large look-elsewhere effect. The sensitivity of the approach is discussed using Standard Model processes and benchmark signals of new physics. As an example, results are shown for 3.2fb-1 of proton-proton collision data at a centre-of-mass energy of 13TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 105 regions have been analysed. No significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.

Abstract: The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators. Performing statistically convergent scans of high-dimensional BSM theories is consequently challenging, and in practice unfeasible for very high-dimensional BSM theories. We present here a new machine learning method that accelerates the interpretation of LHC data, by learning the relationship between BSM theory parameters and data. As a proof-of-concept, we demonstrate that this technique accurately predicts natural SUSY signal events in two signal regions at the High Luminosity LHC, up to four orders of magnitude faster than standard techniques. The new approach makes it possible to rapidly and accurately reconstruct the theory parameters of complex BSM theories, should an excess in the data be discovered at the LHC.