Abstract: The NA62 experiment at the CERN SPS reports the first search for K+ -> pi(+) nu(nu) over bar using the decay-in-flight technique, based on a sample of 1.21 x10(11) K+ decays collected in 2016. The single event sensitivity is 3.15 x10(-10), corresponding to 0.267 Standard Model events. One signal candidate is observed while the expected background is 0.152 events. This leads to an upper limit of 14 x10(-10) on the K+ -> pi(+) nu(nu) over bar branching ratio at 95% CL.

Abstract: We show that a good description of the Upsilon(10860) properties, in particular the mass, the e(+) e(-) leptonic widths and the pi(+) pi(-) Upsilon(ns) (n = 1, 2, 3) production rates, can be obtained under the assumption that Upsilon(10860) is a mixing of the conventional Upsilon(5s) quark model state with the lowest P-wave hybrid state.

Abstract: For the Phase-II Upgrade of the ATLAS detector at CERN, the current ATLAS Inner Detector will be replaced with the ATLAS Inner Tracker (ITk). The ITk will be an all-silicon detector, consisting of a pixel tracker and a strip tracker. Sensors for the ITk strip tracker are required to have a low leakage current up to bias voltages of 500V to maintain a low noise and power dissipation. In order to minimise sensor leakage currents, particularly in the high-radiation environment inside the ATLAS detector, sensors are foreseen to be operated at low temperatures and to be manufactured from wafers with a high bulk resistivity of several k Omega.cm. Simulations showed the electric field inside sensors with high bulk resistivity to extend towards the sensor edge, which could lead to increased surface currents for narrow dicing edges. In order to map the electric field inside biased silicon sensors with high bulk resistivity, three diodes from ATLAS silicon strip sensor prototype wafers were studied with a monochromatic, micro-focused X-ray beam at the Diamond Light Source (Didcot, U.K.). For all devices under investigation, the electric field inside the diode was mapped and its dependence on the applied bias voltage was studied.

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.

Abstract: We extend the adiabatic regularization method by introducing an arbitrary mass scale μin the construction of the subtraction terms. This allows us to obtain, in a very robust way, the running of the coupling constants by demanding mu-invariance of the effective semiclassical (Maxwell-Einstein) equations. In particular, we get the running of the electric charge of perturbative quantum electrodynamics. Furthermore, the method brings about a renormalization of the cosmological constant and the Newtonian gravitational constant. The running obtained for these dimensionful coupling constants has new relevant (non-logarithmic) contributions, not predicted by dimensional regularization.