Abstract: The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, due to the large dimensionality of the space of possible choices for geometry, detection technology, materials, data-acquisition, and information-extraction techniques, and the interdependence of the related parameters. On the other hand, massive potential gains in performance over standard, “experience-driven” layouts are in principle within our reach if an objective function fully aligned with the final goals of the instrument is maximized through a systematic search of the configuration space. The stochastic nature of the involved quantum processes make the modeling of these systems an intractable problem from a classical statistics point of view, yet the construction of a fully differentiable pipeline and the use of deep learning techniques may allow the simultaneous optimization of all design parameters.

Abstract: The mass of the Higgs boson is measured in the H→γγ decay channel, exploiting the high resolution of the invariant mass of photon pairs reconstructed from the decays of Higgs bosons produced in proton-proton collisions at a centre-of-mass energy s√=13 TeV. The dataset was collected between 2015 and 2018 by the ATLAS detector at the Large Hadron Collider, and corresponds to an integrated luminosity of 140 fb−1. The measured value of the Higgs boson mass is 125.17±0.11(stat.)±0.09(syst.) GeV and is based on an improved energy scale calibration for photons, whose impact on the measurement is about four times smaller than in the previous publication. A combination with the corresponding measurement using 7 and 8 TeV pp collision ATLAS data results in a Higgs boson mass measurement of 125.22±0.11(stat.)±0.09(syst.) GeV. With an uncertainty of 1.1 per mille, this is currently the most precise measurement of the mass of the Higgs boson from a single decay channel.

Abstract: The CP properties of the coupling between the Higgs boson and the top quark are investigated using 139 fb(-1) of proton-proton collision data recorded by the ATLAS experiment at the LHC at a centre-of-mass energy of root s = 13 TeV. The CP structure of the top quark-Higgs boson Yukawa coupling is probed in events with a Higgs boson decaying into a pair of b-quarks and produced in association with either a pair of top quarks, t (t) over barH or a single top quark, tH. Events containing one or two electrons or muons are used for the measurement. Multivariate techniques are used to select regions enriched in t (t) over barh and tH events, where dedicated SP-sensitive observables are exploited. In an extension of the Standard Model (SM) with a CP-odd admixture in the top-Higgs Yukawa coupling, the mixing angle between CP-even and CP-odd couplings is measured to be alpha = 11 degrees(+52 degrees)(-73 degrees) compatible with the SM prediction corresponding to alpha = 0.

Abstract: CompactLight is a Design Study funded by the European Union under the Horizon 2020 research and innovation funding programme, with Grant Agreement No. 777431. CompactLight was conducted by an International Collaboration of 23 international laboratories and academic institutions, three private companies, and five third parties. The project, which started in January 2018 with a duration of 48 months, aimed to design an innovative, compact, and cost-effective hard X-ray FEL facility complemented by a soft X-ray source to pave the road for future compact accelerator-based facilities. The result is an accelerator that can be operated at up to 1 kHz pulse repetition rate, beyond today's state of the art, using the latest concepts for high brightness electron photoinjectors, very high gradient accelerating structures in X-band, and novel short-period undulators. In this report, we summarize the main deliverable of the project: the CompactLight Conceptual Design Report, which overviews the current status of the design and addresses the main technological challenges.

Abstract: We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that forces the model to partially ignore high-gradients in the physical variables, achieved by introducing a suitable weighting function. The method relies on a set of hyperparameters that control how gradients are treated in the physical loss. The performance of our methodology is demonstrated by solving Riemann problems in special relativistic hydrodynamics, extending earlier studies with PINNs in the context of the classical Euler equations. The solutions obtained with the GA-PINN model correctly describe the propagation speeds of discontinuities and sharply capture the associated jumps. We use the relative l(2) error to compare our results with the exact solution of special relativistic Riemann problems, used as the reference ''ground truth'', and with the corresponding error obtained with a second-order, central, shock-capturing scheme. In all problems investigated, the accuracy reached by the GA-PINN model is comparable to that obtained with a shock-capturing scheme, achieving a performance superior to that of the baseline PINN algorithm in general. An additional benefit worth stressing is that our PINN-based approach sidesteps the costly recovery of the primitive variables from the state vector of conserved variables, a well-known drawback of grid-based solutions of the relativistic hydrodynamics equations. Due to its inherent generality and its ability to handle steep gradients, the GA-PINN methodology discussed in this paper could be a valuable tool to model relativistic flows in astrophysics and particle physics, characterized by the prevalence of discontinuous solutions.