Abstract: .The U-235(n, f ) cross section was measured at n_TOF relative to Li-6(n, t) and B-10(n,alpha) , with high resolution ( L=183.49(2) m) and in a wide energy range (25meV-170keV) with 1.5% systematic uncertainty, making use of a stack of six samples and six silicon detectors placed in the neutron beam. This allowed us to make a direct comparison of the yields of the U-235(n, f ) and of the two reference reactions under the same experimental conditions, and taking into account the forward/backward emission asymmetry. A hint of an anomaly in the 10-30keV neutron energy range had been previously observed in other experiments, indicating a cross section systematically lower by several percent relative to major evaluations. The present results indicate that the cross section in the 9-18keV neutron energy range is indeed overestimated by almost 5% in the recently released evaluated data files ENDF/B-VIII.0 and JEFF3.3, as a consequence of a 7% overestimate in a single GMA node in the IAEA reference file. Furthermore, these new high-resolution data confirm the existence of resonance-like structures in the keV neutron energy region. The results here reported may lead to a reduction of the uncertainty in the 1-100keV neutron energy region. Finally, from the present data, a value of 249.7 +/- 1.4( stat )+/- 0.94( syst ) b<bold>eV has been extracted for the cross section integral between </bold>7.8 and 11eV, confirming the value of 247.5 +/- 3 b<bold>eV recently established as a standard</bold>.

Abstract: Theoretical interpretations of particle physics data, such as the determination of the Wilson coefficients of the Standard Model Effective Field Theory (SMEFT), often involve the inference of multiple parameters from a global dataset. Optimizing such interpretations requires the identification of observables that exhibit the highest possible sensitivity to the underlying theory parameters. In this work we develop a flexible open source frame-work, ML4EFT, enabling the integration of unbinned multivariate observables into global SMEFT fits. As compared to traditional measurements, such observables enhance the sensitivity to the theory parameters by preventing the information loss incurred when binning in a subset of final-state kinematic variables. Our strategy combines machine learning regression and classification techniques to parameterize high-dimensional likelihood ratios, using the Monte Carlo replica method to estimate and propagate methodological uncertainties. As a proof of concept we construct unbinned multivariate observables for top-quark pair and Higgs+Z production at the LHC, demonstrate their impact on the SMEFT parameter space as compared to binned measurements, and study the improved constraints associated to multivariate inputs. Since the number of neural networks to be trained scales quadratically with the number of parameters and can be fully parallelized, the ML4EFT framework is well-suited to construct unbinned multivariate observables which depend on up to tens of EFT coefficients, as required in global fits.

Abstract: We propose a novel statistical method to extend Fermi-LAT catalogues of highlatitude -y-ray sources below their nominal threshold. To do so, we rely on the determination of the differential source -count distribution of sub -threshold sources which only provides the statistical flux distribution of faint sources. By simulating ensembles of synthetic skies, we assess quantitatively the likelihood for pixels in the sky with relatively low -test statistics to be due to sources, therefore complementing the source -count distribution with spatial information. Besides being useful to orient efforts towards multi -messenger and multi -wavelength identification of new -y-ray sources, we expect the results to be especially advantageous for statistical applications such as cross -correlation analyses.

Abstract: A measurement of the polarisation of Wbosons produced in top-quark decays is presented, using proton-proton collision data at a centre-of-mass energy of v s= 13TeV. The data were collected by the ATLAS detector at the Large Hadron Collider and correspond to an integrated luminosity of 139fb(-1). The measurement is performed selecting t tevents decaying into final states with two charged leptons (electrons or muons) and at least two b-tagged jets. The polarisation is extracted from the differential cross-section distribution of the cos theta* variable, where theta(*) is the angle between the momentum direction of the charged lepton from the Wboson decay and the reversed momentum direction of the b-quark from the top-quark decay, both calculated in the Wboson rest frame. Parton-level results, corrected for the detector acceptance and resolution, are presented for the cos theta* angle. The measured fractions of longitudinal, left- and right-handed polarisation states are found to be f(0) = 0.684 +/- 0.005 (stat.)+/- 0.014 (syst.), f(L)= 0.318 +/- 0.003 (stat.)+/- 0.008 (syst.) and f(R)=-0.002 +/- 0.002 (stat.)+/- 0.014 (syst.), in agreement with the Standard Model prediction.

Abstract: Measurements and searches performed with the ATLAS detector at the CERN LHC often involve signatures with one or more prompt leptons. Such analyses are subject to 'fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria. These backgrounds often arise within a hadronic jet because of particle decays in the showering process, particle misidentification or particle interactions with the detector material. As it is challenging to model these processes with high accuracy in simulation, their estimation typically uses data-driven methods. Three methods for carrying out this estimation are described, along with their implementation in ATLAS and their performance.