Abstract: The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using root s = 13 TeV proton-proton collision data with an integrated luminosity of 140 fb(-1) collected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points.

Abstract: Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Abstract: The objective of this work is the evaluation of the risk of suffering a multipactor discharge in an S-band dielectric-assist accelerating (DAA) structure for a compact low-energy linear particle accelerator dedicated to hadrontherapy treatments. A DAA structure consists of ultra-low loss dielectric cylinders and disks with irises which are periodically arranged in a metallic enclosure, with the advantage of having an extremely high quality factor and very high shunt impedance at room temperature, and it is therefore proposed as a potential alternative to conventional disk-loaded copper structures. However, it has been observed that these structures suffer from multipactor discharges. In fact, multipactor is one of the main problems of these devices, as it limits the maximum accelerating gradient. Because of this, the analysis of multipactor risk in the early design steps of DAA cavities is crucial to ensure the correct performance of the device after fabrication. In this paper, we present a comprehensive and detailed study of multipactor in our DAA design through numerical simulations performed with an in-house developed code based on the Monte-Carlo method. The phenomenology of the multipactor (resonant electron trajectories, electron flight time between impacts, etc.) is described in detail for different values of the accelerating gradient. It has been found that in these structures an ultra-fast non-resonant multipactor appears, which is different from the types of multipactor theoretically studied in the scientific literature. In addition, the effect of several low electron emission coatings on the multipactor threshold is investigated. Furthermore, a novel design based on the modification of the DAA cell geometry for multipactor mitigation is introduced, which shows a significant increase in the accelerating gradient handling capabilities of our prototype.