Abstract: This article reports the first measurement of prompt chi(c1) and chi(c2) charmonium production in nuclear collisions at Large Hadron Collider energies. The cross-section ratio sigma(chi(c2))/sigma(chi(c1)) is measured in pPb collisions at root s(NN) = 8.16 TeV, collected with the LHCb experiment. The chi(c1,2) states are reconstructed via their decay to a J/psi meson, subsequently decaying into a pair of oppositely charged muons, and a photon, which is reconstructed in the calorimeter or via its conversion in the detector material. The cross-section ratio is consistent with unity in the two considered rapidity regions. Comparison with a corresponding cross-section ratio previously measured by the LHCb Collaboration in pp collisions suggests that chi(c1) and chi(c2) states are similarly affected by nuclear effects occurring in pPb collisions.

Abstract: Proto-neutron stars forming a few seconds after core-collapse supernovae are hot and dense environments where hyperons can be efficiently produced by weak processes. By making use of various state-of-the-art supernova simulations combined with the proper extensions of the equations of state including Lambda hyperons, we calculate the cooling of the star induced by the emission of dark particles X-0 through the decay Lambda -> nX(0). Comparing this novel energy-loss process to the neutrino cooling of SN 1987A allows us to set a stringent upper limit on the branching fraction, BR(Lambda -> nX(0)) <= 8 x 10(-9), that we apply to massless dark photons and axions with flavor-violating couplings to quarks. We find that the new supernova bound can be orders of magnitude stronger than other limits in dark-sector models.

Abstract: Achieving a precise description of the internal structure of hadrons is crucial for deciphering the hidden properties and symmetries of fundamental particles. It is a hard task since there are several bottlenecks in obtaining theoretical predictions starting from first principles. In order to complement highly accurate experiments, it is necessary to use ingenious strategies to impose constraints from the theory side. In this article, we describe how photons can be used to unveil the internal structure of hadrons. We explore how to describe NLO QCD plus LO QED corrections to hadron plus photon production at colliders and discuss the impact of these effects on the experimental measurements.

Abstract: A search for a heavy neutral Higgs boson, A, decaying into a Z boson and another heavy Higgs boson, H, is performed using a data sample corresponding to an integrated luminosity of 139 fb(-1) from proton-proton collisions at root s = 13 TeV recorded by the ATLAS detector at the LHC. The search considers the Z boson decaying into electrons or muons and the H boson into a pair of b-quarks or W bosons. The mass range considered is 230-800 GeV for the A boson and 130-700 GeV for the H boson. The data are in good agreement with the background predicted by the Standard Model, and therefore 95% confidence-level upper limits for sigma x B( A -> ZH) x B(H -> bb or H -> WW) are set. The upper limits are in the range 0.0062-0.380 pb for the H. bb channel and in the range 0.023-8.9 pb for the H -> WW channel. An interpretation of the results in the context of two-Higgs-doublet models is also given.

Abstract: The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. We do this by encoding and decoding the graphical representation of background events in the XENONnT experiment with a convolutional variational autoencoder. We describe a methodology that utilizes the `anomaly score' derived from the reconstruction loss of the convolutional variational autoencoder as well as a pre-trained standard convolutional neural network, in a semi-supervised fashion. Indeed, we observe that optimum results are obtained only when both unsupervised and supervised anomaly scores are considered together. A data set that has a higher proportion of anomaly score is deemed anomalous and deserves further investigation. Contrary to classical analyses, in principle all information about the events is used, preventing unnecessary information loss. Lastly, we demonstrate the reach of learning-focused anomaly detection in this context by comparing results with classical inference, observing that, if tuned properly, these techniques have the potential to outperform likelihood-based methods.