Abstract: A search for rare B. D mu+ mu- decays is performed using proton-proton collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb-1. No significant signals are observed in the non-resonant mu+ mu- modes, and upper limits of B -> B0. D0 mu+ mu- < 5.1 x 10-8, B B+. D+ s mu+ mu- -> < 3.2 x 10-8, B -> B0 s. D0 mu+ mu--> < 1.6 x 10-7 and fc/fu center dot B B+ c. D+ s mu+ mu--> < 9.6 x 10-8 are set at the 95% confidence level, where fc and fu are the fragmentation fractions of a B meson with a c and u quark respectively in proton-proton collisions. Each result is either the first such measurement or an improvement by three orders of magnitude on an existing limit. Separate upper limits are calculated when the muon pair originates from a J/.. mu+ mu- decay. The branching fraction of B+ c. D+ s J/. multiplied by the fragmentation-fraction ratio is measured to be fc fu center dot B -> B+ c. D+ s J/.-> = (1.63 +/- 0.15 +/- 0.13) x 10-5, where the first uncertainty is statistical and the second systematic.

Abstract: A search for the dimuon decay of the Standard Model (SM) Higgs boson is performed using data corresponding to an integrated luminosity of 139 fb(-1) collected with the ATLAS detector in Run 2 pp collisions at root s = 13 TeV at the Large Hadron Collider. The observed (expected) significance over the background-only hypothesis for a Higgs boson with a mass of 125.09 GeV is 2.0 sigma (1.7 sigma). The observed upper limit on the cross section times branching ratio for pp -> H -> μμis 2.2 times the SM prediction at 95% confidence level, while the expected limit on a H -> μμsignal assuming the absence (presence) of a SM signal is 1.1(2.0). The best-fit value of the signal strength parameter, defined as the ratio of the observed signal yield to the one expected in the SM, is μ= 1.2 +/- 0.6.

Abstract: A search for the Xi(++)(cc) baryon through the Xi(++)(cc) -> D(+)pK(-)pi(+) decay is performed with a data sample corresponding to an integrated luminosity of 1.7 fb(-1) recorded by the LHCb experiment in pp collisions at a centre-of-mass energy of 13 TeV. No significant signal is observed in the mass range from the kinematic threshold of the decay to 3800 MeV/c(2). An upper limit is set on the ratio of branching fractions R = B(Xi(++)(cc) -> D(+)pK(-)pi(+))/B(Xi(++)(cc) -> A(c)(+) K- pi(+)pi(+)) with R < 1.7 (2.1) x 10(-2) at the 90% (95%) confidence level at the known mass of the Xi(++)(cc) state.

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.

Abstract: One factor limiting the current applicability extent of hadron therapy is the lack of a reliable method for real time treatment monitoring. The use of Compton imaging systems as monitors requires the correct reconstruction of the distribution of prompt gamma productions during patient irradiation. In order to extract the maximum information from all the measurable events, we implemented a spectral reconstruction method that assigns to all events a probability of being either partial or total energy depositions. The method, implemented in a list-mode maximum likelihood expectation maximization algorithm, generates a four dimensional image in the joint spatial-spectral domain, in which the voxels containing the emission positions and energies are obtained. The analytical model used for the system response function is also employed to derive an analytical expression for the sensitivity, which is calculated via Monte Carlo integration. The performance of the method is evaluated through reconstruction of various experimental and simulated sources with different spatial and energy distributions. The results show that the proposed method can recover the spectral and spatial information simultaneously, but only under the assumption of ideal measurements. The analysis of the Monte Carlo simulations has led to the identification of two important degradation sources: the mispositioning of the gamma interaction point and the missing energy recorded in the interaction. Both factors are related to the high energy transferred to the recoil electrons, which can travel far from the interaction point and even escape the detector. These effects prevent the direct application of the current method in more realistic scenarios. Nevertheless, experimental point-like sources have been accurately reconstructed and the spatial distributions and spectral emission of complex simulated phantoms can be identified.