In this paper we report the use of superconducting transmon qubit in a 3D cavity for quantum machine learning and photon counting applications. We first describe the realization andcharacterization of a transmon qubit coupled to a 3D resonator, providing a detailed description of the simulation framework and of the experimental measurement of important parameters, like the dispersive shift and the qubit anharmonicity. We then report on a Quantum Machine Learning application implemented on the single-qubit device to fit the u-quark parton distribution function of the proton. In the final section of the manuscript we present a new microwave photon detection scheme based on two qubits coupled to the same 3D resonator. This could in principle decrease the dark count rate, favouring applications like axion dark matter searches.
Quantum Sensing is a rapidly expanding research field that finds one of its applications in Fundamental Physics, as the search for Dark Matter. Recent developments in the fabricationof superconducting qubits are contributing to driving progress in Quantum Sensing. Such devices have already been successfully applied in detecting few-GHz single photons via Quantum Non-Demolition measurement (QND). This technique allows us to detect the presence of the same photon multiple times without absorbing it, with remarkable sensitivity improvements and dark count rate suppression in experiments based on high-precision microwave photon detection, such as Axions and Dark Photons search experiments. In this context, the INFN Qub-IT project goal is to realize an itinerant single-photon counter based on superconducting qubits that will exploit QND. The simulation step is fundamental for optimizing the design before manufacturing and finally characterizing the fabricated chip in a cryogenic environment. In this study we present Qub-IT’s status towards the characterization of its first superconducting transmon qubit devices, illustrating their design and simulation.