In this paper, we report the use of a superconducting transmon qubit in a 3D cavity for quantum machine learning and photon counting applications. We first describe the realization and characterization 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, such as the dispersive shift and the qubit anharmonicity. We then report on a Quantum Machine Learning application implemented on a 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, favoring applications like axion dark matter searches.
Characterization of a Transmon Qubit in a 3D Cavity for Quantum Machine Learning and Photon Counting
Fabio Chiarello;
2024
Abstract
In this paper, we report the use of a superconducting transmon qubit in a 3D cavity for quantum machine learning and photon counting applications. We first describe the realization and characterization 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, such as the dispersive shift and the qubit anharmonicity. We then report on a Quantum Machine Learning application implemented on a 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, favoring applications like axion dark matter searches.File | Dimensione | Formato | |
---|---|---|---|
applsci-14-01478-v2.pdf
accesso aperto
Tipologia:
Versione Editoriale (PDF)
Licenza:
Creative commons
Dimensione
5.1 MB
Formato
Adobe PDF
|
5.1 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.