Transmon Qubit Modeling and Characterization for Dark Matter Search
Year: 2025
Type: article
Abstract: This study presents the design, simulation, and experimental characterization of a superconducting transmon qubit circuit prototype for potential applications in dark matter detection experiments. We describe a planar circuit design featuring two non-interacting transmon qubits, one with fixed frequency and the other flux tunable. Finite-element simulations were employed to extract key Hamiltonian parameters and optimize component geometries. The qubit was fabricated and then characterized at 20 mK, allowing for a comparison between simulated and measured qubit parameters. Good agreement was found for transition frequencies and anharmonicities (within 1% and 10% respectively) while coupling strengths exhibited larger discrepancies (30%). We discuss potential causes for measured coherence times falling below expectations (T1 ∼1-2 μs) and propose strategies for future design improvements. Notably, we demonstrate the application of a hybrid 3D-2D simulation approach for energy participation ratio evaluation, yielding a more accurate estimation of dielectric losses. This work represents an important first step in developing planar Quantum Non-Demolition (QND) single-photon counters for dark matter searches, particularly for axion and dark photon detection schemes.
Authors: Roberto Moretti, Danilo Labranca, Pietro Campana, Rodolfo Carobene, Marco Gobbo, Manuel A. Castellanos-Beltran, David Olaya, Peter F. Hopkins, Leonardo Banchi, Matteo Borghesi, Alessandro Candido, Stefano Carrazza, Hervè Atsè Corti, Alessandro D’Elia, Marco Faverzani, Elena Ferri, Angelo Nucciotti, Luca Origo, Andrea Pasquale, Alex Stephane Piedjou Komnang, Alessio Rettaroli, Simone Tocci, Claudio Gatti, Andrea Giachero
Institutions: University of Milano-Bicocca, National Institute of Standards and Technology, University of Florence, European Organization for Nuclear Research, Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Frascati, Istituto Nazionale di Fisica Nucleare, Sezione di Milano Bicocca, University of Milan
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,075
OpenAlex ID: W4416214620