Improving Transmon Qubit Performance with Fluorine-based Surface Treatments

• URL: http://arxiv.org/abs/2507.08089v1
• Date: Thu, 10 Jul 2025 18:02:58 GMT
• Title: Improving Transmon Qubit Performance with Fluorine-based Surface Treatments
• Authors: Michael A. Gingras, Bethany M. Niedzielski, Kevin A. Grossklaus, Duncan Miller, Felipe Contipelli, Kate Azar, Luke D. Burkhart, Gregory Calusine, Daniel Davis, Renée DePencier Piñero, Jeffrey M. Gertler, Thomas M. Hazard, Cyrus F. Hirjibehedin, David K. Kim, Jeffrey M. Knecht, Alexander J. Melville, Christopher O'Connell, Robert A. Rood, Ali Sabbah, Hannah Stickler, Jonilyn L. Yoder, William D. Oliver, Mollie E. Schwartz, Kyle Serniak,
• Abstract summary: Two fluorine-based wet etches are used to treat the silicon surface underneath the Josephson junctions (JJs) of fixed-frequency transmon qubits.<n>Surface treatments result in significantly improved energy relaxation times for the highest performing process.
• Score: 25.973305185093782
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Reducing materials and processing-induced decoherence is critical to the development of utility-scale quantum processors based on superconducting qubits. Here we report on the impact of two fluorine-based wet etches, which we use to treat the silicon surface underneath the Josephson junctions (JJs) of fixed-frequency transmon qubits made with aluminum base metallization. Using several materials analysis techniques, we demonstrate that these surface treatments can remove germanium residue introduced by our JJ fabrication with no other changes to the overall process flow. These surface treatments result in significantly improved energy relaxation times for the highest performing process, with median $T_1=334~\mu$s, corresponding to quality factor $Q=6.6\times10^6$. This result suggests that the metal-substrate interface directly underneath the JJs was a major contributor to microwave loss in these transmon qubit circuits prior to integration of these surface treatments. Furthermore, this work illustrates how materials analysis can be used in conjunction with quantum device performance metrics to improve performance in superconducting qubits.

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