Evidence for unexpectedly low quasiparticle generation rates across Josephson junctions of driven superconducting qubits

Recent studies find that even drives far below the superconducting gap frequency may cause drive-induced quasiparticle generation (QPG) across Josephson junctions (JJs) of superconducting qubits (SCQs), posing a serious concern for fault-tolerant superconducting quantum computing (FTSQC). Nonetheless, quantitative experimental estimation on QPG rates has remained vague. Here, we investigate QPG using strongly driven SCQs, reaching qubit drive amplitudes up to $2π\times$300 GHz by applying intense drive fields through the readout resonators. The resonator nonlinear responses enable quantification of the energy loss at SCQs, including the contribution from QPG. Surprisingly, the estimated total energy loss rates are far lower than those expected by the Floquet-Markov formalism with QPG as the sole loss mechanism. Meanwhile, calculations that incorporate high-frequency cutoffs (HFCs) in the QPG conductance at approximately 17-20 GHz effectively explain the experimental observations. These results suggest limitations in either the QPG conductance model or the Markovian treatment of the QPG processes. Both possibilities possess crucial implications for handling QPG problems toward FTSQC and for a more deeper understanding of Josephson junctions.

💡 Research Summary

The advancement of superconducting quantum computing (SCQ) relies heavily on maintaining long coherence times, which is significantly threatened by the generation of quasiparticles (QPG) within the Josephson junctions (JJs) of superconducting qubits. A major concern in the field is that even drive frequencies well below the superconducting gap can trigger QPG, leading to energy loss and decoherence. While this phenomenon is a known obstacle to achieving fault-tolerant superconducting quantum computing (FTSQC), previous experimental attempts to quantitatively estimate QPG rates have remained imprecise and vague.

In this study, the researchers investigated QPG using strongly driven superconducting qubits, employing an innovative approach that applies intense drive fields—reaching amplitudes up as high as 2π×300 GHz—through readout resonators. By analyzing the nonlinear responses of these resonators, the team was able to precisely quantify the energy loss occurring at the qubits, specifically isolating the contribution from QPG.

The most striking finding of this research is the significant discrepancy between experimental observations and the standard theoretical framework. According to the Floquet-Markov formalism, which assumes QPG as the primary loss mechanism, the predicted energy loss rates were substantially higher than what was actually measured in the lab. This unexpected finding suggests that the existing models for QPG-induced energy dissipation are overestimating the actual loss rates.

To reconcile this gap, the researchers introduced the concept of a High-Frequency Cutoff (HFC) into the QPG conductance model. By implementing a cutoff frequency in the range of approximately 17-20 GHz, the theoretical calculations aligned remarkably well with the experimental energy loss data. This discovery implies that the process of quasiparticle generation is not an unbounded phenomenon across all frequencies but is subject to a specific frequency-dependent suppression.

The implications of this work are profound for both fundamental physics and quantum engineering. The results suggest that either the current models for QPG conductance are incomplete, or the traditional Markovian treatment of QPG processes—which assumes the system’s future state depends only on its current state—is insufficient. Addressing these limitations is crucial for developing more accurate error-correction protocols and for designing the next generation of robust, fault-tolerant quantum hardware. This research provides a vital new direction for understanding the complex dynamics of Josephson junctions and for mitigating the impact of quasiparticles in scalable quantum architectures.