Quantum Benchmarking of High-Fidelity Noise-Biased Operations on a Detuned-Kerr-Cat Qubit
Bingcheng Qing, Ahmed Hajr, Ke Wang, Gerwin Koolstra, Long B. Nguyen, Jordan Hines, Irwin Huang, Bibek Bhandari, Larry Chen, Ziqi Kang, Christian J\"unger, Noah Goss, Nikitha Jain, Hyunseong Kim, Kan-Heng Lee, Akel Hashim, Nicholas E. Frattini, Zahra Pedramrazi, Justin Dressel

TL;DR
This paper demonstrates high-fidelity quantum operations on a noise-biased detuned Kerr-cat qubit, providing a comprehensive benchmarking framework and establishing a new performance benchmark for noise-biased quantum hardware.
Contribution
It develops a control toolbox and benchmarking methods for a scalable noise-biased Kerr-cat qubit, achieving state-of-the-art noise bias and high gate fidelities.
Findings
Achieved gate fidelities of 99.2% for Z(π/2) and 92.5% for X(π/2) gates.
Noise bias approaches 250, surpassing previous Kerr-cat qubits.
Direct benchmarking reveals overestimation of noise bias from simpler metrics.
Abstract
Ubiquitous noises in quantum systems remain a key obstacle to building quantum computers, necessitating the use of quantum error correction codes. Recently, error-correcting codes tailored for noise-biased systems have been shown to offer high fault-tolerance thresholds and reduced hardware overhead, positioning noise-biased qubits as promising candidates for building universal quantum computers. However, quantum operations on these platforms remain challenging, and their noise structures have not yet been rigorously benchmarked to the same extent as those of conventional quantum hardware. In this work, we develop a comprehensive quantum control toolbox for a scalable noise-biased qubit, detuned Kerr-cat qubit, including initialization, universal single-qubit gates and quantum non-demolition readout. We systematically characterize the noise structure of these operations using gate set…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum Mechanics and Applications
