Quantum Benchmarking of High-Fidelity Noise-Biased Operations on a Detuned-Kerr-Cat Qubit

Kavli Affiliate: Ke Wang

| First 5 Authors: Bingcheng Qing, Bingcheng Qing, , ,

| Summary:

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 tomography
and dihedral randomized benchmarking, achieving high local gate fidelities,
with $mathcalF[Z(pi/2)]=99.2%$ and $mathcalF[X(pi/2)]=92.5%$.
Notably, the noise bias of the detuned Kerr-cat qubit approaches 250, which
outperforms its resonant-Kerr-cat qubit counterparts as reported previously,
representing a new state-of-the-art performance benchmark for noise-biased
qubits. Moreover, our results reveal a critical overestimation of operational
noise bias inferred from bit-flip and phase-flip times alone, highlighting the
necessity of a precise and direct benchmarking for noise-biased qubit
operations. Our work thus establishes a framework for systematically
characterizing and validating the performance of quantum operations in
structured-noise architectures, which lays the groundwork for implementing
efficient quantum error correction in next-generation architectures.

| Search Query: ArXiv Query: search_query=au:”Ke Wang”&id_list=&start=0&max_results=3

Read More