Robust Calibration of a Universal Single-Qubit Gate-Set via Robust Phase Estimation
arXiv:1502.02677 · doi:10.1103/PhysRevA.92.062315
Abstract
An important step in building a quantum computer is calibrating experimentally implemented quantum gates to produce operations that are close to ideal unitaries. The calibration step involves estimating the systematic errors in gates and then using controls to correct the implementation. Quantum process tomography is a standard technique for estimating these errors, but is both time consuming, (when one only wants to learn a few key parameters), and is usually inaccurate without resources like perfect state preparation and measurement, which might not be available. With the goal of efficiently and accurately estimating specific errors using minimal resources, we develop a parameter estimation technique, which can gauge key systematic parameters (specifically, amplitude and off-resonance errors) in a universal single-qubit gate-set with provable robustness and efficiency. In particular, our estimates achieve the optimal efficiency, Heisenberg scaling, and do so without entanglement and entirely within a single-qubit Hilbert space. Our main theorem making this possible is a robust version of the phase estimation procedure of Higgins et al. [B. L. Higgins, New J. Phys. 11, 073023 (2009)].
Errata added; our error analysis is based on an incorrect assumption. However, our overall approach for robust calibration via phase estimation is still valid with a looser error bound - see the Errata before the Introduction for more information
References in corpus (6)
- Randomized Benchmarking of Quantum Gates
- Robust randomized benchmarking of quantum processes
- High-fidelity projective readout of a solid-state spin quantum register
- Randomized benchmarking and process tomography for gate errors in a solid-state qubit
- Phase estimation without a priori knowledge in the presence of loss
- Joint estimation of phase and phase diffusion for quantum metrology
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