Estimating gate-set properties from random sequences
arXiv:2110.13178 · doi:10.1038/s41467-023-39382-9
Abstract
With quantum computing devices increasing in scale and complexity, there is a growing need for tools that obtain precise diagnostic information about quantum operations. However, current quantum devices are only capable of short unstructured gate sequences followed by native measurements. We accept this limitation and turn it into a new paradigm for characterizing quantum gate-sets. A single experiment - random sequence estimation - solves a wealth of estimation problems, with all complexity moved to classical post-processing. We derive robust channel variants of shadow estimation with close-to-optimal performance guarantees and use these as a primitive for partial, compressive and full process tomography as well as the learning of Pauli noise. We discuss applications to the quantum gate engineering cycle, and propose novel methods for the optimization of quantum gates and diagnosing cross-talk.
10+17 pages, 3 figures, replaced with final version
References in corpus (25)
- Supplementary information for "Quantum supremacy using a programmable superconducting processor"
- Randomized Benchmarking of Quantum Gates
- Robust randomized benchmarking of quantum processes
- Direct Fidelity Estimation from Few Pauli Measurements
- Evenly distributed unitaries: on the structure of unitary designs
- The randomized measurement toolbox
- Characterization of addressability by simultaneous randomized benchmarking
- Provably efficient machine learning for quantum many-body problems
- Gate Set Tomography
- Fermionic partial tomography via classical shadows
- Computational advantage of quantum random sampling
- Robust shadow estimation
- Theory of quantum system certification: a tutorial
- A general framework for randomized benchmarking
- Optimizing quantum process tomography with unitary 2-designs
- Experimental Characterization of Crosstalk Errors with Simultaneous Gate Set Tomography
- Shadow process tomography of quantum channels
- Statistical analysis of randomized benchmarking
- Matchgate benchmarking: Scalable benchmarking of a continuous family of many-qubit gates
- Modeling and mitigation of cross-talk effects in readout noise with applications to the Quantum Approximate Optimization Algorithm
- Quantum Channel Marginal Problem
- Estimating gate-set properties from random sequences
- Compressive gate set tomography
- Towards a general framework of Randomized Benchmarking incorporating non-Markovian Noise
- Randomized linear gate set tomography
Cited by in corpus (20)
- Shallow shadows: Expectation estimation using low-depth random Clifford circuits
- Classical shadows with Pauli-invariant unitary ensembles
- Estimating gate-set properties from random sequences
- Demonstration of Robust and Efficient Quantum Property Learning with Shallow Shadows
- A Practical Introduction to Benchmarking and Characterization of Quantum Computers
- Tensor network noise characterization for near-term quantum computers
- Randomized measurement protocols for lattice gauge theories
- Operational Markovianization in Randomized Benchmarking
- Randomised benchmarking for universal qudit gates
- Group twirling and noise tailoring for multi-qubit controlled phase gates
- Hands-on Introduction to Randomized Benchmarking
- Robust Estimation of Nonlinear Properties of Quantum Processes
- Holographic Classical Shadow Tomography
- Bosonic randomized benchmarking with passive transformations
- Counting collisions in random circuit sampling for benchmarking quantum computers
- Benchmarking non-Clifford gates using only Pauli twirling group
- Classical Shadows with Improved Median-of-Means Estimation
- Efficient Characterization of Coherent and Correlated Low-Degree Noise in Layers of Gates
- The perfect entangler spectrum as a tool to analyze crosstalk
- Reducing Complexity of Shadow Process Tomography with Generalized Measurements