Principles of quantum functional testing
arXiv:2209.11712 · doi:10.1103/PhysRevA.108.022602
Abstract
With increasing commercial availability of quantum information processing devices the need for testing them efficiently for their specified functionality will arise. Complete quantum channel characterization is out of the question for anything more than the simplest quantum channels for one or two qubits. Quantum functional testing leads to a decision problem with outcomes corresponding to rejection or acceptance of the claim of the producer that the device parameters are within certain specifications. In this context, we introduce and analyse three ingredients that can speed up this decision problem: iteration of the channel, efficient decision criteria, and non-greedy adaptive experimental design.
arXiv comment13 pages, 12 figures
References in corpus (43)
- Supplementary information for "Quantum supremacy using a programmable superconducting processor"
- Characterizing Quantum Supremacy in Near-Term Devices
- Quantum state tomography via compressed sensing
- Randomized Benchmarking of Quantum Gates
- Prescription for experimental determination of the dynamics of a quantum black box
- Many-body quantum state tomography with neural networks
- Robust randomized benchmarking of quantum processes
- Validating quantum computers using randomized model circuits
- Efficient quantum state tomography
- The Quantum Chernoff Bound
- Quantum Process Tomography: Resource Analysis of Different Strategies
- Efficient measurement of quantum gate error by interleaved randomized benchmarking
- Quantum Tomography via Compressed Sensing: Error Bounds, Sample Complexity, and Efficient Estimators
- Ancilla-assisted quantum process tomography
- Tomography of Quantum Operations
- Asymptotic Error Rates in Quantum Hypothesis Testing
- Efficient tomography of a quantum many-body system
- Robust Online Hamiltonian Learning
- Realization of quantum process tomography in NMR
- Gate Set Tomography
- Reliable Quantum State Tomography
- The Chernoff lower bound for symmetric quantum hypothesis testing
- Adaptive Bayesian Quantum Tomography
- The quantum Chernoff bound as a measure of distinguishability between density matrices: application to qubit and Gaussian states
- Theory of quantum system certification: a tutorial
- Randomized Benchmarking of Multi-Qubit Gates
- Self-guided quantum tomography
- Fundamental limits to quantum channel discrimination
- Systematic errors in current quantum state tomography tools
- Practical Bayesian Tomography
- Two-qubit spectroscopy of spatiotemporally correlated quantum noise in superconducting qubits
- Efficient and feasible state tomography of quantum many-body systems
- How to best sample a periodic probability distribution, or on the accuracy of Hamiltonian finding strategies
- Scalable on-chip quantum state tomography
- A Scalable Maximum Likelihood Method for Quantum State Tomography
- Deep reinforcement learning for quantum multiparameter estimation
- Neural-Network Heuristics for Adaptive Bayesian Quantum Estimation
- Selective and Efficient Quantum Process Tomography
- QInfer: Statistical inference software for quantum applications
- Randomized benchmarking for individual quantum gates
- High posterior density ellipsoids of quantum states
- Near-optimal quantum tomography: estimators and bounds
- Identifying nonclassicality from experimental data using artificial neural networks