Quantum Vulnerability Analysis to Accurate Estimate the Quantum Algorithm Success Rate
arXiv:2207.14446 · doi:10.1109/TQE.2023.3343625
Abstract
While quantum computers provide exciting opportunities for information processing, they currently suffer from noise during computation that is not fully understood. Incomplete noise models have led to discrepancies between quantum program success rate (SR) estimates and actual machine outcomes. For example, the estimated probability of success (ESP) is the state-of-the-art metric used to gauge quantum program performance. The ESP suffers poor prediction since it fails to account for the unique combination of circuit structure, quantum state, and quantum computer properties specific to each program execution. Thus, an urgent need exists for a systematic approach that can elucidate various noise impacts and accurately and robustly predict quantum computer success rates, emphasizing application and device scaling. In this article, we propose quantum vulnerability analysis (QVA) to systematically quantify the error impact on quantum applications and address the gap between current success rate (SR) estimators and real quantum computer results. The QVA determines the cumulative quantum vulnerability (CQV) of the target quantum computation, which quantifies the quantum error impact based on the entire algorithm applied to the target quantum machine. By evaluating the CQV with well-known benchmarks on three 27-qubit quantum computers, the CQV success estimation outperforms the estimated probability of success state-of-the-art prediction technique by achieving on average six times less relative prediction error, with best cases at 30 times, for benchmarks with a real SR rate above 0.1%. Direct application of QVA has been provided that helps researchers choose a promising compiling strategy at compile time.
11pages, 11 figures
References in corpus (18)
- Quantum Computing in the NISQ era and beyond
- Supplementary information for "Quantum supremacy using a programmable superconducting processor"
- Coupling Superconducting Qubits via a Cavity Bus
- Demonstration of Two-Qubit Algorithms with a Superconducting Quantum Processor
- Robust randomized benchmarking of quantum processes
- Complete Characterization of a Quantum Process: the Two-Bit Quantum Gate
- Quantum optimization using variational algorithms on near-term quantum devices
- Characterizing Quantum Gates via Randomized Benchmarking
- Characterization of addressability by simultaneous randomized benchmarking
- Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers
- Randomized Benchmarking of Multi-Qubit Gates
- Mitiq: A software package for error mitigation on noisy quantum computers
- Optimized Compilation of Aggregated Instructions for Realistic Quantum Computers
- An Experimental Microarchitecture for a Superconducting Quantum Processor
- Extracting Success from IBM's 20-Qubit Machines Using Error-Aware Compilation
- Scalable quantum computer with superconducting circuits in the ultrastrong coupling regime
- Systematic Crosstalk Mitigation for Superconducting Qubits via Frequency-Aware Compilation
- Effective quantum volume, fidelity and computational cost of noisy quantum processing experiments