Experimental benchmarking of an automated deterministic error suppression workflow for quantum algorithms

Abstract

Excitement about the promise of quantum computers is tempered by the reality that the hardware remains exceptionally fragile and error-prone, forming a bottleneck in the development of novel applications. In this manuscript, we describe and experimentally test a fully autonomous workflow designed to deterministically suppress errors in quantum algorithms from the gate level through to circuit execution and measurement. We introduce the key elements of this workflow, delivered as a software package called Fire Opal, and survey the underlying physical concepts: error-aware compilation, automated system-wide gate optimization, automated dynamical decoupling embedding for circuit-level error cancellation, and calibration-efficient measurement-error mitigation. We then present a comprehensive suite of performance benchmarks executed on IBM hardware, demonstrating up to > 1000X improvement over the best alternative expert-configured techniques available in the open literature. Benchmarking includes experiments using up to 16 qubit systems executing: Bernstein Vazirani, Quantum Fourier Transform, Grover's Search, QAOA, VQE, Syndrome extraction on a five-qubit Quantum Error Correction code, and Quantum Volume. Experiments reveal a strong contribution of Non-Markovian errors to baseline algorithmic performance; in all cases the deterministic error-suppression workflow delivers the highest performance and approaches incoherent error bounds without the need for any additional sampling or randomization overhead, while maintaining compatibility with all additional probabilistic error suppression techniques.

20 pages, 16 figures

References in corpus (22)

• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Quantum computational advantage using photons
• The Variational Quantum Eigensolver: a review of methods and best practices
• Randomized Benchmarking of Quantum Gates
• Fault-tolerant quantum computation with high threshold in two dimensions
• Simple pulses for elimination of leakage in weakly nonlinear qubits
• Noise-Induced Barren Plateaus in Variational Quantum Algorithms
• Robust randomized benchmarking of quantum processes
• t$|$ket$⟩$ : A Retargetable Compiler for NISQ Devices
• Scalable mitigation of measurement errors on quantum computers
• Process verification of two-qubit quantum gates by randomized benchmarking
• Measuring the Capabilities of Quantum Computers
• Experimental noise filtering by quantum control
• Reducing unitary and spectator errors in cross resonance with optimized rotary echoes
• Deep Reinforcement Learning for Quantum Gate Control
• Experimental Deep Reinforcement Learning for Error-Robust Gateset Design on a Superconducting Quantum Computer
• Foliated Quantum Codes
• Integrated tool-set for Control, Calibration and Characterization of quantum devices applied to superconducting qubits
• Suppressing quantum circuit errors due to system variability
• Error-robust quantum logic optimization using a cloud quantum computer interface
• Rolling quantum dice with a superconducting qubit
• Tensor-network codes

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• Achieving computational gains with quantum error-correction primitives: Generation of long-range entanglement enhanced by error detection
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