Optimized Quantum Compilation for Near-Term Algorithms with OpenPulse
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Abstract (arXiv)
Quantum computers are traditionally operated by programmers at the granularity of a gate-based instruction set. However, the actual device-level control of a quantum computer is performed via analog pulses. We introduce a compiler that exploits direct control at this microarchitectural level to achieve significant improvements for quantum programs. Unlike quantum optimal control, our approach is bootstrapped from existing gate calibrations and the resulting pulses are simple. Our techniques are applicable to any quantum computer and realizable on current devices. We validate our techniques with millions of experimental shots on IBM quantum computers, controlled via the OpenPulse control interface. For representative benchmarks, our pulse control techniques achieve both 1.6x lower error rates and 2x faster execution time, relative to standard gate-based compilation. These improvements are critical in the near-term era of quantum computing, which is bottlenecked by error rates and qubit lifetimes.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Apr 2020.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 1; 2024: 2.
8 papers.
- 2021QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuitscited by 97
- 2024'Eliv'agar: Efficient Quantum Circuit Search for Classificationcited by 12
- 2022NAPA: Intermediate-level Variational Native-pulse Ansatz for Variational Quantum Algorithmscited by 4
- 2022FrozenQubits: Boosting Fidelity of QAOA by Skipping Hotspot Nodescited by 4
- 2024Unleashing the Expressive Power of Pulse-Based Quantum Neural Networkscited by 4
- 2022Review of Ansatz Designing Techniques for Variational Quantum Algorithmscited by 3
- 2023RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Trainingcited by 2
- 2021Towards Efficient Ansatz Architecture for Variational Quantum Algorithmscited by 0
- 2024Unleashing the Expressive Power of Pulse-Based Quantum Neural Networks5 Feb 2024
- 2024'Eliv'agar: Efficient Quantum Circuit Search for Classification17 Jan 2024
- 2023RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training27 Nov 2023
- 2022Review of Ansatz Designing Techniques for Variational Quantum Algorithms7 Dec 2022
- 2022FrozenQubits: Boosting Fidelity of QAOA by Skipping Hotspot Nodes31 Oct 2022
- 2022NAPA: Intermediate-level Variational Native-pulse Ansatz for Variational Quantum Algorithms2 Aug 2022
- 2021Towards Efficient Ansatz Architecture for Variational Quantum Algorithms26 Nov 2021
- 2021QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits22 Jul 2021