Quantum-classical processing and benchmarking at the pulse-level

• URL: http://arxiv.org/abs/2303.03816v2
• Date: Tue, 14 Nov 2023 09:36:15 GMT
• Title: Quantum-classical processing and benchmarking at the pulse-level
• Authors: Lior Ella, Lorenzo Leandro, Oded Wertheim, Yoav Romach, Lukas Schlipf, Ramon Szmuk, Yoel Knol, Nissim Ofek, Itamar Sivan and Yonatan Cohen
• Abstract summary: We discuss the requirements for quantum-classical processing at the pulse-level. We propose well-defined performance benchmarks for quantum control systems. We expect the metrics defined in this work to continue to push the boundaries of quantum computing via control systems.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Towards the practical use of quantum computers in the NISQ era, as well as the realization of fault-tolerant quantum computers that utilize quantum error correction codes, pressing needs have emerged for the control hardware and software platforms. In particular, a clear demand has arisen for platforms that allow classical processing to be integrated with quantum processing. While recent works discuss the requirements for such quantum-classical processing integration that is formulated at the gate-level, pulse-level discussions are lacking and are critically important. Moreover, defining concrete performance benchmarks for the control system at the pulse-level is key to the necessary quantum-classical integration. In this work, we categorize the requirements for quantum-classical processing at the pulse-level, demonstrate these requirements with a variety of use cases, including recently published works, and propose well-defined performance benchmarks for quantum control systems. We utilize a comprehensive pulse-level language that allows embedding universal classical processing in the quantum program and hence allows for a general formulation of benchmarks. We expect the metrics defined in this work to form a solid basis to continue to push the boundaries of quantum computing via control systems, bridging the gap between low-level and application-level implementations with relevant metrics.

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