QLOPS Metric Benchmarks Performance of Fault-Tolerant Quantum Computing Schemes

Quantum computing promises revolutionary advances across fields like cryptography and materials science, but realising this potential demands both scalable hardware and robust methods for correcting errors. Linghang Kong, Fang Zhang, and Jianxin Chen, from Zhongguancun Laboratory and Tsinghua University, address a critical gap in the field by introducing a new benchmarking metric, Logical Operations Per Second, or QLOPS. This framework moves beyond theoretical evaluations by integrating practical considerations such as code rates, decoder accuracy, and processing speed, to provide a more realistic assessment of fault-tolerant quantum computer performance. By pinpointing hardware bottlenecks and enabling comparative analysis of different designs, this work offers valuable guidance for future development and helps estimate the resources needed to run complex algorithms on quantum computers, ultimately accelerating progress towards practical quantum computation.

Evaluating Fault Tolerance Across Quantum Platforms

Quantum computing promises revolutionary advances across numerous fields, but building practical quantum computers presents significant challenges due to the fragility of quantum information and inherent errors. Achieving reliable computation requires fault-tolerant quantum computing, employing techniques to protect quantum information and ensure accurate results. Currently, evaluating the performance of different fault-tolerance approaches and hardware platforms lacks a comprehensive framework. To address this gap, researchers have proposed a new metric called Quantum Logical Operations Per Second, or QLOPS. QLOPS aims to provide a holistic evaluation of fault-tolerant quantum computing hardware by integrating key factors such as error correction code rates, decoder accuracy, and the throughput and latency of the decoding process. This comprehensive approach allows for the identification of performance bottlenecks and guides the development of optimized hardware, enabling a more nuanced comparison of different schemes on various platforms.

Logical Qubit Stability Without Operations

Current discussions on fault-tolerant quantum computing primarily focus on assessing the stability of logical qubits, but this approach does not fully capture the costs associated with performing actual quantum computations. This work benchmarks the computational capability of quantum hardware from the perspective of logical operations, establishing QLOPS as a comprehensive metric that incorporates relevant factors. Researchers calculate the QLOPS of superconducting qubits with the surface code and neutral atom qubits with the generalized bicycle codes as an example. This work offers a holistic evaluation framework, integrating factors relevant to fault-tolerant quantum computing and allowing a more realistic estimation of progress in the field. Early research often overlooks the cost introduced by classical computation, but as quantum hardware scales, decoder throughput has emerged as a bottleneck. This metric will pinpoint bottlenecks and guide iterative hardware development, quantifying the impact of parameter enhancements and allowing for comparison of schemes on a given quantum hardware.

Results establish a comparative framework for evaluating Fault-Tolerant Quantum Computing designs. This benchmarking approach considers practical applications and may assist in estimating the hardware resources needed to implement quantum algorithms. It also offers preliminary insights into potential timelines.

QLOPS Defines Fault-Tolerant Quantum Performance

Researchers introduce QLOPS (Quantum Logical Operations Per Second) as a metric to evaluate the performance of fault-tolerant quantum computers, analogous to FLOPS for classical computers but tailored to quantum systems. The goal is to provide a theoretical upper bound on the computational capability of a quantum hardware platform, based on factors such as physical error rates, quantum error correction codes, fault-tolerant quantum computation schemes, logical qubit overhead, magic state production rate, and decoding speed. Researchers calculate the QLOPS for both superconducting and neutral atom quantum computing platforms, highlighting that magic state production is a major bottleneck in both systems. The calculated QLOPS values are significantly higher than the actual number of Toffoli gates that can be applied in practice, due to limitations in parallelization and the overhead of fault tolerance. QLOPS allows for a theoretical comparison of different hardware platforms, and can guide hardware development, inform algorithm design, and provide a standardized way to compare platforms. Potential implications include guiding hardware development, informing algorithm design, benchmarking and comparison of platforms, and creating realistic roadmaps for the development of fault-tolerant quantum computers.