Dynamic quantum circuits with mid-circuit measurements (MCMs) and feed-forward operations play a crucial role in various applications, such as quantum error correction and quantum algorithms. With advancements in quantum hardware enabling the implementation of MCM and feed-forward loops, the use of dynamic circuits has become increasingly prevalent. There is a significant need for a benchmarking framework specially designed for dynamic circuits to capture their unique properties, as current benchmarking tools are designed primarily for unitary circuits and cannot be trivially extended to dynamic circuits. We propose dynamarq, a scalable and hardware-agnostic benchmarking framework for dynamic circuits. We collect a set of dynamic circuit benchmarks spanning various applications and propose a broad set of circuit features to characterize the structure of these dynamic circuits. We run them on two IBM quantum processors and the Quantinuum Helios-1E emulator, and propose scalable, application-dependent fidelity scores for each benchmark based on hardware execution results. We perform statistical modeling to identify correlations between circuit features and fidelity scores, and demonstrate highly accurate fidelity prediction using our model. Our model parameters are also transferable across hardware backends and calibration cycles. Our framework facilitates the understanding of dynamic circuit structures and provides insights for designing and optimizing dynamic circuits to achieve high execution fidelity on quantum hardware.
Randomized Benchmarking Protocol for Dynamic Circuits
IBM Quantum, IBM Research - Israel（IBM量子，IBM以色列研究中心）；IBM Quantum, IBM Almaden Research Center（IBM量子，IBM阿尔马登研究中心）；IBM Quantum, IBM TJ Watson Research Center（IBM量子，IBM托马斯·J·沃森研究中心）
In-situ benchmarking of fault-tolerant quantum circuits. I. Clifford circuits
Joint Center for Quantum Information and Computer Science, NIST/University of Maryland（量子信息与计算机联合中心，美国国家标准与技术研究院/马里兰大学）；Simons Institute for the Theory of Computing, University of California at Berkeley（西蒙斯计算理论研究所，加州大学伯克利分校）；Institute for Theoretical Physics, ETH Zürich（理论物理研究所，苏黎世联邦理工学院）；Department of Physics, Harvard University（物理学系，哈佛大学）；National Institute of Standards and Technology（美国国家标准与技术研究院）
Quickly extracting fidelity decay rates in random circuit benchmarking experiments
CWI & QuSoft（荷兰数学与计算机科学研究中心与QuSoft）；Quantum Research Center, Technology Innovation Institute（技术研究院量子研究中心）；Institute for Theoretical Physics, University of Cologne（科隆大学理论物理研究所）；Johannes Kepler Universität Linz（林茨约翰内斯·开普勒大学）；Rigetti Computing（里吉蒂计算）
BenchQC -- Scalable and modular benchmarking of industrial quantum computing applications
Fraunhofer Institute for Cognitive Systems IKS（弗劳恩霍夫认知系统研究所）；Fraunhofer Institute for Integrated Circuits IIS（弗劳恩霍夫集成电路研究所）；Reply SE, Machine Learning Reply GmbH（Reply股份公司，机器学习Reply有限公司）；OptWare GmbH（OptWare有限公司）
Sample-efficient benchmarking of shallow all-to-all random quantum circuits
The College of William & Mary（威廉玛丽学院）；The University of Chicago（芝加哥大学）；Joint Center for Quantum Information and Computer Science, University of Maryland and NIST（马里兰大学和NIST联合量子信息与计算中心）；University of Waterloo（滑铁卢大学）
QMetric: Benchmarking Quantum Neural Networks Across Circuits, Features, and Training Dimensions
IT4Innovations National Supercomputing Center（IT4创新国家超级计算中心）；Systems Research Institute, Polish Academy of Sciences（波兰科学院系统研究所）；Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences（波兰科学院尼古拉·哥白尼天体物理中心）；Center of Excellence in Artificial Intelligence, AGH University（AGH大学人工智能卓越中心）；University of L'Aquila（拉奎拉大学）
Characterization of Unlearnable Noise with Mid-Circuit-Measurement-Based Cycle Benchmarking
Imperial College London（帝国理工学院）；Fraunhofer Institute for Industrial Mathematics（弗劳恩霍夫工业数学研究所）；Algorithmiq Ltd（Algorithmiq有限公司）；University of Helsinki（赫尔辛基大学）；Fraunhofer Center for Maritime Logistics（弗劳恩霍夫海事物流中心）
Platform-Agnostic Modular Architecture for Quantum Benchmarking
University of Central Florida（佛罗里达中央大学）；University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；North Carolina State University（北卡罗来纳州立大学）；Pennsylvania State University（宾夕法尼亚州立大学）；Sandia National Laboratories（桑迪亚国家实验室）
Benchmarking Encoding Families in Quantum Neural Networks Under Fixed Circuit Area for Frequency Spectrum and Trainability
Military University of Technology（军事理工大学）；The Washington Institute for STEM Entrepreneurship and Research（华盛顿STEM创业与研究学院）；Fraunhofer Institute for Industrial Mathematics ITWM（弗劳恩霍夫工业数学研究所ITWM）；Georgia Institute of Technology（佐治亚理工学院）
Randomized Benchmarking with Synthetic Quantum Circuits
Quantum Performance Laboratory, Sandia National Laboratories（桑迪亚国家实验室）；Department of Physics, University of Idaho（爱达荷大学）；HRL Laboratories, LLC（HRL实验室有限责任公司）
Circuit Quantum Acoustodynamics in a Scalable Phononic Integrated Circuit Architecture
Tsinghua University（清华大学）；University of Science and Technology of China（中国科学技术大学）；Beijing Academy of Quantum Information Sciences（北京量子信息科学研究院）；Hefei National Laboratory（合肥国家实验室）
