Breakthrough:
Developed a guide that introduces the most common Quantum Characterization, Verification, and Validation (QCVV) methods and protocols used to assess quantum computer performance, with the goal of teaching foundational QCVV concepts and enabling users to select the most suitable methods for their needs. Drawing on thirty years of QCVV advancements—a field central to progress in quantum computing—this work offers a practical and accessible foundation for effectively characterizing and benchmarking quantum systems. The guide spans protocols from basic to advanced, includes illustrative examples, compares the strengths and limitations of each method, and serves as both an introductory guide and a comprehensive reference. As a result, this work removes barriers to entry and accelerates progress in quantum computing by equipping researchers and engineers with the practical knowledge needed to validate and improve cutting-edge quantum technologies.
Background:
As quantum computing advances from theoretical promise to experimental reality, ensuring the reliability and performance of quantum devices has become a central challenge for the field. QCVV provides the essential framework for rigorously testing, benchmarking, and improving quantum hardware and algorithms. Over the past three decades, a wide array of QCVV methods and protocols has emerged, enabling researchers to diagnose errors, monitor system fidelity, and guide the development of scalable quantum technologies. However, the increasing complexity and variety of these techniques can be daunting, especially as quantum technologies grow in sophistication and real-world impact. Comprehensive resources that systematically introduce, compare, and explain QCVV approaches are crucial for accelerating both foundational research and practical deployment of quantum computing.
Breakdown:
The work first defines and explains QCVV’s core models and concept —quantum states, measurements, and processes—and illustrates how these building blocks are leveraged to examine a target system or operation. Then, it introduces the various different performance metrics used to quantify the error in the target system or operation used throughout QCVV. Finally, it presents step-by-step descriptions of widely used QCVV protocols, compares their strengths, limitations, and scalability, and highlights best practices for practical implementation. Through systematic organization, detailed examples, and side-by-side comparisons, the guide equips readers with the knowledge and tools necessary for effective characterization and benchmarking of quantum systems.
Co-authors:
Akel Hashim, Long B. Nguyen, Noah Goss, Brian Marinelli, Ravi K. Naik, Trevor Chistolini, Jordan Hines, J.P. Marceaux, Yosep Kim, Pranav Gokhale, Teague Tomesh, Senrui Chen, Liang Jiang, Samuele Ferracin, Kenneth Rudinger, Timothy Proctor, Kevin C. Young, Irfan Siddiqi, and Robin Blume-Kohout.
Publication:
Funding:
Advanced Quantum Testbed (AQT)
About Computing Sciences at Berkeley Lab
High performance computing plays a critical role in scientific discovery. Researchers increasingly rely on advances in computer science, mathematics, computational science, data science, and large-scale computing and networking to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab's Computing Sciences Area researches, develops, and deploys new foundations, tools, and technologies to meet these needs and to advance research across a broad range of scientific disciplines.
