The article "Benchmarking Quantum Computers" by Timothy Proctor, Kevin Young, Andrew D. Baczewski, and Robin Blume-Kohout provides an overview of the science of benchmarking quantum computers. The authors discuss the importance of benchmarks in assessing the performance of quantum hardware and software, emphasizing that good benchmarks can drive progress towards the long-term goal of useful quantum computations, or "quantum utility." They explain how different types of benchmarks quantify the performance of various components of a quantum computer and survey existing benchmarks, recent trends, and open research questions in the field. The article highlights the evolution of quantum computer benchmarking from early techniques like randomized benchmarking (RB) to more sophisticated methods that measure the overall performance of integrated quantum computers. It also discusses the role of benchmarks in sociological and engineering contexts, such as influencing decisions, optimizing systems, and comparing different technologies. Key aspects covered include: - **Types of Benchmarks**: Low-level and high-level benchmarks, focusing on specific quantum circuits or broader computational problems. - **Performance Metrics**: Metrics like error rates, quantum volume, and capability regions. - **Robustness and Efficiency**: Ensuring benchmarks are well-motivated, robust, and efficient. - **Verification Challenges**: Addressing the difficulty of efficiently verifying the correctness of solutions to computational problems. - **Component and Subroutine Benchmarks**: Measuring the performance of individual gates and components. - **Compilation and Abstraction Levels**: The impact of different levels of abstraction on benchmarking. - **Roadmaps to Quantum Utility**: Using challenge problems, resource estimates, and roadmaps to track progress towards quantum utility. The authors emphasize the need for benchmarks that are well-motivated, robust, and efficient, and that can effectively measure and guide progress towards practical quantum computing applications.The article "Benchmarking Quantum Computers" by Timothy Proctor, Kevin Young, Andrew D. Baczewski, and Robin Blume-Kohout provides an overview of the science of benchmarking quantum computers. The authors discuss the importance of benchmarks in assessing the performance of quantum hardware and software, emphasizing that good benchmarks can drive progress towards the long-term goal of useful quantum computations, or "quantum utility." They explain how different types of benchmarks quantify the performance of various components of a quantum computer and survey existing benchmarks, recent trends, and open research questions in the field. The article highlights the evolution of quantum computer benchmarking from early techniques like randomized benchmarking (RB) to more sophisticated methods that measure the overall performance of integrated quantum computers. It also discusses the role of benchmarks in sociological and engineering contexts, such as influencing decisions, optimizing systems, and comparing different technologies. Key aspects covered include: - **Types of Benchmarks**: Low-level and high-level benchmarks, focusing on specific quantum circuits or broader computational problems. - **Performance Metrics**: Metrics like error rates, quantum volume, and capability regions. - **Robustness and Efficiency**: Ensuring benchmarks are well-motivated, robust, and efficient. - **Verification Challenges**: Addressing the difficulty of efficiently verifying the correctness of solutions to computational problems. - **Component and Subroutine Benchmarks**: Measuring the performance of individual gates and components. - **Compilation and Abstraction Levels**: The impact of different levels of abstraction on benchmarking. - **Roadmaps to Quantum Utility**: Using challenge problems, resource estimates, and roadmaps to track progress towards quantum utility. The authors emphasize the need for benchmarks that are well-motivated, robust, and efficient, and that can effectively measure and guide progress towards practical quantum computing applications.