Statistical Assertions for Debugging Quantum Circuits and States in CUDA-Q

TL;DR

This paper introduces a statistical assertion-based debugging workflow for CUDA-Q, enabling easier verification of quantum circuit correctness and state analysis, leveraging GPU acceleration for larger and more complex quantum circuits.

Contribution

It presents a novel debugging approach for CUDA-Q using statistical assertions, improving reliability with Fisher's exact test and Monte Carlo methods, tailored for CUDA-Q's kernel-based model.

Findings

Enhanced debugging accuracy with Fisher's exact test and Monte Carlo methods.

Improved detection of deviations in quantum states during circuit execution.

Facilitated debugging of larger, more complex quantum circuits.

Abstract

As quantum computing continues to mature, more developers are designing, coding, and simulating quantum circuits. A challenge exists, however, in debugging quantum circuits, particularly as they scale in size and complexity. Given the lack of effective debugging workflows, developers are forced to manually inspect their circuits and analyze various quantum states, which is error-prone and time-consuming. In this research, we present a statistical assertion-based debugging workflow for CUDA-Q. CUDA-Q has gained popularity due to its ability to leverage GPUs to accelerate quantum circuit simulations; this allows circuits to scale to larger depths and widths, where they can be particularly hard to debug by hand. Inspired by and building from prior Qiskit-based debuggers, our work allows CUDA-Q users to verify quantum program correctness with greater ease. Through the insertion of statistical assertions within a quantum circuit, our tool provides valuable insights into the state of qubits at any point within a circuit, tracks their evolution, and helps detect deviations from expected behavior. Furthermore, we improve the reliability and accuracy of the product state assertion by using a combination of Fisher's exact test and the Monte Carlo Method instead of a chi-square test, and examine the impact of CUDA-Q's distinct kernel-based programming model on the design of our debugging tool. This work offers a practical solution to one of CUDA-Q's usability gaps, paving the way for more reliable and efficient quantum software development.