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Approximation errors must be taken into account when compiling quantumprograms into a low-level gate set. We present a methodology that tracks sucherrors automatically and then optimizes accuracy parameters to guarantee aspecified overall accuracy while aiming to minimize the implementation cost interms of quantum gates. The core idea of our approach is to extract functionsthat specify the optimization problem directly from the high-level descriptionof the quantum program. Then, custom compiler passes optimize these functions,turning them into (near-)symbolic expressions for (1) the total error and (2)the implementation cost (e.g., total quantum gate count). All unspecifiedparameters of the quantum program will show up as variables in theseexpressions, including accuracy parameters. After solving the correspondingoptimization problem, a circuit can be instantiated from the found solution. Wedevelop two prototype implementations, one in C++ based on Clang/LLVM, andanother using the Q# compiler infrastructure. We benchmark our prototypes ontypical quantum computing programs, including the quantum Fourier transform,quantum phase estimation, and Shor's algorithm.

Enabling Accuracy-Aware Quantum Compilers using Symbolic Resource Estimation