Evaluating Quantum Algorithm Resource Requirements through the QuRA Toolset

Quantum computing promises significant advantages over classical computing for specific problems, yet current quantum devices remain highly resource-constrained, limiting the size and complexity of executable programs. Accurate estimation of quantum resources, such as qubit count, circuit depth, and gate usage, is therefore essential for program feasibility analysis and optimization. This thesis extends the QuRA tool, which builds on Proto-Quipper, a functional quantum programming language with a strong type system for static resource analysis. Beyond type-checking and symbolic estimation of circuit size, we formalize an evaluation semantics that translates well-typed Proto-Quipper programs into a Circuit Representation Language (CRL), enabling explicit circuit construction and validation of inferred resource bounds. Finally, we develop a translation pipeline from CRL to OpenQASM 3.0, bridging high-level program analysis with hardware-executable code. The resulting framework provides both formal guarantees of correctness and practical outputs, supporting early feasibility analysis, validation of parametric bounds, and integration with existing compilation toolchains. This work lays the foundation for further extensions, including tighter resource estimates, dynamic analysis, and broader backend compatibility.