An Automated Synthesis Framework for Benchmarking Quantum Resource Costs of Symmetric-Key Cryptography

Modern information security relies heavily on symmetric-key cryptography such as AES. As quantum computing advances, these classical schemes face increasing pressure from quantum key-search attacks, most notably Grover’s algorithm. To evaluate and compare quantum security quantitatively, the core components of symmetric-key algorithms must be implemented and optimized as quantum circuits. Among them, the S-box is a key source of nonlinearity and often dominates the circuit cost. In this paper, we introduce ADOQ (Automatic Depth Optimizer for Quantum circuits), a modular Python (version 3.13.3) framework that automatically synthesizes reversible quantum circuits from S-box specifications and applies a sequence of depth optimization techniques to produce optimized QASM circuits. Our experiments show that ADOQ achieves circuit depths comparable to prior work on 4-qubit S-boxes, and it also supports synthesis for larger S-boxes.