Clifford Extraction and Absorption for Quantum Circuit Optimization

Quantum circuit optimization is essential for improving the performance of both near-term Noisy Intermediate-Scale Quantum (NISQ) devices and future Fault-Tolerant Quantum Computing (FTQC) devices. This work introduces QuCLEAR, a novel compilation framework that optimizes quantum circuits by significantly reducing two-qubit gate counts and circuit depth. QuCLEAR achieves these improvements through two key techniques. The first is Clifford Extraction, which identifies and repositions Clifford subcircuits to the end of the circuit, simultaneously optimizing the gate structure. The second is Clifford Absorption, which leverages the classical simulability of Clifford circuits to process these extracted Clifford subcircuits efficiently. We evaluate QuCLEAR on quantum simulation circuits, relevant to quantum chemistry, many-body physics, and combinatorial optimization. These applications also include near-term algorithms like VQE and QAOA. Experimental results show that QuCLEAR delivers reductions of up to 77.7% in CNOT gate count and 84.1% in entangling depth, outperforming existing state-of-the-art methods across various benchmarks.