COGNAC: Circuit Optimization via Gradients and Noise-Aware Compilation

• URL: http://arxiv.org/abs/2311.02769v2
• Date: Fri, 15 Mar 2024 15:59:59 GMT
• Title: COGNAC: Circuit Optimization via Gradients and Noise-Aware Compilation
• Authors: Finn Voichick, Leonidas Lampropoulos, Robert Rand,
• Abstract summary: We present COGNAC, a novel strategy for compiling quantum circuits. We use a simple noise model informed by the duration entangling gates. We reduce a circuit's gate count without the need for a large number of explicit elimination rewrite rules.
• Score: 0.29998889086656577
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present COGNAC, a novel strategy for compiling quantum circuits based on numerical optimization algorithms from scientific computing. Using a simple noise model informed by the duration of entangling gates, our gradient-based method can quickly converge to a local optimum that closely approximates the target unitary. By iteratively and continuously decreasing a gate's duration to zero, we reduce a circuit's gate count without the need for a large number of explicit elimination rewrite rules. We have implemented this technique as a general-purpose Qiskit compiler plugin and compared performance with state-of-the-art optimizers on a variety of standard 4-qubit benchmarks. COGNAC typically outperforms existing optimizers in reducing 2-qubit gate count, sometimes significantly. Running on a low-end laptop, our plugin takes seconds to optimize a small circuit, making it effective and accessible for a typical quantum programmer.

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