Fast Swapping in a Quantum Multiplier Modelled as a Queuing Network

TL;DR

This paper introduces a queuing network model to predict the SWAP depth in quantum circuits, aiding efficient compilation by estimating parallelism and duration, demonstrated on a quantum multiplier circuit.

Contribution

It presents a novel queuing network approach for modeling quantum circuits to predict SWAP depth, improving scalability and accuracy for large circuits.

Findings

Accurately predicts SWAP depth in quantum circuits

Models quantum circuits as queuing networks for efficiency

Demonstrates scalability on a quantum multiplier circuit

Abstract

Predicting the optimum SWAP depth of a quantum circuit is useful because it informs the compiler about the amount of necessary optimization. Fast prediction methods will prove essential to the compilation of practical quantum circuits. In this paper, we propose that quantum circuits can be modeled as queuing networks, enabling efficient extraction of the parallelism and duration of SWAP circuits. To provide preliminary substantiation of this approach, we compile a quantum multiplier circuit and use a queuing network model to accurately determine the quantum circuit parallelism and duration. Our method is scalable and has the potential speed and precision necessary for large scale quantum circuit compilation.