Scaling and assigning resources on ion trap QCCD architectures

TL;DR

This paper introduces a new initial qubit placement method for ion trap QCCD architectures, improving efficiency and scalability by analyzing different topologies and trap capacities to enhance quantum circuit fidelity.

Contribution

It presents a novel initial qubit placement technique and evaluates the scalability of QCCD architectures with different topologies and trap capacities.

Findings

Up to 50% improvement in initial qubit placement efficiency.

Scalability varies between 1D-linear and ring topologies.

Excess trap capacity significantly impacts algorithm performance.

Abstract

Ion trap technologies have earned significant attention as potential candidates for quantum information processing due to their long decoherence times and precise manipulation of individual qubits, distinguishing them from other candidates in the field of quantum technologies. However, scalability remains a challenge, as introducing additional qubits into a trap increases noise and heating effects, consequently decreasing operational fidelity. Trapped-ion Quantum Charge-Coupled Device (QCCD) architectures have addressed this limitation by interconnecting multiple traps and employing ion shuttling mechanisms to transfer ions among traps. This new architectural design requires the development of novel compilation techniques for quantum algorithms, which efficiently allocate and route qubits, and schedule operations. The aim of a compiler is to minimize ion movements and, therefore, reduce the execution time of the circuit to achieve a higher fidelity. In this paper, we propose a novel approach for initial qubit placement, demonstrating enhancements of up to 50\% compared to prior methods. Furthermore, we conduct a scalability analysis on two distinct QCCD topologies: a 1D-linear array and a ring structure. Additionally, we evaluate the impact of the excess capacity -- i.e. the number of free spaces within a trap -- on the algorithm performance.