Reducing Runtime Overhead via Use-Based Migration in Neutral Atom Quantum Architectures

Neutral atoms are a promising choice for scalable quantum computing architectures. Features such as long distance interactions and native multiqubit gates offer reductions in communication costs and operation count. However, the trapped atoms used as qubits can be lost over the course of computation and due to adverse environmental factors. The value of a lost computation qubit cannot be recovered and requires the reloading of the array and rerunning of the computation, greatly increasing the number of runs of a circuit. Software mitigation strategies exist [1] but exhaust the original mapped locations of the circuit slowly and create more spread out clusters of qubits across the architecture decreasing the probability of success. We increase flexibility by developing strategies that find all reachable qubits, rather only adjacent hardware qubits. Second, we divide the architecture into separate sections, and run the circuit in each section, free of lost atoms. Provided the architecture is large enough, this resets the circuit without having to reload the entire architecture. This increases the number of effective shots before reloading by a factor of two for a circuit that utilizes 30% of the architecture. We also explore using these sections to parallelize execution of circuits, reducing the overall runtime by a total 50% for 30 qubit circuit. These techniques contribute to a dynamic new set of strategies to combat the detrimental effects of lost computational space.

I. Introduction

If realized physically, scalable quantum computing could dramatically affect what can be realistically computed. However, there is no obvious choice for quantum architectures as we scale from Noisy Intermediate Scale Quantum (NISQ) computing era and into fault tolerating quantum computing [2]. There are several technologies in different phases of development including superconducting [3], trapped ion [4] and neutral atom [5] based architectures. All have shared challenges such as maximizing device and operation quality, but each comes with their with unique scalability challenges. For superconducting based architectures, fabrication consistency is a limiting factor [3]. Trapped ions face a similar issue when connecting different "chains" of qubits [4]. Larger neutral atom architectures can lose atoms over the course of computation. These are aspects of physical quantum computation that must be resolved to realize scalable architectures.