Scalable suppression of heating errors in large trapped-ion quantum processors

TL;DR

This paper introduces a flexible, efficient framework to suppress heating errors in large trapped-ion quantum processors, significantly improving fidelity and scalability for quantum computing.

Contribution

It presents a novel, comprehensive method for mitigating heating errors that is compatible with existing techniques and scalable to large ion systems.

Findings

Up to tenfold reduction in infidelity in simulations with 55 qubits.

Framework adaptable to various control bases, ion numbers, and noise levels.

Efficient cost function avoids exponential complexity in fidelity estimation.

Abstract

Trapped-ion processors are leading candidates for scalable quantum computation. However, motional heating remains a key obstacle to fault-tolerant operation, especially when system size increases. Heating error is particularly challenging to suppress due to is incoherence nature, and no general methods currently exist for mitigating their impact even in systems with more than two ions. In this work, based on a careful analysis about the dependence of heating-induced infidelity on phase-space trajectories, we present a simple yet comprehensive framework for suppressing heating errors in large trapped-ion quantum processors. Our approach is flexible, allowing various control pulse bases, ion numbers, and noise levels. Our approach is also compatible with existing error-mitigation techniques, including those targeting laser phase and frequency noise. Crucially, it relies on an efficiently computable cost function that avoids the exponential overhead of full fidelity estimation. We perform numerical simulations for systems with up to 55 qubits, demonstrating up to an order-of-magnitude reduction in infidelities. These results offer a practical route toward robust, large-scale quantum computation with trapped ions.