Resource-efficient simulation of noisy quantum circuits and application to network-enabled QRAM optimization

TL;DR

This paper presents a resource-efficient simulation method for noisy quantum circuits, enabling analysis of large-scale QRAM architectures and proposing improvements for network-based QRAM to enhance fidelity and access rates.

Contribution

It introduces a novel simulation approach for large noisy quantum systems and proposes a modified QRAM architecture suitable for near-term quantum networks.

Findings

Efficient simulation of hundreds to thousands of qubits under noise.

Network-based QRAM feasible with current or near-term photonic and atomic technologies.

Modified QRAM architecture improves fidelity and access rate.

Abstract

Giovannetti, Lloyd, and Maccone [Phys. Rev. Lett. 100, 160501] proposed a quantum random access memory (QRAM) architecture to retrieve arbitrary superpositions of $N$ (quantum) memory cells via $O(\log(N))$ quantum switches and $O(\log(N))$ address qubits. Towards physical QRAM implementations, Chen et al. [PRX Quantum 2, 030319] recently showed that QRAM maps natively onto optically connected quantum networks with $O(\log(N))$ overhead and built-in error detection. However, modeling QRAM on large networks has been stymied by exponentially rising classical compute requirements. Here, we address this bottleneck by: (i) introducing a resource-efficient method for simulating large-scale noisy entanglement, allowing us to evaluate hundreds and even thousands of qubits under various noise channels; and (ii) analyzing Chen et al.'s network-based QRAM as an application at the scale of quantum data centers or near-term quantum internet; and (iii) introducing a modified network-based QRAM architecture to improve quantum fidelity and access rate. We conclude that network-based QRAM could be built with existing or near-term technologies leveraging photonic integrated circuits and atomic or atom-like quantum memories.