Quantum Memory: A Missing Piece in Quantum Computing Units

TL;DR

This paper explores the design, types, and potential applications of quantum memory in quantum computing architectures, emphasizing its importance beyond current quantum registers and proposing a comprehensive framework for future development.

Contribution

It provides a full design stack view of quantum memory, introduces metrics for physical platforms, and discusses various quantum memory devices and their integration into quantum computing architectures.

Findings

Introduces a quantum memory design framework and metrics.

Reviews two types of quantum memory devices: RAQM and QRAM.

Proposes a programming model and discusses applications of quantum memory.

Abstract

Memory is an indispensable component in classical computing systems. While the development of quantum computing is still in its early stages, current quantum processing units mainly function as quantum registers. Consequently, the actual role of quantum memory in future advanced quantum computing architectures remains unclear. With the rapid scaling of qubits, it is opportune to explore the potential and feasibility of quantum memory across different substrate device technologies and application scenarios. In this paper, we provide a full design stack view of quantum memory. We start from the elementary component of a quantum memory device, quantum memory cells. We provide an abstraction to a quantum memory cell and define metrics to measure the performance of physical platforms. Combined with addressing functionality, we then review two types of quantum memory devices: random access quantum memory (RAQM) and quantum random access memory (QRAM). Building on top of these devices, quantum memory units in the computing architecture, including building a quantum memory unit, quantum cache, quantum buffer, and using QRAM for the quantum input-output module, are discussed. We further propose the programming model for the quantum memory units and discuss their possible applications. By presenting this work, we aim to attract more researchers from both the Quantum Information Science (QIS) and classical memory communities to enter this emerging and exciting area.