Quantum computation by measurement and quantum memory

Gerard J Milburn, Cassius D'Helon

Chenxu Liu, Meng Wang, Samuel A. Stein +2 more

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.

Jinghang Zhang, Yu Luo

Quantum memory plays a critical role in quantum communication, sensing, and computation. However, studies on quantum memory under a unified benchmarking framework remain scarce. In this paper, we propose a weight-based quantifier as a benchmarking method to evaluate the performance advantage of quantum memory in nonlocal exclusion tasks. We establish a general lower bound for the weight-based measure of quantum memory. Moreover, this measure provides fundamental theoretical bounds for transforming a general channel into an ideal quantum memory. Finally, we present explicit calculations of the weight-based quantifier for various channels, including unitary channels, depolarizing channels, maximal replacement channels, stochastic damping channels, and erasure channels.

Hans J. Briegel, Dan E. Browne, Wolfgang Dür +2 more

Peter C. Humphreys, W. Steven Kolthammer, Joshua Nunn +3 more

We develop a scheme for time-frequency encoded continuous-variable cluster-state quantum computing using quantum memories. In particular, we propose a method to produce, manipulate, and measure two-dimensional cluster states in a single spatial mode by exploiting the intrinsic time-frequency selectivity of Raman quantum memories. Time-frequency encoding enables the scheme to be extremely compact, requiring a number of memories that are a linear function of only the number of different frequencies in which the computational state is encoded, independent of its temporal duration. We therefore show that quantum memories can be a powerful component for scalable photonic quantum information processing architectures.

Dan E. Browne, Janet Anders