Circuit-based quantum random access memory for classical data with continuous amplitudes

TL;DR

This paper introduces an efficient circuit-based quantum RAM (FF-QRAM) that loads continuous classical data into quantum devices with reduced computational cost, suitable for noisy intermediate-scale quantum computers.

Contribution

It proposes a novel strategy to load continuous data without post-selection, improving efficiency over previous methods by using standard quantum gates and probabilistic quantum memory.

Findings

Loads continuous data with cost O(Mn)

Compatible with noisy intermediate-scale quantum computers

Eliminates the need for post-selection in data loading

Abstract

Loading data in a quantum device is required in several quantum computing applications. Without an efficient loading procedure, the cost to initialize the algorithms can dominate the overall computational cost. A circuit-based quantum random access memory named FF-QRAM can load M n-bit patterns with computational cost O(CMn) to load continuous data where C depends on the data distribution. In this work, we propose a strategy to load continuous data without post-selection with computational cost O(Mn). The proposed method is based on the probabilistic quantum memory, a strategy to load binary data in quantum devices, and the FF-QRAM using standard quantum gates, and is suitable for noisy intermediate-scale quantum computers.