Efficient and Error-Resilient Data Access Protocols for a Limited-Sized Quantum Random Access Memory
Zhao-Yun Chen, Cheng Xue, Yun-Jie Wang, Tai-Ping Sun, Huan-Yu Liu,, Xi-Ning Zhuang, Meng-Han Dou, Tian-Rui Zou, Yuan Fang, Yu-Chun Wu and, Guo-Ping Guo

TL;DR
This paper introduces efficient, error-resilient protocols for quantum random access memory (QRAM) that handle larger data words and sizes without increasing QRAM levels, improving practicality for quantum computing.
Contribution
It proposes novel data loading protocols for larger word lengths and data sizes, reducing qubit and error requirements for practical QRAM implementation.
Findings
Achieves $O(n+k)$ time complexity for larger word lengths
Outperforms existing hybrid QRAM+QROM architectures
Reduces qubit count and error scaling in QRAM devices
Abstract
Quantum Random Access Memory (QRAM) is a critical component for loading classical data into quantum computers. While constructing a practical QRAM presents several challenges, including the impracticality of an infinitely large QRAM size and a fully error-correction implementation, it is essential to consider a practical case where the QRAM has a limited size. In this work, we focus on the access of larger data sizes without keeping on increasing the size of the QRAM. Firstly, we address the challenge of word length, as real-world datasets typically have larger word lengths than the single-bit data that most previous studies have focused on. We propose a novel protocol for loading data with larger word lengths without increasing the number of QRAM levels . By exploiting the parallelism in the data query process, our protocol achieves a time complexity of and improves…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Stochastic Gradient Optimization Techniques · Advanced Memory and Neural Computing
