Quantum Random Access Memory (QRAM) has the potential to revolutionize the area of
quantum computing. QRAM uses quantum computing principles to store and modify …

Deep learning achieves unprecedented success involves many fields, whereas the high
requirement of memory and time efficiency tolerance have been the intractable challenges …

In this paper we propose the Quantum Data Center (QDC), an architecture combining
Quantum Random Access Memory (QRAM) and quantum networks. We give a precise …

Quantum random-access memory (QRAM) is a mechanism to access data (quantum or
classical) based on addresses which are themselves a quantum state. QRAM has a long …

We provide a modular circuit-level implementation and resource estimates for several
methods of block-encoding a dense matrix of classical data to precision; the minimal-depth …

Quantum random access memory (QRAM)—memory which stores classical data but allows
queries to be performed in superposition—is required for the implementation of numerous …

A quantum version of data centers might be significant in the quantum era. In this paper, we
introduce Quantum Data Center (QDC)[1], a quantum version of existing classical data …

Emerging quantum algorithms for problems such as element distinctness, subset sum, and
closest pair demonstrate computational advantages by relying on abstract data structures …

Memory is an indispensable component in classical computing systems. While the
development of quantum computing is still in its early stages, current quantum processing …

Quantum algorithms for tasks such as factorization, search, and simulation rely on control
flow such as branching and iteration that depends on the value of data in superposition …