Francesco Cesa

Quantum devices can process data in a fundamentally different way than classical computers. To leverage this potential, many algorithms require the aid of a quantum Random Access Memory (QRAM), i.e. a module capable of efficiently loading datasets (both classical and quantum) onto the quantum processor. However, a realisation of this fundamental building block is still outstanding, since existing proposals require prohibitively many resources for reliable implementations, or are not compatible with current architectures. Moreover, present approaches cannot be scaled-up, as they do not allow for efficient quantum error-correction. Here we develop a QRAM design, that enables fast and robust QRAM calls, naturally allows for fault-tolerant and error-corrected operation, and can be integrated on present hardware. Our proposal employs a special quantum resource state that is consumed during the QRAM call: we discuss how it can be assembled and processed efficiently in a dedicated module. Concretely, we provide detailed blueprints and quantitative estimations for modern neutral-atom processors, demonstrating that high-fidelity QRAM queries can be implemented at rates compatible with the fault-tolerant computational clock-time. Our work places a long missing, fundamental component of quantum computers within reach of currently available technology; this opens the door to algorithms featuring practical quantum advantage, including search or oracular problems, quantum chemistry and machine learning.