Quantum autoencoders for communication-efficient quantum cloud computing

TL;DR

This paper introduces quantum autoencoders for quantum gates to compress quantum computations, reducing communication in quantum cloud computing while preserving data privacy, validated through numerical experiments.

Contribution

It proposes a novel quantum autoencoder method for compressing quantum gates, enhancing communication efficiency and privacy in quantum cloud computing.

Findings

Effective compression of quantum gates demonstrated

Reduced quantum communication in simulated scenarios

Preservation of privacy in the autoencoder process

Abstract

In the model of quantum cloud computing, the server executes a computation on the quantum data provided by the client. In this scenario, it is important to reduce the amount of quantum communication between the client and the server. A possible approach is to transform the desired computation into a compressed version that acts on a smaller number of qubits, thereby reducing the amount of data exchanged between the client and the server. Here we propose quantum autoencoders for quantum gates (QAEGate) as a method for compressing quantum computations. We illustrate it in concrete scenarios of single-round and multi-round communication and validate it through numerical experiments. A bonus of our method is it does not reveal any information about the server's computation other than the information present in the output.