Optimized Quantum Autoencoder

• URL: http://arxiv.org/abs/2404.08429v1
• Date: Fri, 12 Apr 2024 12:25:39 GMT
• Title: Optimized Quantum Autoencoder
• Authors: Yibin Huang, Muchun Yang, D. L. Zhou,
• Abstract summary: We show how to decrease the lost information in QAE for any input mixed state. We numerically identify that our compression scheme outperforms the quantum variational circuit based QAE@.
• Score: 0.641460223525021
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum autoencoder (QAE) compresses a bipartite quantum state into its subsystem by a self-checking mechanism. How to characterize the lost information in this process is essential to understand the compression mechanism of QAE\@. Here we investigate how to decrease the lost information in QAE for any input mixed state. We theoretically show that the lost information is the quantum mutual information between the remaining subsystem and the ignorant one, and the encoding unitary transformation is designed to minimize this mutual information. Further more, we show that the optimized unitary transformation can be decomposed as the product of a permutation unitary transformation and a disentanglement unitary transformation, and the permutation unitary transformation can be searched by a regular Young tableau algorithm. Finally we numerically identify that our compression scheme outperforms the quantum variational circuit based QAE\@.

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