Fei Meng, City University of Hongkong

Zoom: https://eu02web.zoom-x.de/j/63290859023?pwd=Gs5vKyEipDSMtVwLbLQVtbjCuhDrFk.1

Abstract:

Can quantum technology enhance energy efficiency in information processing? I explore this question from a fundamental perspective, focusing on data compression and replication.
First, I present a resource-theoretic framework to quantify the thermodynamic cost of accurate information processing, showing that replicating quantum data using a coherent quantum machine incurs a lower cost than a semi-classical approach. Second, for classical data compression, I introduce a quantum autoencoder leveraging the hidden subgroup algorithm, achieving exponential speedup over classical methods. This advantage allows a quantum agent to efficiently compress random sequences that a classical agent cannot, leading to higher assigned free energy and greater energy extraction.
Our findings highlight the fundamental thermodynamic benefits of quantum information processing.