Error mitigation in brainbox quantum autoencoders

Scientific Reports, vol. 15, pp. 2257

Abstract

Quantum hardware faces noise challenges that disrupt multiqubit entangled states. Quantum autoencoder circuits with a single qubit bottleneck have demonstrated the capability to correct errors in noisy entangled states. By introducing slightly more complex structures in the bottleneck, referred to as brainboxes, the denoising process can occure more quickly and efficiently in the presence of stronger noise channels. Selecting the most suitable brainbox for the bottleneck involves a trade-off between the intensity of noise on the hardware and training complexity. Finally, by analysing the Rényi entropy flow throughout the networks, we demonstrate that the localization of entanglement plays a central role in denoising through learning.

Authors 2

1. Joséphine Pazem Aachen Institute for Quantum Information

   RWTH Aachen University · Universität Innsbruck

   Affiliation as printed

   Institut für Theoretische Physik, Universität Innsbruck, Technikerstraße 25, A-6020, Innsbruck, Austria

   Institute for Quantum Information, RWTH Aachen University, D-52056, Aachen, Germany

2. Mohammad H. Ansari corresponding Aachen Institute for Quantum Information

   RWTH Aachen University · Forschungszentrum Jülich

   Affiliation as printed

   Institute for Quantum Information, RWTH Aachen University, D-52056, Aachen, Germany. m.ansari@fz-juelich.de

   Peter Grünberg Institute (PGI-2), Forschungszentrum Jülich, 52428, Jülich, Germany. m.ansari@fz-juelich.de

   Peter Grünberg Institute (PGI-2), Forschungszentrum Jülich, 52428, Jülich, Germany