Erwin Schrödinger Center for Quantum Science & Technology (ESQ)

In the past few decades, memristive devices have attracted enormous interest in electronics. This is because memristive dynamics is very pervasive in nanoscale devices, and has potentially groundbreaking applications ranging from energy-efficient memories to physical neural networks and neuromorphic computing platforms. Recently, the concept of a quantum memristor was introduced by a few proposals, all of which face limited technological practicality. Here the authors propose and experimentally demonstrate a novel quantum-optical memristor (based on integrated photonics) that acts on single-photon states. They fully characterize the memristive dynamics of their device and tomographically reconstruct its quantum output state. Finally, they propose a possible application of their device in the framework of quantum machine learning through a scheme of quantum reservoir computing, which they apply to classical and quantum learning tasks. Their simulations show promising results, and may break new ground towards the use of quantum memristors in quantum neuromorphic architectures.

For more information see:

https://www.nature.com/articles/s41566-022-00973-5