Nonlinear Dynamics in Semiconductor Lasers 2023 - Abstract

Gies, Christopher

Quantum reservoir computing with semiconductor-based quantum-photonic hardware

Semiconductor-based nanolasers have been thoroughly researched over the past decades. From an application perspective, they are not only a promising platform for green photonics, but they may also be an enabling technology for noisy intermediate scale quantum (NISQ) hardware. While fully-fledged quantum computing requires near-error free qubit- and gate operations, alternative approaches are being developed for the NISQ-era that deserve attention. Quantum reservoir computing (QRC) is such a paradigm: It relies on the complex dynamics that can be found in open quantum systems and aims at exploiting the exponentially large internal degrees of freedom. In my talk, I will explain the interest in this novel field that combines machine learning, quantum mechanics, and complex systems theory. I will introduce measures for quantifying performance and quantum advantage, as well as discussing possible implementations. Interconnected nanolasers forming a quantum-photonic artificial neural network may turn out as a suitable platform to realize such a quantum-machine learning devices in the foreseeable future.