Learning an unknown transformation via a genetic approach

23Citations
Citations of this article
33Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Recent developments in integrated photonics technology are opening the way to the fabrication of complex linear optical interferometers. The application of this platform is ubiquitous in quantum information science, from quantum simulation to quantum metrology, including the quest for quantum supremacy via the boson sampling problem. Within these contexts, the capability to learn efficiently the unitary operation of the implemented interferometers becomes a crucial requirement. In this letter we develop a reconstruction algorithm based on a genetic approach, which can be adopted as a tool to characterize an unknown linear optical network. We report an experimental test of the described method by performing the reconstruction of a 7-mode interferometer implemented via the femtosecond laser writing technique. Further applications of genetic approaches can be found in other contexts, such as quantum metrology or learning unknown general Hamiltonian evolutions.

Cite

CITATION STYLE

APA

Spagnolo, N., Maiorino, E., Vitelli, C., Bentivegna, M., Crespi, A., Ramponi, R., … Sciarrino, F. (2017). Learning an unknown transformation via a genetic approach. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-14680-7

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free