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.
Highlights
Linear optical networks have recently received increasing attention in the quantum regime thanks to the enhanced capability of building complex interferometers made possible by integrated photonics
Genetic algorithms are a broad class of algorithms inspired by the natural evolution of biological systems, which evolve following the principle of natural selection[38,39,40]
The fitness of an individual is determined by its genetic signature, the DNA, which is composed by a set of genes representing its fundamental units
Summary
Nicolò Spagnolo[1], Enrico Maiorino[1], Chiara Vitelli[1], Marco Bentivegna[1], Andrea Crespi[2,3], Roberta Ramponi 2,3, Paolo Mataloni[1], Roberto Osellame 2,3 & Fabio Sciarrino[1]. Linear optical networks have recently received increasing attention in the quantum regime thanks to the enhanced capability of building complex interferometers made possible by integrated photonics This experimental achievement opened new perspectives in the adoption of linear optical networks for different quantum tasks, including quantum walks and quantum simulation[1,2,3,4,5,6,7,8,9,10], quantum phase estimation[11,12,13], as well as the experimental implementation of the Boson Sampling problem[14,15,16,17,18,19,20,21]. In this article we discuss and test experimentally an approach for the reconstruction of linear optical interferometers based on the class of genetic algorithms[38,39,40] The latter is a general method that exploits the principles of natural selection in the evolution of a biological system, and has found application to find the solution to.
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