Simple measurements and efficient optimization of linear optical networks

In this proceeding, we describe a simulated model for the characterization of arbitrary unitary matrices implemented by an reconfigurable linear optical network. We build on the method of Hoch et. al, which itself builds on Liang et. al, for characterizing the arbitrary unitary transformation, U, implemented on such devices as an equivalent real bordered form U<sub>rb</sub>. We disscuss how the measurement scheme requires fewer and simpler measurements than. We describe a solution that utilizes a novel algorithm to efficiently recover the complex signs of U<sub>rb</sub> under measurement noise and scaling with system size N.

Authors

Institutions

Publication Details

Published
2025-03-19
DOI
https://doi.org/10.1117/12.3043503
Primary Topic
Optical Network Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simple measurements and efficient optimization of linear optical networks

Shannon Ray, A. Matthew Smith, Daniel Koch, Paul M. Alsing et al.
Optical Network Technologies
article

Simple measurements and efficient optimization of linear optical networks

Shannon Ray, A. Matthew Smith, Daniel Koch, Paul M. Alsing, S C Ellis, Christopher C. Tison
article en

Abstract

In this proceeding, we describe a simulated model for the characterization of arbitrary unitary matrices implemented by an reconfigurable linear optical network. We build on the method of Hoch et. al, which itself builds on Liang et. al, for characterizing the arbitrary unitary transformation, U, implemented on such devices as an equivalent real bordered form U<sub>rb</sub>. We disscuss how the measurement scheme requires fewer and simpler measurements than. We describe a solution that utilizes a novel algorithm to efficiently recover the complex signs of U<sub>rb</sub> under measurement noise and scaling with system size N.

United States Air Force Research Laboratory (US), Rochester Institute of Technology (US)
Affordable and clean energy
Openalex Percentile: Top 96%
Optical Network Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.