Classifying Photonic Topological Phases Using Manifold Learning

Or Yair; Eran Lustig; Ronen Talmon; Mordechai Segev

doi:10.1364/CLEO_QELS.2018.FM1E.6

Conference on Lasers and Electro-Optics
OSA Terchnical Digest (online) (Optica Publishing Group, 2018),
paper FM1E.6
•https://doi.org/10.1364/CLEO_QELS.2018.FM1E.6

Classifying Photonic Topological Phases Using Manifold Learning

Or Yair, Eran Lustig, Ronen Talmon, and Mordechai Segev

CLEO: QELS_Fundamental Science 2018

San Jose, California United States
13–18 May 2018
ISBN: 978-1-943580-42-2

From the session
Topological Optics (FM1E)

Not Accessible

Your library or personal account may give you access

Get PDF
Email
Share
Get Citation
Copy Citation Text
O. Yair, E. Lustig, R. Talmon, and M. Segev, "Classifying Photonic Topological Phases Using Manifold Learning," in Conference on Lasers and Electro-Optics, OSA Terchnical Digest (online) (Optica Publishing Group, 2018), paper FM1E.6.

Export Citation
- BibTex
- Endnote (RIS)
- HTML
- Plain Text
Citation alert
Save article

Abstract

We use Manifold Learning to classify topological phases of photonic systems, from an arbitrary set of measurements without any prior knowledge or assumptions.

PDF Article

More Like This

Manifold Learning for Reducing the Design Complexity of Photonic Nanostructures

Mohammadreza Zandehshahvar, Yashar Kiarashi, Muliang Zhu, Hossein Maleki, Tyler Brown, and Ali Adibi
JTu3A.115 CLEO: Applications and Technology (CLEO:A&T) 2021

Quantitative Phase Maps of Live Cells Classified By Transfer Learning and Generative Adversarial Network (GAN)

Moran Rubin, Omer Stein, Raja Giryes, Darina Roitshtain, and Natan T. Shaked
CW2E.7 Computational Optical Sensing and Imaging (COSI) 2018

Photonic Parity-Time Symmetric Topological Edge States in a Two-Dimensional Lattice

Jiho Noh, Wladimir A. Benalcazar, Taylor L. Hughes, and Mikael C. Rechtsman
FM2Q.2 CLEO: QELS_Fundamental Science (CLEO:FS) 2018

Previous Article Next Article