Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • 2013 Conference on Lasers and Electro-Optics - International Quantum Electronics Conference
  • (Optica Publishing Group, 2013),
  • paper CE_3_2

Photon-counting Raman Spectroscopy of Silicon Nanowires

Not Accessible

Your library or personal account may give you access

Abstract

Raman scattering can be exploited for amplification in optical fiber telecommunications or, chemical identification in spectroscopy, but represents a source of detrimental noise photons for quantum communications. The spectral distribution of spontaneous Raman scattering (SpRS) can be measured in bulk samples with the free-space 90° scattering method [1]. In long fibers the SpRS spectra can be measured using a pulsed laser to achieve measurable signals [2], incompatible with the damage threshold of many on-chip devices. Measurements of stimulated Raman scattering have been performed using nonlinear pump-probe techniques [3], requiring the addition of either a highly tunable or ultra-broad bandwidth probe. Recently photon-counting techniques have been demonstrated to measure weak SpRS signals in fibers [4–6], however no direct measurements of the SpRS spectra of nanophotonic chip-devices over a broad bandwidth have been performed.

© 2013 IEEE

PDF Article
More Like This
Raman Spectroscopy with Single Photon Counting

Santosh Kumar, Yehong Li, Tianhang Huo, Henry Du, and Yuping Huang
JM7A.120 Frontiers in Optics (FiO) 2023

Design of a Photon-Counting System for Raman Spectroscopy

F. R. Pérez, C. Del Valle, L. Reyes, J. Tobón, C. Barrero, and A. Velásquez
JSuA8 Frontiers in Optics (FiO) 2007

Ultrafast optical-pump terahertz-probe spectroscopy of individual silicon nanowires

Taeyong Kim, Sangwan Sim, Jungmok Seo, Jaehong Lee, Heetak Han, Taeyoon Lee, and Hyunyong Choi
QM3D.2 CLEO: QELS_Fundamental Science (CLEO:FS) 2013

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.