Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 15,
  • Issue 12,
  • pp. 121901-
  • (2017)

Conical sum-frequency generation in a bulk anomalous-like dispersion medium

Not Accessible

Your library or personal account may give you access

Abstract

We observe conical sum-frequency generation in a bulk anomalous-like dispersion medium, which is attributed to complete phase-matching of one fundamental wave and the scattering wave of the other fundamental wave. In addition, efficient sum-frequency output is achieved making use of total internal reflection with conversion efficiency of 7.9% by only one reflection. The experiment proposes a new phase-matching mode under an anomalous-like dispersion condition, which suggests potential applications in efficient frequency conversion.

© 2017 Chinese Laser Press

PDF Article
More Like This
Normal, degenerated, and anomalous-dispersion-like Cerenkov sum-frequency generation in one nonlinear medium

Ning An, Yuanlin Zheng, Huaijin Ren, Xiaohui Zhao, Xuewei Deng, and Xianfeng Chen
Photon. Res. 3(4) 106-109 (2015)

Large acceptance of non-collinear phase-matching second harmonic generation on the surface of an anomalous-like bulk dispersion medium

Xiaojing Wang, Huaijin Ren, Ning An, Xiaohui Zhao, Yuanlin Zheng, and Xianfeng Chen
Opt. Express 22(23) 28234-28239 (2014)

Sum-frequency nonlinear Cherenkov radiation generated on the boundary of bulk medium crystal

Xiaojing Wang, Jianjun Cao, Xiaohui Zhao, Yuanlin Zheng, Huaijin Ren, Xuewei Deng, and Xianfeng Chen
Opt. Express 23(25) 31838-31843 (2015)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

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.