Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 22,
  • Issue 3,
  • pp. 031301-
  • (2024)

Ultra-compact and broadband polarization-insensitive mode-order converting power splitter

Not Accessible

Your library or personal account may give you access

Abstract

A polarization-insensitive mode-order converting power splitter using a pixelated region is presented and investigated in this paper. As TE0 and TM0 modes are injected into the input port, they are converted into TE1 and TM1 modes, which evenly come out from the two output ports. The finite-difference time-domain method and direct-binary-search optimization algorithm are utilized to optimize structural parameters of the pixelated region to attain small insertion loss, low crosstalk, wide bandwidth, excellent power uniformity, polarization-insensitive property, and compact size. Experimental results reveal that the insertion loss, crosstalk, and power uniformity of the fabricated device at 1550 nm are 0.57, −19.67, and 0.094 dB in the case of TE polarization, while in the TM polarization, the relevant insertion loss, crosstalk, and power uniformity are 0.57, −19.40, and 0.11 dB. Within a wavelength range from 1520 to 1600 nm, for the fabricated device working at TE polarization, the insertion loss, crosstalk, and power uniformity are lower than 1.39, −17.64, and 0.14 dB. In the case of TM polarization, we achieved an insertion loss, crosstalk, and power uniformity less than 1.23, −17.62, and 0.14 dB.

© 2024 Chinese Laser Press

PDF Article

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.