High precious automatic balanced homodyne detector for quantum information processing based on proportional-integral-derivative

Zhuoran Dai; Zhenghua Li; Dengke Qi; Xiangyu Wang; Bin Luo

doi:10.1117/12.3017348

15 December 2023 High precious automatic balanced homodyne detector for quantum information processing based on proportional-integral-derivative

Zhuoran Dai, Zhenghua Li, Dengke Qi, Xiangyu Wang, Bin Luo

Author Affiliations +

Proceedings Volume 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023); 129710A (2023) https://doi.org/10.1117/12.3017348
Event: Third International Conference on Optics and Communication Technology (ICOCT 2023), 2023, Changchun, China

Abstract

Balance homodyne detector plays an important role in quantum information processing, which is used to achieve high precision quantum measurement. In the actual measurement, the symmetry of the two arms of the detector will become worse due to the influence of objective factors such as environment and temperature, which will lead to the performance decline and the wrong quantum information. In this paper, a high precious automatic balanced homodyne detector based on Proportional-Integral-Derivative is proposed, in order to realize the automatic balancing of the detector, which can improve the common mode rejection ratio of 22.4 dB, so as to complete the stable and high precision quantum information processing.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhuoran Dai, Zhenghua Li, Dengke Qi, Xiangyu Wang, and Bin Luo "High precious automatic balanced homodyne detector for quantum information processing based on proportional-integral-derivative", Proc. SPIE 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023), 129710A (15 December 2023); https://doi.org/10.1117/12.3017348

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available