A Differential Detection Method Based on a Linear Weak Measurement System.

Nian Xiong,Tian Guan,Yang Xu,Dongmei Li,Yonghong He,Suyi Zhong,Xuesi Zhou,Lixuan Shi

doi:10.3390/s19112473

Abstract

Self-reference detection is necessary and important to a biosensor. The linear weak measurement system based on total internal reflection has attracted widespread attention due to its high stability, label-free detection, and easy integration. In this paper, we propose a differential detection method based on the linear total internal reflection weak measurement system. We introduce the half-wave plate (HWP) to convert the H light and the V light to each other, thereby obtaining the difference in phase change of the optical path before and after the HWP. Experiments show that the system can not only achieve differential detection, but also has high stability. The linear differential weak measurement system proposed in this paper not only provides a new differential measurement method for real-time biosensors, but also enriches the types of weak measurement sensors.

Highlights

IntroductionRealized by Ritchie et al in 1991 for the first time in experiments [2]
The principle of weak value amplification (WVA) was proposed in 1988 by Aharonov et al [1]and realized by Ritchie et al in 1991 for the first time in experiments [2]
In this paper we proposed a differential weak value amplification (WVA) measurement method that can be based on a linear common-path weak measurement system

Summary

Introduction

Realized by Ritchie et al in 1991 for the first time in experiments [2]. It has gradually attracted widespread attention in society. With proper pre-selection and post-selection, this slight offset can be amplified and eventually be read out from the pointer received by the detector, which is the so-called weak value amplification. Differential detection methods are important in high precision measurements, as a self-compensating switchable measurement method where dielectric properties are highly important. These methods compensate environment effect, voltage offset, frequency drift, and temperature influence, such as we can see in [12,13]

Methods

Discussion

Conclusion