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Communications Physics

Weak signal extraction in non-stationary channel with weak measurement

Qi Song, Hongjing Li, Jingzheng Huang, Peng Huang, Xiaorui Tan, Tao Yu, Chunhui Shi, Guihua Zeng

Published Dec 21, 2023• 11 citations
Publisher

Abstract

Abstract An emerging challenge of integrated communication and sensing is the extraction of weak sensing signals transmitted through an unknown non-stationary channel. In this work, we propose a weak signal extraction method with weak measurement. Taking advantage of time division multiplexing, we preliminarily estimate the channel via adjustable finite impulse response filter, further suppressing the interfering signal caused by background noises via spectrum shift. By subsequently using the time-varying phase estimation method via weak measurement, the real-time detection of weak signals in the non-stationary channel is achieved. We demonstrate via theoretical analysis and confirmatory experiment that our method is able to amplify the phase shift, to suppress technical noise and to improve detection resolution limit, while proving robust against light source fluctuations, initial phase differences and detector saturation. The method hence enables weak sensing signal extraction with a low signal-to-noise ratio non-stationary channel. Furthermore, we interface our measurement method to squeezed light sources, offering the possibility of surpassing standard quantum limit.

DOI
10.1038/s42005-023-01492-7

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Abstract An emerging challenge of integrated communication and sensing is the extraction of weak sensing signals transmitted through an unknown non-stationary channel. In this work, we propose a weak signal extraction method with weak measurement. Taking advantage of time division multiplexing, we preliminarily estimate the channel via adjustable finite impulse response filter, further suppressing the interfering signal caused by background noises via spectrum shift. By subsequently using the time-varying phase estimation method via weak measurement, the real-time detection of weak signals in the non-stationary channel is achieved. We demonstrate via theoretical analysis and confirmatory experiment that our method is able to amplify the phase shift, to suppress technical noise and to improve detection resolution limit, while proving robust against light source fluctuations, initial phase differences and detector saturation. The method hence enables weak sensing signal extraction with a low signal-to-noise ratio non-stationary channel. Furthermore, we interface our measurement method to squeezed light sources, offering the possibility of surpassing standard quantum limit.
Abstract Reliable detection of weak phase signals under significant channel loss and complex noise environments is a crucial step for practical applications of optical integrated communication and sensing systems. In this letter, we propose and experimentally demonstrate an enhanced long-distance weak signal transmission method assisted by weak measurement. Performing heterodyne detection and light intensity compensation on two nearly symmetric post-selected paths, the method enables real-time estimation of a time-varying phase while maintaining robustness against technical noises proportional to light intensity or photon number, detector common-mode noise, and significant attenuation over long-distance transmission. Experimental results indicate a potential phase sensitivity at the level of 10 −8 rad even with a signal light intensity attenuation of 48.1 dB. Potentially, combining the adaptive adjustment strategy, the method may provide a viable solution in remote weak signal detection and extraction, thereby contributing to optical integrated communication and sensing.
Extending quantum sensing to time-varying parameter estimation is a potential and challenging task in practical application. To achieve this goal, we propose an adaptive method to estimate an unknown time-varying parameter through light-intensity split detection and the insertion of reference phases in the weak measurement. Theoretical analysis and numerical simulation are applied to illustrate the feasibility and practical applications of our method. The results demonstrate that the method has adjustable sensitivity and linear dynamic range, and is robust to nonideal measurement conditions. Moreover, we analyze the precision of our method and show that its precision limit can surpass the standard quantum limit and approach the Heisenberg scaling when using a squeezed light of optimal Gaussian state.
The real-time estimation of a time-varying phase is of great importance in several fields. In order to estimate a time-varying phase with high precision and sensitivity, we propose and experimentally demonstrate an adaptive phase estimation method via weak value amplification by splitting the light into sensing path and monitoring path. In the proposed method, the phase shift can be amplified, an adjustable sensitivity and linear dynamic range can be obtained through the insertion of the reference phase, and a full-range phase estimation could be realized via an appropriate adjustment strategy. Furthermore, detectors with a higher resolution could be selected to detect weak signal by the adjustment of attenuation. Potentially, the phase estimation precision of about 10−8 rad could be achieved with the available equipment.
Weak measurement is employed to measure faint signals due to its capability to amplify detection results above technical noise. However, achieving high amplification effects requires accurate adjustment to the experimental system. Estimating unknown time-varying phases, accurately estimating phases, and sensitively perceiving phase changes pose challenges, demanding the system to continuously remain at the appropriate working range. To address this issue, we propose a neural network-based adaptive weak measurement scheme via single-channel light intensity detection. Through machine learning calibrating the experimental system, the reference phase can be dynamically and accurately adjusted, accommodating time-varying phase changes and ensuring the system operates optimally. Compared with traditional dual-channel weak measurement systems, the scheme reduces experimental complexity. Meanwhile, by accurately adjusting the reference phase, the scheme has higher sensitivity and estimation precision compared to the non-modulated scheme. We validate the effectiveness of the scheme in estimating the period and stochastic time-varying phase. The proposed method highlights the advancement of machine learning in weak measurement systems and can also be applied to other quantum-enhanced measurement schemes.
Phase estimation has attracted much attention in the field of sensing, where weak measurement has become an effective solution for the study of small physical quantities because of its anomalous amplification property. However, it is difficult for weak measurement to cope with large low-frequency noise signals in the environment due to its extremely narrow linear range, which makes the extension of weak measurement to practical applications a challenging task. In order to solve this issue, we propose and experimentally verify a phase demodulation scheme based on weak measurement, which solves the problem of working point offset caused by the noise through artificially introducing a high-frequency carrier and performing demodulation operations on the output light. The experimental results show that the scheme can improve the signal-to-noise ratio by 17 dB compared to standard weak measurement and ensures low distortion in phase demodulation. Moreover, the scheme is not limited to a specific modulation depth, which greatly improves the robustness of the scheme.
Spectral analysis technology in optical signal detection can obtain the spectral characteristics of matter according to the wavelength or frequency information of the optical signal. Commonly used spectral analysis techniques include grating spectrometer, Fourier transform infrared spectrometer (FTIR), Raman spectrometer, etc. In order to improve the measurement of optical signal, due to the limitation of detector detection bandwidth and system noise and external interference, this paper proposes an optical signal estimation scheme based on weak measurement method. Moreover, compared with the original weak measurement scheme, the detection time of the new scheme proposed in this paper breaks through the limitation of Nyquist sampling theorem, has the performance advantage of resisting aliasing interference, and can effectively improve the signal-to-noise ratio of the system by extending the detection time. This paper presents a new weak measurement theory scheme for optical signals. Theoretical research studies show that the scheme can estimate the amplitude and phase of the optical signal and recover the time domain by setting the dynamic phase factor with time for the previous or post-selection process. Because the detection time of the scheme is not limited by the Nyquist sampling theorem, the new scheme has the performance advantage of anti-aliasing interference, which effectively solves the limitation of the detector detection bandwidth in the original scheme.