Abstract Quantum metrology has emerged as a crucial paradigm for enhancing measurement sensitivity beyond classical limits. While standard weak measurement and static biased phase methods can effectively amplify extremely small signals, they fundamentally suffer from a trade-off between postselection probability and linear response range, leaving them vulnerable to parameter drift. Motivated by realistic experimental applications such as measuring optical birefringence or thickness using a polarization-frequency Sagnac interferometer, we propose an adaptive biased weak measurement (ABWM) scheme that combines the sensitivity enhancement of biased weak measurement with a feedback-assisted adjustment of the bias phase. By dynamically updating the bias phase in response to measurement outcomes, the system can track slow parameter variations and maintain nearoptimal estimation precision. Numerical simulations under technical noise demonstrate reliable convergence from multiple random initial bias phases and show that the proposed adaptive- β strategy achieves more accurate dynamic tracking than standard weak measurement and static biased weak measurement. Our results suggest that ABWM provides a flexible and resource-efficient strategy for high-precision quantum metrology in realistic experimental scenarios.
Abstract Quantum metrology has emerged as a crucial paradigm for enhancing measurement sensitivity beyond classical limits. While standard weak measurement and static biased phase methods can effectively amplify extremely small signals, they fundamentally suffer from a trade-off between postselection probability and linear response range, leaving them vulnerable to parameter drift. Motivated by realistic experimental applications such as measuring optical birefringence or thickness using a polarization-frequency Sagnac interferometer, we propose an adaptive biased weak measurement (ABWM) scheme that combines the sensitivity enhancement of biased weak measurement with a feedback-assisted adjustment of the bias phase. By dynamically updating the bias phase in response to measurement outcomes, the system can track slow parameter variations and maintain nearoptimal estimation precision. Numerical simulations under technical noise demonstrate reliable convergence from multiple random initial bias phases and show that the proposed adaptive- β strategy achieves more accurate dynamic tracking than standard weak measurement and static biased weak measurement. Our results suggest that ABWM provides a flexible and resource-efficient strategy for high-precision quantum metrology in realistic experimental scenarios.
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.
Recently, biased quantum weak measurement has shown higher precision than both conventional measurement and standard quantum weak measurement in optical metrology. In this work, a scheme of detecting the ultrasmall rotation velocity in Sagnac's interferometer with biased quantum weak measurement is proposed. In biased quantum weak measurement, additional progress of pre-coupling is introduced in standard quantum weak measurement to enhance the sensitivity for the estimated parameter, and the cost of the reduction of photons in the post-selection by pre-coupling may not impact the measurement because eliminating the saturation effect of the detector response. In addition, our numerical results show that the scheme with biased quantum weak measurement can obtain a higher sensitivity for rotation velocity measurement than the scheme with standard quantum weak measurement.
We experimentally demonstrate a sub-nanometer optical path difference (OPD) metrology scheme based on biased weak measurement (BWM) with real weak values using a classical coherent light source. By introducing a controlled bias phase in a Mach-Zehnder interferometric configuration, the proposed approach enables enhanced detection of sub-nanometer OPD variations while maintaining compatibility with common optical components and narrowband light sources. We systematically compare the measurement response, sensitivity, and signal-to-noise ratio (SNR) of BWM with those of standard weak measurement (SWM) and conventional interferometric measurement (CM) under identical experimental conditions. Relative to SWM, BWM provides an approximately fourfold enhancement in measurement response within the linear operating range, while achieving a (94 ± 10)-fold signal amplification compared with CM. Furthermore, the measured SNR exhibits an order-of-magnitude improvement over CM under detector-saturation-limited measurement conditions. Experimentally, the BWM scheme achieves a minimum detectable OPD of (5.6 ± 0.36) × 10 −4 nm, obtained from Allan deviation analysis. These results highlight the potential of weak measurement as a practical strategy for high-precision optical path metrology and precision interferometric 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.
Squeezed light enables quantum-enhanced phase estimation, with crucial applications in both fundamental physics and emerging technologies. To fully exploit the advantage provided by this approach, estimation protocols must remain optimal across the entire parameter range and resilient to instabilities in the probe state. In this context, strategies that rely on pre-calibrated squeezing levels are vulnerable to degradation over time and become sub-optimal when experimental conditions fluctuate. Here, we develop an adaptive multiparameter estimation strategy for ab-initio phase estimation, achieving sub-shot noise limit precision in the full periodicity interval [0, π), without relying on prior knowledge of the squeezing parameter. Our approach employs real-time feedback to jointly estimate both the optical phase and the squeezing level, ensuring robustness against experimental drifts and calibration errors. This self-calibrating scheme establishes a reliable quantum-enhanced sensing framework, opening new routes for practical scenarios and scalable distributed sensor networks using squeezed light.
An adaptive correction algorithm is demonstrated based on weak measurement, which introduces a feedback and an additional interaction to the system and can dynamically adjust the operating point in accordance with the condition of the estimated phase change. Two schemes, fast adaptive correction and slow adaptive correction, are proposed for different conditions of the modulation device. Fast adaptive correction scheme can realize a real-time correction and maintain the high sensitivity. Slow adaptive correction scheme, as a supplement, can correct the distortion of the measured parameter by changing the measuring period. These two schemes are useful for high precision phase estimation with time in modern physics and practical applications, including, but not limited to, timing synchronization, accurate distance measurement, and gravity wave detection. Moreover, we discuss the deviation of the adaptive correction for considering system noise in practical measurement.