Criticality-enhanced global frequency sensing with a monitored Kerr parametric oscillator via extended Kalman filter

Fuente: arXiv
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Auteurs principaux: Zhang, Cheng, Cirio, Mauro, Li, Xin-Qi, Liang, Pengfei
Format: Preprint
Publié: 2026
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author Zhang, Cheng
Cirio, Mauro
Li, Xin-Qi
Liang, Pengfei
author_facet Zhang, Cheng
Cirio, Mauro
Li, Xin-Qi
Liang, Pengfei
contents We analyze a global sensing scenario in which the frequency of a monitored Kerr parametric oscillator is estimated assuming limited prior information. The frequency is estimated in real-time by continuously monitoring the oscillator quadrature through homodyne detection and processing the resulting photocurrent with an extended Kalman filter (EKF). Due to the sensor nonlinearity, individual EKF trajectories do not always converge to the true unknown frequency in the long-time limit. However, we show that the statistical distribution of the frequency estimates does exhibit a sharp peak around the true value in the same limit. Leveraging this key statistical property, we develop a global sensing protocol assisted by adaptive control of the sensor parameters to harness critical enhancement. We present numerical evidence that this criticality-enhanced frequency estimation remains robust under low detection efficiency.
format Preprint
id arxiv_https___arxiv_org_abs_2603_11587
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Criticality-enhanced global frequency sensing with a monitored Kerr parametric oscillator via extended Kalman filter
Zhang, Cheng
Cirio, Mauro
Li, Xin-Qi
Liang, Pengfei
Quantum Physics
We analyze a global sensing scenario in which the frequency of a monitored Kerr parametric oscillator is estimated assuming limited prior information. The frequency is estimated in real-time by continuously monitoring the oscillator quadrature through homodyne detection and processing the resulting photocurrent with an extended Kalman filter (EKF). Due to the sensor nonlinearity, individual EKF trajectories do not always converge to the true unknown frequency in the long-time limit. However, we show that the statistical distribution of the frequency estimates does exhibit a sharp peak around the true value in the same limit. Leveraging this key statistical property, we develop a global sensing protocol assisted by adaptive control of the sensor parameters to harness critical enhancement. We present numerical evidence that this criticality-enhanced frequency estimation remains robust under low detection efficiency.
title Criticality-enhanced global frequency sensing with a monitored Kerr parametric oscillator via extended Kalman filter
topic Quantum Physics
url https://arxiv.org/abs/2603.11587