We develop a new framework to optimize and understand uncertainty from in situ strong field measurements of laser field parameters. We present the first derivation of quantum and classical Fisher information for an electron undergoing strong-field ionization. This is used for parameter estimation and to characterize the uncertainty of the ponderomotive energy, directly proportional to laser intensity. In particular, the quantum and classical Fisher information for the momentum basis displays quadratic scaling over time. This can be linked to above-threshold ionization interference rings for measurements in the momentum basis and to the `ponderomotive phase' for the `ideal' quantum measurements. Preferential scaling is found for increasing laser pulse length and intensity. We use this to demonstrate for in situ measurements of laser intensity, that high resolution momentum spectroscopy has the capacity to reduce the uncertainty by over $25$ times compared to measurements employing the ionization rate, while using the `ideal' quantum measurement would reduce it by a further factor of $2.6$. A minimum uncertainty of the order $2.8 \times 10^{-3}~\%$ is theorized for this framework. Finally, we examine previous in situ measurements formulating a measurement that matches the experimental procedure and suggest how to improve this.
Chernoff Information Bottleneck for Covert Quantum Target Sensing
Dipartimento di Fisica e Astronomia, Università di Firenze（佛罗伦萨大学物理与天文系）；Istituto Nazionale di Fisica Nucleare, Sezione di Firenze（意大利国家核物理研究所佛罗伦萨分部）；Quantum metrology and nano technologies division, INRiM（INRiM量子计量与纳米技术部）
Anonymous quantum sensing robust against state preparation errors
Graduate School of Pure and Applied Sciences, University of Tsukuba（筑波大学理工学综合研究科）；Graduate School of Science and Technology, Keio University（庆应义塾大学理工学部）；Department of Mathematics, Waseda University（早稻田大学数学系）；NTT Communication Science Laboratories, NTT Corporation（日本电信电话公司通信科学实验室）；NTT Research Center for Theoretical Quantum Information, NTT Corporation（日本电信电话公司理论量子信息研究中心）；Information Technology R&D Center, Mitsubishi Electric Corporation（三菱电机株式会社信息技术研发中心）
Deep Neural Network-assisted improvement of quantum compressed sensing tomography
ICFO - Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology（ICFO - 光子科学研究所，巴塞罗那科学技术学院）；ICREA（加泰罗尼亚高级研究学院）；Physics Department E. Pancini - Università degli Studi di Napoli Federico II（那不勒斯费德里科二世大学E. Pancini物理系）
