The sensitivity of optical measurement is ultimately constrained by the shot noise to the standard quantum limit. It has become a common concept that beating this limit requires quantum resources. A deep-learning neural network free of quantum principle has the capability of removing classical noise from images, but it is unclear in reducing quantum noise. In a coincidence-imaging experiment, we show that quantum-resource-free deep learning can be exploited to surpass the standard quantum limit via the photon-number-dependent nonlinear feedback during training. Using an effective classical light with photon flux of about 9×104 photons per second, our deep-learning-based scheme achieves a 14 dB improvement in signal-to-noise ratio with respect to the standard quantum limit.

We investigate the single-photon transport problem in the system of a whispering-gallery mode microresonator chirally coupled with a two-level quantum emitter (QE). Conventionally, this chiral QE-microresonator coupling system can be studied by the master equation and the single-photon transport methods. Here, we provide a new approach, based on the transfer matrix, to assess the single-photon transmission of such a system. Furthermore, we prove that these three methods are equivalent. The corresponding relations of parameters among these approaches are precisely deduced. The transfer matrix can be extended to a multiple-resonator system interacting with two-level QEs in a chiral way. Therefore, our work may provide a convenient and intuitive form for exploring more complex chiral cavity quantum electrodynamics systems.

一台基于分子双边缘鉴频技术的车载瑞利多普勒激光雷达系统，于2014年至2016年先后在山西忻州（38.42°N 112.72°E）和甘肃酒泉（39.74°N 98.49°E）地区对平流层风场进行连续观测。观测结果表明：18~25 km范围内，酒泉春、秋季节以及忻州冬季均出现了准零风层大气结构，并伴有明显的上下浮动现象，该准零风层结构与2011年夏季新疆乌鲁木齐（42.1°N 87.1°E）多普勒激光雷达系统观测到的结果具有明显差异。分析认为：由于5月与10月处于短暂的季节过渡时期，中纬度地区平流层东风环流尚未稳定导致零风线的上下浮动；2015年1月忻州地区出现平流层准零风层与平流层爆发性增温有关。