Fig. 1: Principle illustration of the QCS imaging.

a Principle diagram of the passive QCS imaging approach, see the Materials and methods for experimental details. The radiation signal x of the windmill can be considered as a modulated mixed state that corresponds to the initial quantum state preparation and manipulation in QCS. Our goal is to reconstruct the signal through sparse photon detection, where time-domain single-photon detection corresponds to the process of quantum states detection, and finally obtain the estimated signal through a signal reconstruction algorithm. b The photon-counting image of a simulated windmill house pattern. c QCS imaging result. d Dynamic characteristic spectrum of the signal. Each pixel records the photon arrival time independently, and the characteristic spectrum can be obtained by performing a discrete Fourier transform on the photon arrival time series y = [y₁, y₂, …, y_m, …, y_M]. Signal x can be reconstructed by applying a signal reconstruction algorithm, which will show in Fig. 4. Here, we demonstrate the feasibility of our method solely through a simulated pattern. The two illustrations depict sparse characteristic spectrum lines and a white noise base derived from background noise counts, dark counts, and shot noise of photon counting