Ghost imaging [1,2] is an experimental technique that extracts higher-dimensional information from a single-pixel camera (or a “bucket” detector). The experimental setup typically consists of a beam splitter that splits the incident light into two paths: one going through the sample and the bucket detector, the other reaching a pixelated detector to measure the spatial profile of the incident light. By correlating the bucket detector reading and the spatial measurement of the incident light, one can reconstruct the spatial structure of the sample, without ever directly measuring the sample [3-7]. Similarly, one can apply the principles of ghost imaging in the time [8,9] and frequency [10-13] domain to probe the temporal and spectral features of the sample. The shot-to-shot variation in the measurement of the incident light is critical for the reconstruction of the sample. Whereas traditional imaging methods fight to reduce noise, ghost imaging exploits shot-to-shot jitter to extract new information from our experiments. Machine learning algorithms are a critical part of ghost imaging reconstruction. As opposed to traditional correlation analysis, machine learning algorithms exploit prior knowledge of the sample to improve convergence of the reconstruction and reduce the acquisition time and sample damage .
: Erkmen, Baris I., and Jeffrey H. Shapiro. "Ghost imaging: from quantum to classical to computational." Advances in Optics and Photonics 2.4 (2010): 405-450.
: Duarte, Marco F., et al. "Single-pixel imaging via compressive sampling." IEEE signal processing magazine 25.2 (2008): 83-91.
 Pelliccia, Daniele, et al. "Experimental x-ray ghost imaging." Physical review letters 117.11 (2016): 113902.
 Yu, Hong, et al. "Fourier-transform ghost imaging with hard X rays." Physical review letters 117.11 (2016): 113901.
 Zhang, Ai-Xin, et al. "Tabletop x-ray ghost imaging with ultra-low radiation." Optica 5.4 (2018): 374-377.
 Khakimov, Roman I., et al. "Ghost imaging with atoms." Nature 540.7631 (2016): 100.
 Li, S., et al. "Electron ghost imaging." Physical review letters121.11 (2018): 114801.
 Ratner, D., et al. "Pump-probe ghost imaging with SASE FELs." Physical Review X 9.1 (2019): 011045.
 Wu, Han, et al. "Temporal ghost imaging using wavelength conversion and two-color detection." Optica 6.7 (2019): 902-906.
 Amiot, Caroline, et al. "Supercontinuum spectral-domain ghost imaging." Optics letters 43.20 (2018): 5025-5028.
 Janassek, Patrick, Sébastien Blumenstein, and Wolfgang Elsäßer. "Ghost spectroscopy with classical thermal light emitted by a superluminescent diode." Physical Review Applied 9.2 (2018): 021001.
 Kalashnikov, Dmitry A., et al. "Infrared spectroscopy with visible light." Nature Photonics 10.2 (2016): 98.
 Scarcelli, Giuliano, et al. "Remote spectral measurement using entangled photons." Applied physics letters 83.26 (2003): 5560-5562.
 Boyd, Stephen, et al. "Distributed optimization and statistical learning via the alternating direction method of multipliers." Foundations and Trends® in Machine learning 3.1 (2011): 1-122.