Abstract
Quantum correlations become formidable tools for beating classical capacities of measurement. Preserving these advantages in practical systems, where experimental imperfections are unavoidable, is a challenge of the utmost importance. Here we propose and realize a quantum ghost imaging protocol stemming from the differential ghost imaging, a scheme elaborated so far in the limit of bright thermal light, particularly suitable in the relevant case of faint or sparse objects. The extension toward the quantum regime represents an important step as quantum correlations allow low-brightness imaging, desirable for reducing the absorption dose. Furthermore, we optimize the protocol in terms of signal-to-noise ratio, to compensate for the detrimental effects of detection noise and losses. We perform the experiment using spontaneous parametric down conversion light in a microscope configuration. The image is reconstructed exploiting nonclassical intensity correlation in the low photon flux regime, rather than photon pairs detection coincidences. On the one side, we validate the theoretical model and on the other we show the applicability of this technique by imaging biological samples.
Highlights
Ghost imaging (GI) was theoretically proposed in 1994 [1] and experimentally demonstrated by Pittman et al one year later [2] by using quantum correlations generated by spontaneous parametric down conversion (SPDC)
In order to demonstrate the nonclassicality of the detected intensity correlation, we evaluate the noise reduction factor (NRF) parameter defined as NRF = 2(n1 − n2) / n1 + n2, which is the variance of the photon number difference between a pair of correlated pixels normalized by their sum
The attention toward the DGI is justified since it offers significant signal-to-noise ratio (SNR) improvements over the conventional GI, in particular in the presence of small or highly transparent objects
Summary
Ghost imaging (GI) was theoretically proposed in 1994 [1] and experimentally demonstrated by Pittman et al one year later [2] by using quantum correlations generated by spontaneous parametric down conversion (SPDC). The so-called “differential GI” (DGI) proposed in 2010 by Ferri et al [34] has received much attention due to its relevant practical impact, addressing the problem of reconstructing small or faint objects in the field of view. In this situation the conventional GI typically fails because it requires an unaffordable number of acquisitions in order to reach a sufficiently high SNR. In view of real applications, a biological object, a (285 μm) wasp wing detail, is reconstructed with a spatial resolution of 5 μm
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