
- Photonics Research
- Vol. 10, Issue 3, 668 (2022)
Abstract
1. INTRODUCTION
In 1956, Hanbury Brown and Twiss (HBT) [1,2] proposed an intensity interferometer to measure the angular diameter of a star. The star light as natural light obeys the photon statistics of a thermal light field, i.e., the bunching correlation for bosons, where the second-order correlation coefficient
Due to the Pauli exclusive principle and Fermi–Dirac statistics, fermions in a thermal source can manifest antibunching effect with
In conventional optical imaging, the most popular light sources come from natural sunlight. When sunlight is applied to GI, the main obstacle is its fast temporal fluctuation in the face of present, relatively slower response detectors. Liu
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2. THEORY
Considering a polarized beam of intensity
Figure 1.(a) Schematic diagram of the PBS model: two CMOS-based image sensors (detectors) for recording intensity correlation. When the detector in the black-dotted box is replaced with an object and a bucket detector, the setup can facilitate GI experiments. A programmable SLM is utilized to generate the PF of the wavefront with adjustable coherence time. A 4-f lens system (not shown) is used to image the SLM plane onto the detection plane. (b) Schematic diagram of GI for pseudo-natural light: an ordinary BS is introduced to obtain additional reference beam for division and subtraction operations. P, linear polarizer; HWP, half-wave plate; L, lens; RGG, rotating ground glass.
Since
To be clear, we show two examples. (i) Random linearly polarized light with polarization angle
A general polarization state of monochromatic plane wave can be described by the Stokes vector on the Poincaré sphere [50],
We now consider the case in which the beam of intensity
The intensity correlation functions of outgoing beams from the PBS can be factorized according to independent IF and PF. Since
To surpass the obstacle, we propose a scheme of combination of a beam splitter (BS) and a PBS in Fig. 1(b). The pseudo-natural light is divided into two parts after the BS with the intensities
We now perform some basic operations between the random variables
As a result, all the correlation functions related to the PF only have been extracted. Second, we introduce the subtraction operations
The results are exactly the same as the first two equations in Eq. (3), but here the cross-correlations of two polarization modes replace the autocorrelations of each polarization mode. Since two correlated beams are ready, the present method is convenient for GI performance.
3. RESULTS
A. Experimental Observations of Antibunching and Superbunching
In the experimental performance, we discuss three cases for the PF of the Bernoulli distribution with the symmetrical polarization configuration
Figure 2.Second-order correlation coefficients as functions of
For Case 1, when the coherent light drives the SLM, we can observe
For Case 2 we measure
For Case 3, by combination of an ordinary BS and a PBS in Fig. 1(b), we perform the division operation and subtraction operation mentioned above to obtain the original antibunching correlation of PF and superbunching correlation of both IF and PF, respectively. By the division operation,
In the experiment, the values of p are limited by the SLM and PBS in the range
B. Positive and Negative Ghost Images
Next, we observe HBT curves and perform GI experiments. As shown in Fig. 1, the detector in the dotted box is replaced with an object and a bucket detector. The experimental results are presented in Figs. 3 and 4. We first consider the PF source driven by coherent light. For the symmetric Bernoulli distribution (
Figure 3.HBT curves of bunching and antibunching effects and corresponding GIs for different fluctuation sources. (a1) and (b1) Symmetric Bernoulli distribution of PF (
Figure 4.Same as Fig.
In Fig. 4, pseudo-natural light is formed with the symmetric Bernoulli distribution of PF driven by pseudo-thermal light. We consider two cases: (
C. Polarization-Sensitive GI
The combination of two opposite photon correlations can find a variety of applications. Here we demonstrate polarization-sensitive imaging as getting started, which is developed to enhance the visibility of targets in scattering media [52]. As shown in Fig. 5(a),
Figure 5.(a) Schematic diagram of GI with polarization identification. (b1) Positive image with
D. Customization of the Spatial Pattern of Second-Order Correlation Functions
In general, the combination of classical spatial antibunching and bunching effects also provides an alternative toolbox for the customization of the second-order correlation functions. For example, the second-order correlation coefficient can be continuously adjustable in a wide range across 1, which has been shown in Fig. 2. Also, the spatial structure of the second-order correlation function can be tailored based on the opposite spatial correlation distributions.
The schematic diagram of the second example is shown in Fig. 6, which is very similar to Fig. 5(a), but the two beams corresponding to independent IF and PF sources are offset by an adjustable mirror. Figure 7(a) shows the simulation object (
Figure 6.Schematic diagram of the customization of second-order correlation functions. Similar to Fig.
Figure 7.Customization of various unique second-order correlation functions or point spread functions of the GI system. (a) Simulation object; (b1) hollow-like pattern; and (b2)–(b4) peak dip-like patterns with different directions by changing the angle of the mirror in Fig.
Then we introduce the offset of six pixels between the two beams. Two spots with a peak and a dip in the second-order correlation functions are formed with different directions [Figs. 7(b2)–7(b4)] by adjusting the angle of the mirror. With these tailored second-order correlation functions, we can observe the various reconstructed images [Figs. 7(c2)–7(c4)] with edges enhanced at corresponding directions. For comparisons of edge quality, Figs. 7(d1)–7(d4) show one-dimensional (1D) profiles of images in the direction of the corresponding arrow. Hence, the introduction of PF has expanded more unexpected possibilities for GI applications.
4. CONCLUSION
In summary, we have demonstrated antibunching and superbunching effects in the PF of classical light and applied them to high-quality positive and negative GI, and proposed two application examples. Usually either the superbunching effect or the anti-bunching effect can be found in some quantum optical systems. Our model is completely limited in the scope of classical optics but covers both superbunching and antibunching effects. The present scheme is very simple and significantly effective for a special light source with a multiple and broad correlation property. At present, however, while pseudo-thermal light with IF only is still the most popular source in correlation optics, our work affords an alternative choice with enhancements. Sunlight offers humans a visible world free of charge. As natural sunlight contains both IF and PF, our work also opens the way for wide applications for natural light.
APPENDIX A
The coherent beam in this experiment comes from a continuous semiconductor laser (Laserwave, LWGL532 160105) with a center wavelength of 532 nm, and the actual optical power is approximately 160 mW. A transmissive SLM (Daheng Optics, GCI-77) is utilized to generate the PF, so we can artificially preload the profile on the SLM to modulate the polarization distribution of the wavefront. The coherence time of the PFs of this light source is slow enough such that we can easily observe the antibunching effect with CMOS-based detectors (Sony, IMX226; DAHENG IMAGING, MER-133-54U3M), whose detecting signal-to-noise ratio is 37.79 dB and quantum efficiency is
Figure 8.Experimental calibration of SLM. (a) Relationship between the parameter
Figure 9.Raw measurement data of 800 shots that obey the Bernoulli distribution in the second-order correlation coefficient measurement.
Figure 10.Raw speckle patterns of pseudo-thermal light. (a) Without and (b) with passing through the SLM.
Figure 11.Probability density distributions of speckles for pseudo-natural light. (a) Spatial domain, statistics are made for all the speckles in a pattern of
Figure 12.Experimental details of polarization-sensitive GI. (a) Experimental setup of second-order correlation coefficient measurement of the hybrid illumination and the polarization-sensitive GI. P, polarizer; R, reflector; ND, neutral density filter; HWP, half-wave plate; L, imaging lens; OBJ, object; the three optical elements (HWP-PBS-HWP) in the purple dotted box can continuously adjust the intensity and set the polarization angle of the IF source to be oriented at 45°. (b) Tunable correlation of the hybrid illumination with the change of the relative intensity ratio
In almost all imaging modalities, to obtain a polarization-sensitive image, one must collect the two images of two mutually orthogonal components, and then complete the differential operation in the postprocessing. However, in our GI modality, by multiplexing bunching and antibunching into two orthogonal polarization components, only a single round of acquisition is required, and no subsequent differential operations are needed. It is an interesting and special feature that only occurs in GI modality using the hybrid illumination. Also, the edge-enhanced GI experiment presented in Fig.
For an imaging signal
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