Ghost imaging (GI) is an imaging technique that uses the second-order correlation between two light beams to obtain the image of an object. However, standard GI is affected by optical background noise, which reduces its practical use. We investigated the robustness of an instant ghost imaging (IGI) algorithm against optical background noise and compare it with the conventional GI algorithm. Our results show that IGI is extremely resistant to spatiotemporally varying optical background noise that can change over a large range. When the noise is large in relation to the signal, IGI will still perform well in conditions that prevent the conventional GI algorithm from generating an image because IGI uses signal differences for imaging. Signal differences are intrinsically resistant to common noise modes, so the IGI algorithm is strongly robust against noise. This research is of great significance for the practical application of GI.
The transmission properties of beams in gain fibers are studied with the complex refractive index beam propagation method (CRI-BPM). The method is checked by comparison with an analytic method. The behavior of a gain-guided, index antiguided (GG-IAG) fiber with different gain coefficients is studied. The simulation results show that the signal can transfer in the fiber with almost no loss when the gain coefficient reaches the threshold of the fundamental mode, and the shape of output spot will have no major changes when the gain coefficient is over the thresholds of high-order modes, even when the mode competition is not obvious. The CRI-BPM can predict the changes in light power and light mode at the same time, and will be very useful in the designing of fiber amplifiers and lasers with complex structures. More factors will be considered in this method to provide reference for practical application in our further research.
We propose a new experimentally verified ghost imaging (GI) mechanism, derivative GI. Our innovation is that we use the derivatives of the intensities of the test light and the reference light for imaging. Experimental results show that by combining derivative GI with the standard GI algorithm, multiple independent signals can be obtained in one measurement. This combination greatly reduces the number of measurements and the time required for data acquisition and imaging. Derivative GI intrinsically does not produce the storage-consuming background term of GI, so it is suitable for on-chip implementation and makes practical application of GI easier.
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