Further improving the axial resolution is paramount for three-dimensional optical imaging systems. Vortex beams are being widely applied in 3D microscopy techniques. Here we theoretically investigate the ultimate resolution limits using Laguerre-Gauss (LG) beams. Various kinds of superpositions can nowadays be easily prepared by spatial light modulators (SLM). It has been keenly shown that LG beams’ superpositions possess more information than pure LG beams yet do not saturate the ultimate limit with a simple intensity scan. More sophisticated detection schemes based on quantum super-resolution protocols are investigated here to retrieve the discarded information.
We introduce a new generation of 3D imaging devices based on quantum plenoptic imaging. Position-momentum entanglement and photon number correlations are exploited to provide a scan-free 3D image after post-processing of the collected light intensity signal. We explore the steps toward designing and implementing quantum plenop- tic cameras with dramatically improved performances, unattainable in standard plenoptic cameras, such as diffraction-limited resolution, large depth of focus, and ultra-low noise. However, to make these new types of devices attractive to end-users, two main challenges need to be tackled: the reduction of the acquisition times, that for the commercially available high-resolution cameras would be from tens of seconds to a few minutes, and a speed-up in processing the large amount of data that are acquired, in order to retrieve 3D reconstructions or refocused 2D images. To address these challenges, we are employing high-resolution SPAD (single photon avalanche diode) arrays and high-performance low-level programming of ultra-fast electronics, combined with compressive sensing and quantum tomography algorithms, with the aim of reducing both the acquisition and the elaboration time by one or possibly two orders of magnitude. Moreover, in order to achieve the quantum limit and further increase the volumetric resolution beyond the Rayleigh diffraction limit, we explored dedicated pro- tocols based on quantum Fisher information. Finally, we discuss how this new generation of quantum plenoptic devices could be exploited in different fields of research, such as 3D microscopy and space imaging.
The concepts of quantum detection and estimation theory can be of great help in the analysis of faint signals, which must be treated with extreme care due to the fragility and subtlety. But this is surely not the only domain, where the advanced concepts may be applied. Strong optical fields can be analyzed by similar techniques since by virtue of first quantization any optical wave plays role of a quantum state. More precisely, a classical mode of light can be given and alternative interpretation as a quantum state of the spatial degrees of freedom of a photon. Here the formulation of classical optics meets those of quantum information processing. The goal of the research is to optimize classical sensing schemes of strong signals in order to attain the best performance allowed by Nature. As examples of the approach, measurement of two point-like sources separation and full characterization of laser beams by a phase-space tomography will be discussed both theoretically and experimentally.
Wavefront sensing is an advanced technology that enables the precise determination of the phase of a light field, a
critical information for many applications, such as noncontact metrology, adaptive optics, and vision correction.
Here, we reinterpret the operation of wavefront sensors as a simultaneous unsharp measurement of position
and momentum. Utilizing quantum tomography techniques we report an experimental characterization and 3D
imaging of a multimode laser light.
Adaptive image fusion system based on neural network principle was realized. It works with digitalized video
sequences of visible and infrared band sensors, and is able to produce the optimal fused image for a wide range
of lighting conditions through an adaptive change of a fusion algorithm. The change is driven by a change in
the measured statistic of the input images. The best algorithm for a particular input is found with the help of
an objective measurement of the fusion process quality.
Maximum-likelihood estimation is an important method of inference.
Recently, maximum-likelihood techniques have been successfully
applied to absorption tomography of weakly as well as strongly
absorbing materials. In this presentation we generalize this
method to the phase contrast tomography, which combines the phase
estimation and tomography. Unlike the standard phase fitting
followed by the filtered back-projection, the developed procedure
gives reasonable results also when applied to very noisy data or
data consisting of only a few measured projections. The proposed
method could therefore considerably shorten measuring times in
applications involving low intensity beams, such as phase
tomography with low intense X-ray beams or neutrons.
We study teleportation of qubits with imperfect Bell analysis on the sender's side. For the chosen family of Alice's measurements we find Bob's operations maximizing the overall fidelity of the teleportation protocol. In certain cases the optimum maps turn out to be nonunitary operations. This means that decoherence can sometimes enhance the performance of quantum teleportation protocols.
An experimental comparison of several operational phase concepts is presented. In particular, it is shown that statistically motivated evaluation of experimental data may lead to a significant improvement in phase fitting upon the conventional Noh, Fourgeres and Mandel procedure. The analysis is extended to the asymptotic limit of large intensities, where a strong evidence in favor of multi- dimensional procedures has been found.
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