Taxonomy of hybridly polarized Stokes vortex beams.

Structured beams carrying topological defects, namely phase and Stokes singularities, have gained extensive interest in numerous areas of optics. The non-separable spin and orbital angular momentum states of hybridly polarized Stokes singular beams provide additional freedom for manipulating optical fields. However, the characterization of hybridly polarized Stokes vortex beams remains challenging owing to the degeneracy associated with the complex polarization structures of these beams. In addition, experimental noise factors such as relative phase, amplitude, and polarization difference together with beam fluctuations add to the perplexity in the identification process. Here, we present a generalized diffraction-based Stokes polarimetry approach assisted with deep learning for efficient identification of Stokes singular beams. A total of 15 classes of beams are considered based on the type of Stokes singularity and their associated mode indices. The resultant total and polarization component intensities of Stokes singular beams after diffraction through a triangular aperture are exploited by the deep neural network to recognize these beams. Our approach presents a classification accuracy of 98.67% for 15 types of Stokes singular beams that comprise several degenerate cases. The present study illustrates the potential of diffraction of the Stokes singular beam with polarization transformation, modeling of experimental noise factors, and a deep learning framework for characterizing hybridly polarized beams.

Multimodal on-chip nanoscopy and quantitative phase imaging reveals the nanoscale morphology of liver sinusoidal endothelial cells.

Visualization of three-dimensional (3D) morphological changes in the subcellular structures of a biological specimen is a major challenge in life science. Here, we present an integrated chip-based optical nanoscopy combined with quantitative phase microscopy (QPM) to obtain 3D morphology of liver sinusoidal endothelial cells (LSEC). LSEC have unique morphology with small nanopores (50-300 nm in diameter) in the plasma membrane, called fenestrations. The fenestrations are grouped in discrete clusters, which are around 100 to 200 nm thick. Thus, imaging and quantification of fenestrations and sieve plate thickness require resolution and sensitivity of sub-100 nm along both the lateral and the axial directions, respectively. In chip-based nanoscopy, the optical waveguides are used both for hosting and illuminating the sample. The fluorescence signal is captured by an upright microscope, which is converted into a Linnik-type interferometer to sequentially acquire both superresolved images and phase information of the sample. The multimodal microscope provided an estimate of the fenestration diameter of 119 ± 53 nm and average thickness of the sieve plates of 136.6 ± 42.4 nm, assuming the constant refractive index of cell membrane to be 1.38. Further, LSEC were treated with cytochalasin B to demonstrate the possibility of precise detection in the cell height. The mean phase value of the fenestrated area in normal and treated cells was found to be 161 ± 50 mrad and 109 ± 49 mrad, respectively. The proposed multimodal technique offers nanoscale visualization of both the lateral size and the thickness map, which would be of broader interest in the fields of cell biology and bioimaging.

High space-bandwidth in quantitative phase imaging using partially spatially coherent digital holographic microscopy and a deep neural network.

Quantitative phase microscopy (QPM) is a label-free technique that enables monitoring of morphological changes at the subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence properties of the light source and the numerical aperture (NA) of objective lenses. Here, we propose high space-bandwidth quantitative phase imaging using partially spatially coherent digital holographic microscopy (PSC-DHM) assisted with a deep neural network. The PSC source synthesized to improve the spatial sensitivity of the reconstructed phase map from the interferometric images. Further, compatible generative adversarial network (GAN) is used and trained with paired low-resolution (LR) and high-resolution (HR) datasets acquired from the PSC-DHM system. The training of the network is performed on two different types of samples, i.e. mostly homogenous human red blood cells (RBC), and on highly heterogeneous macrophages. The performance is evaluated by predicting the HR images from the datasets captured with a low NA lens and compared with the actual HR phase images. An improvement of 9× in the space-bandwidth product is demonstrated for both RBC and macrophages datasets. We believe that the PSC-DHM + GAN approach would be applicable in single-shot label free tissue imaging, disease classification and other high-resolution tomography applications by utilizing the longitudinal spatial coherence properties of the light source.

Deep learning architecture "LightOCT" for diagnostic decision support using optical coherence tomography images of biological samples.

Optical coherence tomography (OCT) is being increasingly adopted as a label-free and non-invasive technique for biomedical applications such as cancer and ocular disease diagnosis. Diagnostic information for these tissues is manifest in textural and geometric features of the OCT images, which are used by human expertise to interpret and triage. However, it suffers delays due to the long process of the conventional diagnostic procedure and shortage of human expertise. Here, a custom deep learning architecture, LightOCT, is proposed for the classification of OCT images into diagnostically relevant classes. LightOCT is a convolutional neural network with only two convolutional layers and a fully connected layer, but it is shown to provide excellent training and test results for diverse OCT image datasets. We show that LightOCT provides 98.9% accuracy in classifying 44 normal and 44 malignant (invasive ductal carcinoma) breast tissue volumetric OCT images. Also, >96% accuracy in classifying public datasets of ocular OCT images as normal, age-related macular degeneration and diabetic macular edema. Additionally, we show ∼96% test accuracy for classifying retinal images as belonging to choroidal neovascularization, diabetic macular edema, drusen, and normal samples on a large public dataset of more than 100,000 images. The performance of the architecture is compared with transfer learning based deep neural networks. Through this, we show that LightOCT can provide significant diagnostic support for a variety of OCT images with sufficient training and minimal hyper-parameter tuning. The trained LightOCT networks for the three-classification problem will be released online to support transfer learning on other datasets.

High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition.

Sperm cell motility and morphology observed under the bright field microscopy are the only criteria for selecting a particular sperm cell during Intracytoplasmic Sperm Injection (ICSI) procedure of Assisted Reproductive Technology (ART). Several factors such as oxidative stress, cryopreservation, heat, smoking and alcohol consumption, are negatively associated with the quality of sperm cell and fertilization potential due to the changing of subcellular structures and functions which are overlooked. However, bright field imaging contrast is insufficient to distinguish tiniest morphological cell features that might influence the fertilizing ability of sperm cell. We developed a partially spatially coherent digital holographic microscope (PSC-DHM) for quantitative phase imaging (QPI) in order to distinguish normal sperm cells from sperm cells under different stress conditions such as cryopreservation, exposure to hydrogen peroxide and ethanol. Phase maps of total 10,163 sperm cells (2,400 control cells, 2,750 spermatozoa after cryopreservation, 2,515 and 2,498 cells under hydrogen peroxide and ethanol respectively) are reconstructed using the data acquired from the PSC-DHM system. Total of seven feedforward deep neural networks (DNN) are employed for the classification of the phase maps for normal and stress affected sperm cells. When validated against the test dataset, the DNN provided an average sensitivity, specificity and accuracy of 85.5%, 94.7% and 85.6%, respectively. The current QPI + DNN framework is applicable for further improving ICSI procedure and the diagnostic efficiency for the classification of semen quality in regard to their fertilization potential and other biomedical applications in general.

Edge enhancement by negative Poincare-Hopf index filters.

Phase and polarization are interrelated quantities, and hence polarization elements that perform like phase elements can be designed. In this Letter, we show that a polarizing element producing a negative Poincare-Hopf (PH) index beam can be used as a spatial filter to perform edge enhancement. Either isotropic or anisotropic edge enhancement can be achieved by polarization selection of the light that illuminates the sample. A conventional microscope imaging system is modified into a polarization-selective optical Fourier processor. Experimental results are presented to show that negative PH index filters, producing a set of orthogonal polarization distribution and their superpositions, can also be used for edge enhancement in optical signal processing.

Probing the degenerate states of V-point singularities.

V-points are polarization singularities in spatially varying linearly polarized optical fields and are characterized by the Poincare-Hopf index η. Each V-point singularity is a superposition of two oppositely signed orbital angular momentum states in two orthogonal spin angular momentum states. Hence, a V-point singularity has zero net angular momentum. V-points with given |η| have the same (amplitude) intensity distribution but have four degenerate polarization distributions. Each of these four degenerate states also produce identical diffraction patterns. Hence to distinguish these degenerate states experimentally, we present in this Letter a method involving a combination of polarization transformation and diffraction. This method also shows the possibility of using polarization singularities in place of phase singularities in optical communication and quantum information processing.

Polarization-based spatial filtering for directional and nondirectional edge enhancement using an S-waveplate.

Using polarization as an additional parameter apart from amplitude and phase in spatial filtering experiments offers additional advantages and possibilities. An S-waveplate that can convert a linearly polarized light into radially or azimuthally polarized light can also be used for isotropic edge enhancement. For anisotropic edge enhancement, introduction of a polarizer at the output was recommended and edge selection was done by orientation of the polarizer. But the full potential of the S-waveplate as a spatial filter has not been exploited so far. Unlike the standard amplitude and phase-based Fourier filters, which are independent to the state of polarization of the illuminating beam, the S-waveplate acts in a different way depending on the state of polarization. The edge selection does not need to be carried out by changing the orientation of the polarizer. With a fixed polarizer at the output, we show that either isotropic or anisotropic edge enhancement in any desired orientation can be performed by operating the same spatial filter setup in different illuminating polarization states.

Young's experiment with waves near zeros.

We report an interesting observation in the formation of Young's fringes from a two pinhole arrangement illuminated by waves from the neighborhood of a zero of an optical phase singularity. Spacing of the Young's fringes appears to defy the dependence of pin-hole separation. But for larger pinhole separation such an anomalous phenomenon is not discernible. The experiments show that the fringe spacing is governed by the stronger local phase gradient near the vortex core that also has a radial part. Many diffraction experiments reported so far have missed this aspect as the phase gradient in a vortex beam is normally considered to have only azimuthal and longitudinal components. This work reveals the vortex core structure and is the first experimental evidence to the existence of a radial component of this phase gradient.

Analysis of Fibonacci gratings and their diffraction patterns.

Aperiodic and fractal optical elements are proving to be promising candidates in image-forming devices. In this paper, we analyze the diffraction patterns of Fibonacci gratings (FbGs), which are prototypical examples of aperiodicity. They exhibit novel characteristics such as redundancy and robustness that keep their imaging characteristics intact even when there is significant loss of information. FbGs also contain fractal signatures and are characterized by a fractal dimension. Our study suggests that aperiodic gratings may be better than their fractal counterparts in technologies based on such architectures. We also identify the demarcating features of aperiodic and fractal diffraction, which have been rather fuzzy in the literature so far.

Fractal signatures in the aperiodic Fibonacci grating.

The Fibonacci grating (FbG) is an archetypal example of aperiodicity and self-similarity. While aperiodicity distinguishes it from a fractal, self-similarity identifies it with a fractal. Our paper investigates the outcome of these complementary features on the FbG diffraction profile (FbGDP). We find that the FbGDP has unique characteristics (e.g., no reduction in intensity with increasing generations), in addition to fractal signatures (e.g., a non-integer fractal dimension). These make the Fibonacci architecture potentially useful in image forming devices and other emerging technologies.

Conical light sword optical beam and its healing property.

A new diffractive optical element, named as a conical light sword optical element, is presented. In the focal volume, this element produces a helical amplitude profile that can be used as an optical twister. We have experimentally demonstrated the optical healing property of the conical light sword optical beam (CLSOB). This healing property comes from the transverse helical energy flow, due to the evolution of multiple unipolar vortices in the propagation of CLSOB. We envisage that this spiral intensity profile and optical healing property of the beam find potential applications in propagation through a scattering and turbulent media, imaging with extended depth of field, and in optical tweezers.

Robustness of Cantor diffractals.

Diffractals are electromagnetic waves diffracted by a fractal aperture. In an earlier paper, we reported an important property of Cantor diffractals, that of redundancy [R. Verma et. al., Opt. Express 20, 8250 (2012)]. In this paper, we report another important property, that of robustness. The question we address is: How much disorder in the Cantor grating can be accommodated by diffractals to continue to yield faithfully its fractal dimension and generator? This answer is of consequence in a number of physical problems involving fractal architecture.

Redundancy in Cantor diffractals.

Cantor diffractals are waves that have encountered a Cantor grating. In this paper, we report an important property of Cantor diffractals, namely that of redundancy. We observe that the Fraunhofer diffraction pattern comprises of several bands, each containing complete information about the fractal aperture. This redundancy allows for a faithful reconstruction of the Cantor grating by an inverse Fourier transformation of an arbitrary band.

Tailored complex 3D vortex lattice structures by perturbed multiples of three-plane waves.

As three-plane waves are the minimum number required for the formation of vortex-embedded lattice structures by plane wave interference, we present our experimental investigation on the formation of complex 3D photonic vortex lattice structures by a designed superposition of multiples of phase-engineered three-plane waves. The unfolding of the generated complex photonic lattice structures with higher order helical phase is realized by perturbing the superposition of a relatively phase-encoded, axially equidistant multiple of three noncoplanar plane waves. Through a programmable spatial light modulator assisted single step fabrication approach, the unfolded 3D vortex lattice structures are experimentally realized, well matched to our computer simulations. The formation of higher order intertwined helices embedded in these 3D spiraling vortex lattice structures by the superposition of the multiples of phase-engineered three-plane waves interference is also studied.

Sculptured 3D twister superlattices embedded with tunable vortex spirals.

We present diverse reconfigurable complex 3D twister vortex superlattice structures in a large area embedded with tunable vortex spirals as well as dark rings, threaded by vortex helices. We demonstrate these tunable complex chiral vortex superlattices by the superposition of relatively phase engineered plane waves. The generated complex 3D twister lattice vortex structures are computationally as well as experimentally analyzed using various tools to verify the presence of phase singularities. Our observation indicates the application-specific flexibility of our approach to tailor the transverse superlattice spatial irradiance profile of these longitudinally whirling vortex-cluster units and dark rings.

Selective edge enhancement using anisotropic vortex filter.

In optical image processing, selective edge enhancement is important when it is preferable to emphasize some edges of an object more than others. We propose a new method for selective edge enhancement of amplitude objects using the anisotropic vortex phase mask by introducing anisotropy in a conventional vortex mask with the help of the sine function. The anisotropy is capable of edge enhancement in the selective region and in the required direction by changing the power and offset angle, respectively, of the sine function.

Optical phase singularities in detection of laser beam collimation.

Optical phase singularities, also called optical vortices, are known to have applications in various branches of optics. Here the role played by optical vortices in collimation testing is explained. Interference and a diffractive experimental setup in which the presence of an optical vortex permits collimation testing are presented. It is shown that the moire fringes that aid in collimation detection are due solely to the presence of vortices and not to the accompanying phase factors that are involved in producing a grating structure.