Optical Speckle Patterns Research Articles

Probing the enpolarization phenomenon in a speckle pattern using a microwave photonics-inspired approach.

We report how Stokes polarimetry of a highly resolved optical speckle pattern coupled to an original microwave photonics-inspired experimental approach allows new light to be shaded on the so-called enpolarization phenomenon, which consists in the local increase of the light degree of polarization (DOP) inducing a high average DOP value after interaction of unpolarized light with a totally depolarizing sample.

Characterizing localization effects in an ultracold disordered Fermi gas by diffusion analysis

Disorder can fundamentally modify the transport properties of a system. A striking example is Anderson localization, suppressing transport due to destructive interference of propagation paths. In inhomogeneous many-body systems, not all particles are localized for finite-strength disorder, and the system can become partially diffusive. Unraveling the intricate signatures of localization from such observed diffusion is a longstanding problem. Here, we experimentally study a degenerate, spin-polarized Fermi gas in a disorder potential formed by an optical speckle pattern. We record the diffusion through the disordered potential upon release from an external confining potential. We compare different methods to analyze the resulting density distributions, including a new approach to capture particle dynamics by evaluating absorption-image statistics. Using standard observables, such as diffusion exponent and coefficient, localized fraction, or localization length, we find that some show signatures for a transition to localization above a critical disorder strength, while others show a smooth crossover to a modified diffusion regime. In laterally displaced disorder, we spatially resolve different transport regimes simultaneously, which allows us to extract the subdiffusion exponent expected for weak localization. Our work emphasizes that the transition toward localization can be investigated by closely analyzing the system's diffusion, offering ways of revealing localization effects beyond the signature of exponentially decaying density distribution. Published by the American Physical Society 2024

Learning-based super-resolution interpolation for sub-Nyquist sampled laser speckles

Information retrieval from visually random optical speckle patterns is desired in many scenarios yet considered challenging. It requires accurate understanding or mapping of the multiple scattering process, or reliable capability to reverse or compensate for the scattering-induced phase distortions. In whatever situation, effective resolving and digitization of speckle patterns are necessary. Nevertheless, on some occasions, to increase the acquisition speed and/or signal-to-noise ratio (SNR), speckles captured by cameras are inevitably sampled in the sub-Nyquist domain via pixel binning (one camera pixel contains multiple speckle grains) due to finite size or limited bandwidth of photosensors. Such a down-sampling process is irreversible; it undermines the fine structures of speckle grains and hence the encoded information, preventing successful information extraction. To retrace the lost information, super-resolution interpolation for such sub-Nyquist sampled speckles is needed. In this work, a deep neural network, namely SpkSRNet, is proposed to effectively up sample speckles that are sampled below 1/10 of the Nyquist criterion to well-resolved ones that not only resemble the comprehensive morphology of original speckles (decompose multiple speckle grains from one camera pixel) but also recover the lost complex information (human face in this study) with high fidelity under normal- and low-light conditions, which is impossible with classic interpolation methods. These successful speckle super-resolution interpolation demonstrations are essentially enabled by the strong implicit correlation among speckle grains, which is non-quantifiable but could be discovered by the well-trained network. With further engineering, the proposed learning platform may benefit many scenarios that are physically inaccessible, enabling fast acquisition of speckles with sufficient SNR and opening up new avenues for seeing big and seeing clearly simultaneously in complex scenarios.

Oscillating optical fiber speckle patterns: modeling and application

Speckle patterns produced by the interference between multiple optical fiber modes carry detailed information regarding the waveguide characteristics. However, reflection-type setups implemented with fiber coupler and mirror generate oscillating specklegrams that cycle consistently around well-defined states. To study such a peculiar phenomenon, an analytical model derived from a multimode fiber Fabry-Pérot interferometer investigates the contributions of the cavity length, refractive index, and laser wavelength, revealing a sinusoidal modulation of the correlation coefficient. Experiments confirm the effect of the fiber-mirror distance on the specklegram changes: computing the correlation and tracing the spatiotemporal evolution of a light granule through active contour models yielded a phase sensitivity of 15.71 rad/µm. Furthermore, the presented system works as a precise displacement sensor enhanced by the extended correlation algorithm, achieving 3 nm resolution with linear response over a 70 µm range.

High optical contrast nanoimprinted speckle patterns for digital image correlation analysis

For the characterization of the mechanical deformation of materials at microscopic length scales, image processing of a high-quality surface pattern was used. We imprinted speckle patterns onto a thin polymer film attached to the surface of flat and curved metal substrates using flexible molds and soft-thermal nanoimprint lithography. High optical contrast was achieved by mixing black dye into the film generating high absorption in the elevated structures, and by adding titania nanoparticles as fillers to the recessed areas to induce diffuse scattering. For accessing resolution suitable to detect deformation at an individual grain level, the structure sizes were scaled down from 20 μm to 2 μm. For both structure sizes imaging was tested using a digital image correlation setup, that enables 3D imaging of samples with angles of up to 10° of inclination. • Imprint of speckle patterns from computer-generated image templates on curved metal surfaces • Generation of high visual contrast by using a polymer film with high absorption (black) and high diffuse reflection (white) • Quantitative analysis of contrast for two different sizes of speckle patterns to evaluate their feasibility for DIC

Non-invasive blood glucose sensing by machine learning of optic fiber-based speckle pattern variation.

.SignificanceThe ability to perform frequent non-invasive monitoring of glucose in the bloodstream is very applicable for diabetic patients.AimWe experimentally verified a non-invasive multimode fiber-based technique for sensing glucose concentration in the bloodstream by extracting and analyzing the collected speckle patterns.ApproachThe proposed sensor consists of a laser source, digital camera, computer, multimode fiber, and alternating current (AC) generated magnetic field source. The experiments were performed using a covered (with cladding and jacket) and uncovered (without cladding and jacket) multimode fiber touching the skin under a magnetic field and without it. The subject’s finger was placed on a fiber to detect the glucose concentration. The method tracks variations in the speckle patterns due to light interaction with the bloodstream affected by blood glucose.ResultsThe uncovered fiber placed above the finger under the AC magnetic field (150 G) at 140 Hz was found to have a lock-in amplification role, improving the glucose detection precision. The application of the machine learning algorithms in preprocessed speckle pattern data increase glucose measurement accuracy. Classification of the speckle patterns for uncovered fiber under the AC magnetic field allowed for detection of the blood glucose with high accuracy for all tested subjects compared with other tested configurations.ConclusionsThe proposed technique was theoretically analyzed and experimentally validated in this work. The results were verified by the traditional finger-prick method, which was also used for classification as a conventional reference marker of blood glucose levels. The main goal of the proposed technique was to develop a non-invasive, low-cost blood glucose sensor for easy use by humans.

Learning to transmit images through optical speckle of a multimode fiber with high fidelity

Multimode fibers provide a unique opportunity for exploring the spatial degrees of freedom for high throughput light transmission. However, the modal dispersion prevents from the straightforward application of multimode fibers for space division multiplexing, such as image transmission. Herein, we propose and experimentally demonstrate a deep neural network termed multimode fiber inverse-scattering net for overcoming the modal dispersion induced scrambling in multimode fibers. Such a network is capable of transmitting grayscale image through the multimode fiber with high fidelity. 256-level grayscale images with 128 × 128 spatial channels encoded in the input wavefront can be retrieved from the output optical speckle patterns, where the average Pearson correlation coefficient and structural similarity index are as large as 0.97 and 0.95, respectively. Our results demonstrate that the proposed deep neural network has an excellent ability for learning the relationship between the input and output optical fields of a multimode fiber, which might facilitate the realization of high throughput space division multiplexing through multimode fibers.

AI-assisted spectrometer based on multi-mode optical fiber speckle patterns

Speckle patterns at the output end of a multi-mode fiber (MMF) are generated by the interference of eigenmodes propagating along the fiber. A MMF can support thousands of eigenmodes, and the amplitude and phase of each eigenmode changes rapidly with the properties of input light, thus changing the speckle that emerges at the output. Therefore, a MMF can provide ultra-high sensitivity to the changes of the properties of the input light. However, environmental fluctuations of parameters such as temperature, humidity, and vibration limit the applicability of MMF sensors. In this paper, we theoretically and experimentally demonstrate an AI-assisted MMF spectrometer, and examine the limits of the method. The resolution of the spectrometer reached 0.1 picometer (pm, the resolution of the laser source) for linearly polarized monochromatic incidence. The integration of a deep learning algorithm effectively eliminated the perturbation from environmental fluctuations and made the spectrometer ultra-robust. At the end, we have also demonstrated that by using parallel network configuration, the bandwidth of the system can be easily increased without sacrificing the resolution of the system. The AI-assisted fiber spectrometer is compact, super-robust, and low-cost and provides ultrahigh resolution.

A multimodal optical approach for investigating 3D-printed carbon PEEK composites

In the industrial field, it is of great interest to identify fast and low-cost manufacturing procedures to guarantee reliable and functional products. In this frame, 3D printing is a fast and low-cost innovative technique and its capability to produce fibre-reinforced polymer matrix composites widely opens the application possibilities. 3D printing technology can form also composite materials made by short fibres that can be exploited for manufacturing parts and structures in high-tech sectors such as aerospace, automotive or naval, to cite some. Here we show how a multimodal approach can furnish a whole characterisation of reinforced composites produced with a 3D printing technology during and after tensile and flexural tests. In the multimodal strategy, we employed a couple of full-field and non-contact optical techniques, i.e. 2D-Digital-Image-Correlation (2D-DIC) and Electronic Speckle Pattern Interferometry (ESPI) in combination with SEM and optical microscope for analysing the sample at the micro and macroscale. The result of the work allows us to achieve a complete characterisation of the components realized by 3D printing.

Remote recovery of audio signals from videos of optical speckle patterns: a comparative study of signal recovery algorithms.

Optical remote sensors are nowadays ubiquitously used, thanks to unprecedented advances in the last decade in photonics, machine learning and signal processing tools. In this work we study experimentally the remote recovery of audio signals from the silent videos of the movement of optical speckle patterns. This technique can be used even when in between the source and the receiver there is a medium that does not allow for the propagation of sound waves. We use a diode laser to generate a speckle pattern on the membrane of a loudspeaker and a low-cost CCD camera to record the video of the movement of the speckle pattern when the loudspeaker plays an audio signal. We perform a comparative analysis of six signal recovery algorithms. In spite of having different complexity and computational requirements, we find that the algorithms have (except for the simplest one) good performance in terms of the quality of the recovered signal. The best trade-off, in terms of computational costs and performance, is obtained with a new method that we propose, which recovers the signal from the weighted sum of the intensities of all the pixels, where the signs of the weights are determined by selecting a reference pixel and calculating the signs of the cross-correlations of the intensity of the reference pixel and the intensities of the other pixels.

Opto-thermoelectric speckle tweezers.

Opto-thermoelectric tweezers present a new paradigm for optical trapping and manipulation of particles using low-power and simple optics. New real-life applications of opto-thermoelectric tweezers in areas such as biophysics, microfluidics, and nanomanufacturing will require them to have large-scale and high-throughput manipulation capabilities in complex environments. Here, we present opto-thermoelectric speckle tweezers, which use speckle field consisting of many randomly distributed thermal hotspots that arise from an optical speckle pattern to trap multiple particles over large areas. By further integrating the speckle tweezers with a microfluidic system, we experimentally demonstrate their application for size-based nanoparticle filtration. With their low-power operation, simplicity, and versatility, opto-thermoelectric speckle tweezers will broaden the applications of optical manipulation techniques.

Interferometry-free noncontact photoacoustic detection method based on speckle correlation change.

Optical speckle patterns occur when a coherent optical wavefront is randomized but such stochastic yet deterministic information about the medium can be decoded. A simple setup is inspired to monitor the decorrelation of speckle patterns within the memory effect range when the medium is photoacoustically perturbated. Experimentally, a linear relationship is confirmed between the speckle correlation change and the peak-to-peak amplitude of the ultrasonic transducer-detected photoacoustic waves, and the detection sensitivity is comparable. Such a plain specklegram-based method may find special interests when no direct contact is allowed between the sample and the photoacoustic detector.

Coherent diffusion of partial spatial coherence

Partially coherent fields are abundant in many physical systems. While the propagation of partially coherent light undergoing diffraction is well understood, its evolution in the presence of coherent diffusion (i.e., diffusion of complex fields) remains largely unknown. Here we develop an analytic model describing the diffusion of partially coherent beams and study it experimentally. Our model is based on a diffusion analog of the famous Van Cittert–Zernike theorem. Experimentally, we use a four-wave mixing scheme with electromagnetically induced transparency to couple optical speckle patterns to diffusing atoms in a warm vapor. The spatial coherence properties of the speckle fields are monitored under diffusion and are compared to our model and to the familiar evolution of spatial coherence of light speckles under diffraction. We identify several important differences between the evolution dynamics of the spatial coherence under diffraction and diffusion. Our findings shed light on the propagation of partially coherent fields in media where multiple scattering or thermal motion lead to coherent diffusion.

A Low-Cost Portable Nanophotonic Sensor Based on a Smartphone: A System Readily Available for Many Applications

We present the development of a new low-cost and portable nanophotonic sensor to measure mechanical or environmental quantities, such as acoustic, bending, stretching, or temperature changes (see Figure 1). The sensor consists of a compact diode laser, a multimode fiber, and a smartphone, and thus, it is quite portable. The laser light emitted from the multimode fiber forms optical speckle patterns on a screen. We experimentally implement the bending sensing on a smartphone. The relationship between the bending curvature and the optical speckle pattern is quantitatively studied, demonstrating its feasibility of bending sensing.

Landau instability and mobility edges of the interacting one-dimensional Bose gas in weak random potentials

We study the frictional force exerted on the trapped, interacting 1D Bose gas under the influence of a moving random potential. Specifically we consider weak potentials generated by optical speckle patterns with finite correlation length. We show that repulsive interactions between bosons lead to a superfluid response and suppression of frictional force, which can inhibit the onset of Anderson localisation. We perform a quantitative analysis of the Landau instability based on the dynamic structure factor of the integrable Lieb–Liniger model and demonstrate the existence of effective mobility edges.

Matter wave speckle observed in an out-of-equilibrium quantum fluid

We report the results of the direct comparison of a freely expanding turbulent Bose-Einstein condensate and a propagating optical speckle pattern. We found remarkably similar statistical properties underlying the spatial propagation of both phenomena. The calculated second-order correlation together with the typical correlation length of each system is used to compare and substantiate our observations. We believe that the close analogy existing between an expanding turbulent quantum gas and a traveling optical speckle might burgeon into an exciting research field investigating disordered quantum matter.

Super-resolution photoacoustic microscopy using blind structured illumination

We present a method for enhancing the spatial resolution of optical-absorption-based photoacoustic imaging through or within highly scattering media. The optical speckle pattern that emerges as light propagates through diffuse media provides structured illumination to an object placed behind a scattering wall. The photoacoustic signal produced by such illumination is detected using a focused ultrasound transducer. We demonstrate through both simulation and experiment that, by acquiring multiple photoacoustic images, each produced by a different random and unknown speckle pattern, an image of an absorbing object can be reconstructed with a spatial resolution far exceeding that of the ultrasound transducer. The imaging approach and reconstruction method exploiting joint sparsity will be valuable for biomedical applications and other fields where high-frequency structural information is scrambled by diffusive processes.

Ferromagnetism in a repulsive atomic Fermi gas with correlated disorder

We investigate the zero-temperature ferromagnetic behavior of a two-component repulsive Fermi gas in the presence of a correlated random field that represents an optical speckle pattern. The density is tuned so that the (noninteracting) Fermi energy is close to the mobility edge of the Anderson localization transition. We employ quantum Monte Carlo simulations to determine various ground-state properties, including the equation of state, the magnetic susceptibility, and the energy of an impurity immersed in a polarized Fermi gas (repulsive polaron). In the weakly interacting limit, the magnetic susceptibility is found to be suppressed by disorder. However, it rapidly increases with the interaction strength, and it diverges at a much weaker interaction strength compared to the clean gas. Both the transition from the paramagnetic phase to the partially ferromagnetic phase, and the one from the partially to the fully ferromagnetic phase are strongly favored by disorder, indicating a case of order induced by disorder.

Development of a heterodyne speckle imager to measure 3 degrees of vibrational freedom.

A laboratory system has demonstrated the measurement of three degrees of vibrational freedom simultaneously through heterodyne speckle imaging. The random interference pattern generated by the illumination of a rough surface with coherent light can be exploited to extract information about the surface motion. The optical speckle pattern is heterodyne mixed with a coherent reference. The recorded optical data is then processed to extract three dimensions of surface motion. Axial velocity is measured by demodulating the received time-varying intensity of high amplitude pixels. Tilt, a gradient of surface displacement, is calculated by measuring speckle translation following extraction of the speckle pattern from the mixed signal. This paper discusses the laboratory sensor concept, signal processing, and experimental results compared with numeric simulations.

Near-field to far-field characterization of speckle patterns generated by disordered nanomaterials.

We study the intensity spatial correlation function of optical speckle patterns above a disordered dielectric medium in the multiple scattering regime. The intensity distributions are recorded by scanning near-field optical microscopy (SNOM) with sub-wavelength spatial resolution at variable distances from the surface in a range which spans continuously from the near-field (distance ≪ λ) to the far-field regime (distance ≫ λ). The non-universal behavior at sub-wavelength distances reveals the connection between the near-field speckle pattern and the internal structure of the medium.