Structured light beams carrying orbital angular momentum (OAM), such as Laguerre-Gaussian modes, are promising tools for high-capacity optical communications and advanced biomedical imaging. However, multiple scattering in turbid media distorts their phase and amplitude, complicating the retrieval of topological charge. Using experimentally acquired three-channel intensity and interference measurements from 25 independent acquisition sessions, we evaluate signed 11-class and unsigned 6-class topological-charge classification with a matched CNN baseline, an Angular Fourier Transform CNN (AFT-CNN), and a pretrained ResNet18 baseline. The best-performing models achieve high accuracy in the low-scattering regime, with the CNN and ResNet18 remaining near 95% at [Formula: see text] but accuracy drops sharply around [Formula: see text] These results indicate that sign-dependent OAM information can survive multiple scattering in the low-scattering regime and can be decoded from three-channel measurements with deep learning.

Topologically structured light carrying orbital angular momentum (OAM) offers new opportunities for quantitative optical probing of biological tissues, yet its propagation in scattering media remains poorly understood. We report combined experimental and computational studies showing that optical vortex beams maintain their phase topology when transmitted through turbid tissue-like scattering medium and tissue samples. Using a modified Mach-Zehnder interferometer and a Monte Carlo-based photon transport model optimized for phase tracking, we compared conventional Laguerre-Gaussian modes with fractional-OAM beams generated by Conical Refraction. The results demonstrate that fractional vortex beams exhibit superior phase stability and sensitivity to microstructural variations, enabling precise, label-free tissue characterization.

The Stokes-Mueller description of tissue polarimetry is conventionally interpreted through local observables such as birefringence, depolarization, and helicity preservation. We show that tissue structure generates topology in the polarization field itself. Polarization-resolved measurements of unstained human breast tissue reveal polarization vortices and, where the tissue architecture provides coupled azimuthal and radial variation, Neel-type polarization skyrmions. These structures are quantified by the vortex winding number and skyrmion charge, integer-valued topological invariants that vanish for homogeneous media and therefore provide zero background readouts of tissue heterogeneity. Malignant ductal carcinoma exhibits non-trivial polarization topology, whereas adjacent healthy tissue remains topologically trivial. The results establish topological invariants of the polarization field as physically interpretable observables of tissue organization and motivate topological polarimetry as a field-based approach to tissue characterization.

Conventional polarimetry, including schemes leveraging entangled light, characterizes optical samples through linear transformations of polarization states. We introduce a two-photon probing approach in which both photons of an entangled pair interact with the same depolarizing medium simultaneously. In this regime, the transformation of the two-photon polarization correlations becomes quadratic in the Mueller matrix, enabling access to second-order polarization information beyond conventional polarimetry. We develop a theoretical framework linking the Mueller matrix to the evolution of the two-photon polarization correlation tensor and show that depolarization induces quadratic degradation of entanglement and state purity. Experiments using polarization-entangled photon pairs transmitted through controlled scattering media confirm the predicted response and reveal enhanced sensitivity to polarization scrambling compared with single-photon probing. These results establish two-photon probing as a higher-order quantum polarimetric modality for characterizing polarization channels.

Polarimetry with quantum light promises improved measurements for various scenarios. However, fundamental understanding of quantum photonic state transport in complex, real media, and tools to interpret the state after interaction with the sample are still lacking. Here, we theoretically and experimentally explore the evolution of polarization-entangled states in a turbid medium on example of tissue phantoms. By elaborating mathematical relationship between Wolf's coherency matrix and density matrix, we introduce a versatile framework describing the transfer of entangled photons in turbid environments with polarization tracking and resulting quantum state representation with the density operator. Experimentally, we reveal a robust trend in the state evolution depending on the reduced scattering coefficient of the medium. Our theoretical predictions correlate with experimental findings, while the model extends the study by photonic states with different degrees of entanglement. The presented results pave the way for quantitative quantum photonic sensing enabling applications ranging from biomedical diagnostics to remote sensing.

A great research breakthrough that occurred in materials science twenty years ago has brought new metallurgical alloy design principles and made it possible to create a unique kind of artificial materials - multi- element concentrated alloys. These complex solid solutions reveal unique crystalline structures and promising physical and chemical properties. All of these alloys are interesting for their functionality, but they have not yet been introduced into daily life due to their high price and complexity of production. It has recently been proposed that electrical resistance strain gauges and pressure sensors are among the most suitable practical applications in which these materials can be efficiently implemented. The further development of such alloys requires an improved understanding of the physical mechanisms behind high strain gauge sensitivity in these systems. This study focuses on a comprehensive analysis of the effects of pressure and uniaxial stress on electrical resistivity in the equiatomic TiZrHfTa high-entropy alloy, which is a typical representative of this family of materials. We measure electrical, magnetic, and thermal properties of the system and calculate its electronic structure and elastic constants to address issues associated with the strain and pressure effects, as well as evaluate the overall functionality for this kind of alloys in terms of possible passive electronic sensors. The tested alloy exhibits virtually temperature-independent resistivity and a superior strain gauge factor as large as 5.17. By analyzing the obtained data, we suggest that elastic anisotropy effects playa key role in the strain-sensitive behavior of refractory high-entropy alloys.

Structured light beams carrying orbital angular momentum (OAM), such as Laguerre-Gaussian modes, are promising tools for high-capacity optical communications and advanced biomedical imaging. However, multiple scattering in turbid media distorts their phase and amplitude, complicating the retrieval of topological charge. We introduce VortexNet, a deep learning architecture that integrates an Angular Fourier Transform to explicitly extract rotational symmetries of OAM beams from experimentally acquired intensity and interference patterns. By transforming spatial information into the angular frequency domain, VortexNet isolates azimuthal features that persist despite scattering, enabling accurate topological charge classification even in complex optical environments. The results reveal that OAM-specific angular correlations can survive multiple scattering and be decoded through angular-domain learning. This establishes a new paradigm for structured-light analysis in complex medium, where deep learning enables the recovery of topological information beyond the reach of classical optics, paving the way for resilient photonic systems in communication, sensing, and imaging.

This study explores OAM beams for analyte sensing in biological tissues. Demonstrating robust phase memory, our approach enables non-invasive glucose detection in scattering media, offering a highly sensitive optical technique for biomedical diagnostics. (c) 2025 The Authors

To reduce material costs, it is vital to develop reliable theoretical methods for predicting glass formation regions in multicomponent metal systems. We have developed a new model for predicting the compositions of quaternary amorphous metallic glasses and applied it to the Gd-Sc-Co-Al system. The proposed model parameters Theta(1,2)(i-j) (x(i)), Theta(1,2)(i-j)(x(j) ) make it possible to predict the location of glass-forming compositions by finding the minimum of the P-HSS parameter multiplication by the geometric coefficient Gamma(1,2), Gamma(1,2). The alloy with the composition Sc33Gd32Co19Al16 was successfully predicted and cast as a glass rod with a lateral size of 3 mm. According to the results of X-ray diffraction and thermal analysis, the sample Sc33Gd32Co19Al16 is an amorphous material with the lowest crystallinity index (4.3 %). The proposed approach can be used as a predictive model for determining glass-forming compositions in various quaternary metal systems.

A comparative application of major dynamic light scattering (DLS)-based image methodologies applied to transcranial cerebral blood flow imaging is presented. In particular, the study delves into assessing capability of Laser Doppler Flowmetry (LDF), Laser Speckle Contrast Imaging (LSCI), and Diffuse Correlation Spectroscopy (DCS) in enhancing the spatial and temporal resolution of transcranial blood flow imaging. An integral part of the study is focused on the modulation of blood flow through the administration of the vasodilator drug, Sodium Nitroprusside (SNP). This pharmacological intervention facilitated a direct observation of cerebral vasculature's responsiveness to external stimuli, illuminating the physiological adaptations within the brain's microvascular architecture. Advanced LSCI processing techniques are incorporated, notably entropy and principal component analysis (PCA). Entropy is providing a quantifiable measure of the randomness and complexity within the speckle patterns of transcranial blood flow images, revealing remarkably similar outcomes with DSC approach in terms of blood flow dynamics and its quantitative evaluation. The application of PCA approach is provided a more nuanced understanding of blood flow dynamics, facilitating the identification of subtle changes induced by drug administration. This method proved instrumental in enhancing the visualization and detection of nuanced blood flow dynamics, thereby allowing for a more detailed examination of cerebral circulation alterations induced by SNP administration. The study seeks to offer a wider-ranging insight into comprehending the translating further the concept of DLS into transcrainial blood flow vizualization and explore its practical applications, considering hardware, advanced quantitative image processing, and data acquisition. The study presents a comparative analysis of Dynamic Light Scattering (DLS)-based imaging methods for visualizing transcranial blood flow, focusing on techniques like Laser Doppler Flowmetry (LDF), Laser Speckle Contrast Imaging (LSCI), and Diffuse Correlation Spectroscopy (DCS). The study evaluates these methodologies' effectiveness in improving spatial and temporal resolution, offering insights into cerebral hemodynamics, particularly under pharmacological modulation with Sodium Nitroprusside. The research highlights advancements in quantitative image processing, such as entropy and principal component analysis (PCA), enhancing the detection of blood flow dynamics. image

Scandium is commonly known as a superior modifier for most alloys and compounds, substantially improving their phase stability and physical properties, as well as glass-forming ability. A special case is rare-earth based magnetic metallic glasses, which are an unique platform for intra-elemental substitution due to the chemical affinity of the lanthanides, yttrium and scandium. The latter, used as an alloying additive and being the smallest atom among the entire family, can drastically affect structure formation and magnetism in these metallic glasses. The main issue is that its modifying role is not well understood due to scarce information on the scandium effects in such rare-earth systems. This study is focused on thermal and magnetic analysis of some popular Gd-based BMGs redesigned with minor Sc additives. Here, we consider temperature behavior of specific heat capacity and entropy functions for both amorphous and crystalline phases to estimate the scandium effect on GFA and thermal stability of the glasses. As well, we inspect magnetic and magnetocaloric properties of these BMGs to understand whether this very expensive metal can radically improve the alloy magnetism and make these materials suitable for potential applications.

We utilize Laser Speckle Contrast Imaging (LSCI) for visualizing cerebral blood flow in mice during and post-cardiac arrest. Analyzing LSCI images, we noted temporal blood flow variations across the brain surface for hours postmortem. Fast Fourier Transform (FFT) analysis depicted blood flow and microcirculation decay post-death. Continuous Wavelet Transform (CWT) identified potential cerebral hemodynamic synchronization patterns. Additionally, non-negative matrix factorization (NMF) with four components segmented LSCI images, revealing structural subcomponent alterations over time. This integrated approach of LSCI, FFT, CWT, and NMF offers a comprehensive tool for studying cerebral blood flow dynamics, metaphorically capturing the 'end of the tunnel' experience. Results showed primary postmortem hemodynamic activity in the olfactory bulbs, followed by blood microflow relocations between somatosensory and visual cortical regions via the superior sagittal sinus. This method opens new avenues for exploring these phenomena, potentially linking neuroscientific insights with mysteries surrounding consciousness and perception at life's end.

Recent advancements in wavefront shaping techniques have facilitated the study of complex structured light's propagation with orbital angular momentum (OAM) within various media. The introduction of a spiral phase modulation to the Laguerre-Gaussian (LG) beam during its paraxial propagation is facilitated by the negative gradient of the medium's refractive index's temporal change, resulting in an accelerated retardation in OAM twist. This approach attains remarkable sensitivity to even the slightest variations in the medium's refractive index (10^(-6)). The phase memory of OAM is revealed as the ability of twisted light preserving initial helical phase even propagating through the turbid tissue-like multiple scattering medium. The results confirm fascinating opportunities of the exploiting OAM light in biomedical applications, e.g. such as non-invasive trans-cutaneous glucose diagnosis and optical communication through biological tissues and other optically dense media.

A multimode optical fiber supports excitation and propagation of a pure single optical mode, i.e., the field pattern that satisfies the boundary conditions and does not change along the fiber. When two counterpropagating pure optical modes are excited, they could interact through the stimulated Brillouin scattering (SBS) process. Here, we present a simple theoretical formalism describing SBS interaction between two individual optical modes selectively excited in an acoustically isotropic multimode optical fiber. Employing a weakly guiding step-index fiber approach, we have built an analytical expression for the spatial distribution of the sound field amplitude in the fiber core and explored the features of SBS gain spectra, describing the interaction between modes of different orders. In this way, we give a clear insight into the sound propagation effects accompanying SBS in multimode optical fibers, and demonstrate their specific contributions to the SBS gain spectrum.