Explore the vast range of titles available.

We consider aspects that can significantly increase the computational efficiency of solving multisource 3-D problems of airborne electromagnetic prospecting in complex geological media. An approach to fully automatic construction of non-conforming hexahedral finite element (FE) meshes for calculating electromagnetic fields is proposed. To increase the computational efficiency, a grouping of the airborne electromagnetic (AEM) system positions is used. We present the results of computational experiments for a realistic complex geoelectric model with topography, curved layers, 3-D objects of complex shape, and a fragment of a real observation system containing several thousand positions of the AEM system. Using the results of computational experiments, we have drawn conclusions about the optimal size of groups of AEM system positions using sequential and parallel environments on both one PC and six PCs connected by a local network. We also compare the computational cost of the proposed approach with those presented by other authors who use different principles for constructing meshes, as well as other discretizations in space and time. Computational experiments have shown that the proposed approach makes it possible to model electromagnetic fields in much more complex media and, at the same time, regarding the computational efficiency, our approach is superior to the approaches presented by other authors for solving the multisource airborne electromagnetic survey problems.

The main obstacle for optical imaging or for sending information through turbid media such as paint, clouds and biological tissue is the random scattering of light. Owing to its immense complexity, the process of multiple scattering has long been described by the diffusion equation, which ignores the interference of scattered light. Recent developments in optical wavefront shaping and phase recording techniques have enabled the breaking of the diffusion limit and the control of coherent light transport in complex media, including strongly scattering tissues and multimode optical fibres with random mode mixing. Great advances have been made in focusing and controlling the transmission of light through such complex systems and in performing various tasks behind them, such as optical micro-manipulation. Here, we summarize the amazing power and the fundamental limits of controlling multiple light scattering, which lay the physical foundation to harness multiply-scattered light for imaging and communication purposes. Connections to practical applications are illustrated, in particular in those areas covered in the companion articles in this issue. Multiple scattering fundamentally complicates the task of sending light through turbid media, as many applications require. This Review summarizes the theoretical framework and experimental techniques to understand and control these processes.

Optical aberrations place fundamental limits on the achievable resolution with focusing and imaging. In the context of structured light, optical imperfections and misalignments and perturbing media such as turbulent air, underwater and optical fibre distort the amplitude and phase of the light’s spatial pattern. Here we show that polarization inhomogeneity that defines vectorial structured light is immune to all such perturbations, provided they are unitary. As an example, we study the robustness of vector vortex beams propagating through highly aberrated systems, demonstrating that the inhomogeneous nature of polarization remains unaltered even as the medium itself changes. The unitary nature of the channel allows us to undo this change through a simple lossless operation. This approach paves the way to the versatile application of vectorial structured light, even through non-ideal optical systems, crucial in applications such as imaging and optical communication across noisy channels.Structured light is shown to be robust against unitary perturbations.

Nanobodies are single variable domain antibodies isolated from camelids and are rapidly distinguishing themselves as ideal recognition elements in biosensors due to their comparative stability, ease of production and isolation, and high binding affinities. However, transducing analyte binding by nanobodies in real time is challenging, as most nanobodies do not directly produce an optical or electrical signal upon target recognition. Here, we report a general strategy to fabricate sensitive and selective electrochemical sensors incorporating nanobodies for detecting target analytes in heterogeneous media, such as cell lysate. Graphite felt can be covalently functionalized with recombinant HaloTag-modified nanobodies. Subsequent encapsulation with a thin layer of a hydrogel using a vapor deposition process affords encapsulated electrodes that directly display a decrease in current upon antigen binding, without added redox mediators. Differential pulse voltammetry affords clear and consistent decreases in electrode current across multiple electrode samples for specific antigen concentrations. The change in observed current vs increasing antigen concentration follows Langmuir binding characteristics, as expected. Importantly, selective and repeatable target binding in unpurified cell lysate is only demonstrated by the encapsulated electrode, with an antigen detection limit of ca. 30 pmol, whereas bare electrodes lacking encapsulation produce numerous false positive signals in control experiments.

Imaging can take many forms—from optical microscopes and telescopes through ultrasonography to X-ray tomography. However, regardless of the imaging modality, the presence of a complex heterogeneous structure between the imaging system and the scene of interest limits the quality of the images that can be conventionally obtained. In this Review we outline recently introduced strategies to overcome the detrimental effects of scattering in optical imaging. In particular, we focus on approaches that either physically correct scattering using computer-controlled devices or employ computational inversion based on intrinsic correlations of light scattering. Despite focusing on optical techniques, this Review emphasizes the fundamental equivalence of the effects of scattering in different fields of imaging, using the scattering matrix formalism as a bridge that allows techniques developed in one field to be translated to another. Seeing—and consequently imaging—through turbid media such as fog is a difficult task, as multiple scattering scrambles the visual information. This Review summarizes techniques that physically or computationally reconstruct the images.

The last decade has seen the development of a wide set of tools, such as wavefront shaping, computational or fundamental methods, that allow us to understand and control light propagation in a complex medium, such as biological tissues or multimode fibers. A vibrant and diverse community is now working in this field, which has revolutionized the prospect of diffraction-limited imaging at depth in tissues. This roadmap highlights several key aspects of this fast developing field, and some of the challenges and opportunities ahead.

The transfer of quantum information through a noisy environment is a central challenge in the fields of quantum communication, imaging and nanophotonics. In particular, high-dimensional quantum states of light enable quantum networks with significantly higher information capacities and noise robustness as compared with qubits. However, although qubit entanglement has been distributed over large distances through free space and fibre, the transport of high-dimensional entanglement is hindered by the complexity of the channel, which encompasses effects such as free-space turbulence or mode mixing in multimode waveguides. Here, we demonstrate the transport of six-dimensional spatial-mode entanglement through a 2-m-long, commercial multimode fibre with 84.4% fidelity. We show how the entanglement can itself be used to measure the transmission matrix of the complex medium, allowing the recovery of quantum correlations that were initially lost. Using a unique property of entangled states, the medium is rendered transparent to entanglement by carefully ‘scrambling’ the photon that did not enter it, rather than unscrambling the photon that did. Our work overcomes a primary challenge in the fields of quantum communication and imaging, and opens a new pathway towards the control of complex scattering processes in the quantum regime. Higher-dimensional entanglement between two photons can be preserved for a photon passing through a complex medium by applying an appropriate scrambling operation on the entangled partner that does not enter the complex medium.

Diverse processes—e.g. bioremediation, biofertilization, and microbial drug delivery—rely on bacterial migration in disordered, three-dimensional (3D) porous media. However, how pore-scale confinement alters bacterial motility is unknown due to the opacity of typical 3D media. As a result, models of migration are limited and often employ ad hoc assumptions. Here we reveal that the paradigm of run-and-tumble motility is dramatically altered in a porous medium. By directly visualizing individual Escherichia coli , we find that the cells are intermittently and transiently trapped as they navigate the pore space, exhibiting diffusive behavior at long time scales. The trapping durations and the lengths of “hops” between traps are broadly distributed, reminiscent of transport in diverse other disordered systems; nevertheless, we show that these quantities can together predict the long-time bacterial translational diffusivity. Our work thus provides a revised picture of bacterial motility in complex media and yields principles for predicting cellular migration. Many bacteria swim with run-and-tumble motion in unconfined fluid. Here the authors report that confinement of these bacteria in a 3D porous medium changes this motion into hopping and trapping, in which the cells are intermittently and transiently trapped as they navigate the pore space.

Extreme learning machines (ELMs) are a versatile machine learning technique that can be seamlessly implemented with optical systems. In short, they can be described as a network of hidden neurons with random fixed weights and biases, that generate a complex behaviour in response to an input. Yet, despite the success of the physical implementations of ELMs, there is still a lack of fundamental understanding about their optical implementations. This work makes use of an optical complex media to implement an ELM and introduce an ab-initio theoretical framework to support the experimental implementation. We validate the proposed framework, in particular, by exploring the correlation between the rank of the outputs, H , and its generalization capability, thus shedding new light into the inner workings of optical ELMs and opening paths towards future technological implementations of similar principles.

Metasurface-programmable radio environments are considered a key ingredient of next-generation wireless networks. Yet, identifying a metasurface configuration that yields a desired wireless functionality in an unknown complex environment was so far only achieved with closed-loop iterative feedback schemes. Here, we introduce open-loop wave control in metasurface-programmable complex media by estimating the parameters of a compact physics-based forward model. Our experiments demonstrate orders-of-magnitude advantages over deep-learning-based digital-twin benchmarks in terms of accuracy, compactness and required calibration examples. Strikingly, our parameter estimation also works without phase information and without providing measurements for all considered scattering coefficients. These unique generalization capabilities of our pure-physics model unlock unforeseen and previously inaccessible frugal wave control protocols that significantly alleviate the measurement complexity. For instance, we achieve coherent wave control (focusing or perfect absorption) and phase-shift-keying backscatter communications in metasurface-programmable complex media with intensity-only measurements. Our approach is also directly relevant to dynamic metasurface antennas, microwave-based signal processors and emerging in situ reconfigurable nanophotonic, optical and room-acoustical systems. Using a compact physics-based model, the authors experimentally achieve coherent wave control in metasurface-programmable complex systems with surprisingly frugal protocols (e.g., without ever measuring phase).