Resource-efficient photonic networks for next-generation AI computing.

Current trends in artificial intelligence toward larger models demand a rethinking of both hardware and algorithms. Photonics-based systems offer high-speed, energy-efficient computing units, provided algorithms are designed to exploit photonics' unique strengths. The recent implementation of cellular automata in photonics demonstrates how a few local interactions can achieve high throughput and precision.

Nonlinear processing with linear optics.

Deep neural networks have achieved remarkable breakthroughs by leveraging multiple layers of data processing to extract hidden representations, albeit at the cost of large electronic computing power. To enhance energy efficiency and speed, the optical implementation of neural networks aims to harness the advantages of optical bandwidth and the energy efficiency of optical interconnections. In the absence of low-power optical nonlinearities, the challenge in the implementation of multilayer optical networks lies in realizing multiple optical layers without resorting to electronic components.

An actor-model framework for visual sensory encoding.

A fundamental challenge in neuroengineering is determining a proper artificial input to a sensory system that yields the desired perception. In neuroprosthetics, this process is known as artificial sensory encoding, and it holds a crucial role in prosthetic devices restoring sensory perception in individuals with disabilities. For example, in visual prostheses, one key aspect of artificial image encoding is to downsample images captured by a camera to a size matching the number of inputs and resolution of the prosthesis.

Volume holograms with linear diffraction efficiency relation by (3 + 1)D printing.

We demonstrate the fabrication of volume holograms using two-photon polymerization with dynamic control of light exposure. We refer to our method as (3 + 1)D printing. Volume holograms that are recorded by interfering reference and signal beams have a diffraction efficiency relation that is inversely proportional to the square of the number of superimposed holograms.

Beyond fluorescence: advances in computational label-free full specificity in 3D quantitative phase microscopy.

Despite remarkable progresses in quantitative phase imaging (QPI) microscopes, their wide acceptance is limited due to the lack of specificity compared with the well-established fluorescence microscopy. In fact, the absence of fluorescent tag prevents to identify subcellular structures in single cells, making challenging the interpretation of label-free 2D and 3D phase-contrast data. Great effort has been made by many groups worldwide to address and overcome such limitation.

Forward-forward training of an optical neural network.

Neural networks (NNs) have demonstrated remarkable capabilities in various tasks, but their computation-intensive nature demands faster and more energy-efficient hardware implementations. Optics-based platforms, using technologies such as silicon photonics and spatial light modulators, offer promising avenues for achieving this goal. However, training multiple programmable layers together with these physical systems poses challenges, as they are difficult to fully characterize and describe with differentiable functions, hindering the use of error backpropagation algorithm.

Real-world effectiveness of golimumab in adult patients with rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis and an inadequate response to initial TNFi therapy in Greece: the GO-BEYOND prospective, observational study.

The impact of golimumab (GLM) on remission or low disease activity (LDA) was evaluated in patients with moderate-to-severe rheumatoid arthritis (RA), progressive psoriatic arthritis (PsA), or severe axial spondyloarthritis (axSpA), who failed previous treatment for their rheumatic disease with one initial tumor necrosis factor α inhibitor (TNFi). This is a multicenter, prospective, real-world observational 18-month study, conducted in Greece. The primary endpoint, assessed at 6 months, included the proportion of patients attaining LDA and/or remission (Disease Activity Score for 28 joints based on C-reactive protein [DAS28-CRP] ≤ 3.

From 3D to 2D and back again.

The prospect of massive parallelism of optics enabling fast and low energy cost operations is attracting interest for novel photonic circuits where 3-dimensional (3D) implementations have a high potential for scalability. Since the technology for data input-output channels is 2-dimensional (2D), there is an unavoidable need to take 2D-nD transformations into account. Similarly, the 3D-2D and its reverse transformations are also tackled in a variety of fields such as optical tomography, additive manufacturing, and 3D optical memories.

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry.

Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus.

Photonic waveguide bundles using 3D laser writing and deep neural network image reconstruction.

In recent years, three-dimensional (3D) printing with multi-photon laser writing has become an essential tool for the manufacturing of three-dimensional optical elements. Single-mode optical waveguides are one of the fundamental photonic components, and are the building block for compact multicore fiber bundles, where thousands of single-mode elements are closely packed, acting as individual pixels and delivering the local information to a sensor. In this work, we present the fabrication of polymer rectangular step-index (STIN) optical waveguide bundles in the IP-Dip photoresist, using a commercial 3D printer.

Learning to image and compute with multimode optical fibers.

Multimode fibers (MMF) were initially developed to transmit digital information encoded in the time domain. There were few attempts in the late 60s and 70s to transmit analog images through MMF. With the availability of digital spatial modulators, practical image transfer through MMFs has the potential to revolutionize medical endoscopy.

High speed, complex wavefront shaping using the digital micro-mirror device.

Digital micro-mirror devices (DMDs) have been deployed in many optical applications. As compared to spatial light modulators (SLMs), they are characterized by their much faster refresh rates (full-frame refresh rates up to 32 kHz for binary patterns) compared to 120 Hz for most liquid crystal SLMs. DMDs however can only display binary, unipolar patterns and utilize temporal modulation to represent with excellent accuracy multiple gray-levels in display applications.

Scalable optical learning operator.

Today's heavy machine learning tasks are fueled by large datasets. Computing is performed with power-hungry processors whose performance is ultimately limited by the data transfer to and from memory. Optics is a powerful means of communicating and processing information, and there is currently intense interest in optical information processing for realizing high-speed computations.

A membrane-less electrolyzer with porous walls for high throughput and pure hydrogen production.

Membrane-less electrolyzers utilize fluidic forces instead of solid barriers for the separation of electrolysis gas products. These electrolyzers have low ionic resistance, a simple design, and the ability to work with electrolytes at different pH values. However, the interelectrode distance and the flow velocity should be large at high production rates to prevent gas cross over.

3D reconstruction of weakly scattering objects from 2D intensity-only measurements using the Wolf transform.

A new approach to optical diffraction tomography (ODT) based on intensity measurements is presented. By applying the Wolf transform directly to intensity measurements, we observed unexpected behavior in the 3D reconstruction of the sample. Such a reconstruction does not explicitly represent a quantitative measure of the refractive index of the sample; however, it contains interesting qualitative information.

Inference in artificial intelligence with deep optics and photonics.

Artificial intelligence tasks across numerous applications require accelerators for fast and low-power execution. Optical computing systems may be able to meet these domain-specific needs but, despite half a century of research, general-purpose optical computing systems have yet to mature into a practical technology. Artificial intelligence inference, however, especially for visual computing applications, may offer opportunities for inference based on optical and photonic systems.

Fabrication of Sub-Micron Polymer Waveguides through Two-Photon Polymerization in Polydimethylsiloxane.

Flexible ultra-compact low-loss optical waveguides play a vital role in the development of soft photonics. The search for suitable materials and innovative fabrication techniques to achieve low loss long polymer optical waveguides and interconnects has proven to be challenging. In this paper, we demonstrate the fabrication of submicron optical waveguides in polydimethylsiloxane (PDMS) using divinylbenzene (DVB) as the photopolymerizable monomer through two-photon polymerization (2PP).

Gravitational Test beyond the First Post-Newtonian Order with the Shadow of the M87 Black Hole.

The 2017 Event Horizon Telescope (EHT) observations of the central source in M87 have led to the first measurement of the size of a black-hole shadow. This observation offers a new and clean gravitational test of the black-hole metric in the strong-field regime. We show analytically that spacetimes that deviate from the Kerr metric but satisfy weak-field tests can lead to large deviations in the predicted black-hole shadows that are inconsistent with even the current EHT measurements.

Fluorescence-Based and Fluorescent Label-Free Characterization of Polymer Nanoparticle Decorated T Cells.

Cells are attractive carriers for the transport and delivery of nanoparticulate cargo. The use of cell-based carriers allows one to enhance control over the biodistribution of drug-loaded polymers and polymer nanoparticles. One key element in the development of cell-based delivery systems is the loading of the cell-based carrier with the nanoparticle cargo, which can be achieved either by internalization of the payload or by immobilization on the cell surface.

All-fiber spatiotemporally mode-locked laser with multimode fiber-based filtering.

We demonstrate the first all-fiber multimode spatiotemporally mode-locked laser. The oscillator generates dissipative soliton pulses at 1036 nm with 12 mW average power, 6.24 ps duration, and 24.

In Vitro Cytocompatibility Assessment of Ti-Modified, Silicon-oxycarbide-Based, Polymer-Derived, Ceramic-Implantable Electrodes under Pacing Conditions.

Polymer-derived ceramics (PDC) have recently gained increased interest in the field of bioceramics. Among PDC's, carbon-rich silicon oxycarbide ceramics (SiOC) possess good combined electrical and mechanical properties. Their durability in aggressive environments and proposed cytocompatibility makes them an attractive material for fabrication of bio-MEMS devices such as pacemaker electrodes.

Microfluidic-based linear-optics label-free imager.

Linear optics based nanoscopy previously reached resolution beyond the diffraction limit, illuminating samples in the visible light regime while allowing light to interact with freely moving metallic nanoparticles. However, the hydrodynamics governing the nanoparticle motion used to scan the sample is very complex and has low probability of achieving appropriate and fast mapping in practice. Hence, an implementation of the technique on real biological samples has not been demonstrated so far.

Imaging hair cells through laser-ablated cochlear bone.

We report an innovative technique for the visualization of cells through an overlying scattering medium by combining femtosecond laser bone ablation and two-photon excitation fluorescence (TPEF) microscopy. We demonstrate the technique by imaging hair cells in an intact mouse cochlea . Intracochlear imaging is important for the assessment of hearing disorders.

High-fidelity optical diffraction tomography of multiple scattering samples.

We propose an iterative reconstruction scheme for optical diffraction tomography that exploits the split-step non-paraxial (SSNP) method as the forward model in a learning tomography scheme. Compared with the beam propagation method (BPM) previously used in learning tomography (LT-BPM), the improved accuracy of SSNP maximizes the information retrieved from measurements, relying less on prior assumptions about the sample. A rigorous evaluation of learning tomography based on SSNP (LT-SSNP) using both synthetic and experimental measurements confirms its superior performance compared with that of the LT-BPM.