Abstract
Technological advances in global communications depend significantly on robust and efficient long-distance infrastructures. One notable example is the submarine cable network. Installed on the ocean floor, these cables use fiber optic technology to transmit large volumes of data at high speed and low latency between continents. Beyond their primary communication function, recent innovations allow these cables to serve as Distributed Acoustic Sensing (DAS) systems, effectively converting tens of kilometers of passive fiber into massive, coherent arrays of vibration sensors. The primary objective of this project is to enhance maritime surveillance capabilities by integrating DAS technology with advanced kinematic modeling. This paper establishes a rigorous physical and mathematical framework for interpreting the acoustic signatures of surface vessels detected by bottom-mounted fibers. We derive the complete opto-acoustic transfer function, formulate the hyperbolic moveout equations based on a moving point-source solution to the wave equation, and implement a stochastic inversion scheme using Differential Evolution. By optimizing a correlation-based loss function, we demonstrate the ability to recover vessel trajectory, speed, and depth from complex interferometric patterns with speed estimation errors consistently below 1%. This approach allows for the extraction of quantitative physical parameters from raw optical data, bridging the gap between photonics and hydroacoustics.

Abstract
A novel technique based on multiple amplitude wavelength modulation spectroscopy (MA-WMS) for simultaneous measurement of CH4\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {CH}_4$$\end{document} gas concentration and pressure was developed and validated both through simulation and experiment, showing good agreement. To capture the spectrum broadening caused by increasing pressure and concomitantly obtain the concentration at the sensor's location, a laser centered at 1650.9 nm was subjected to multiple amplitude modulation depths while the 2fm\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2f_{m}$$\end{document} signal, normalized by the DC component (an invariant quantity under optical loss), was recorded. While the use of a single and fixed modulation can introduce an ambiguity, as different pairs of pressure and concentration can yield the same value, this ambiguity is eliminated by employing multiple amplitude modulations. In this approach, the intersection point of the three level curves can provide the local pressure and concentration. The proposed system was able to measure concentrations from 5% up to 45% and pressures from 0.25 atm up to 1.75 atm, with a maximum error of 2% in concentration and 0.06 atm in pressure, respectively. The system was also tested for attenuation insensitivity, demonstrating that measurements were not significantly affected for up to 10 dB applied optical loss.

Abstract
Hydrogen (H2) detection has become extremely important in recent years due to the increasing need for sustainable alternative energy sources. In this field, optical sensors can contribute significantly due to remote interrogation capabilities and the absence of ignition sources. Among the different H2 optical sensors, plasmonic sensors appear to be a very sensitive technology; however, they require expensive plasmonic materials like gold or silver, which, together with a palladium-sensitive layer, can increase the sensor cost. In addition, plasmonic bands are usually outside the ideal infrared range for remote interrogation, between 1500 and 1600 nm. This work presents a polymer-protected Tamm Plasmon Resonance (TPR) sensor with a well-defined resonance band at 1572 nm composed of SiO2, TiO2 layers, and palladium as a sensitive layer. This architecture can reduce the production cost of sensing structures, replacing plasmonic films with dielectric materials, while offering improved resonance definition at longer wavelengths. First, numerical calculations were carried out using the Transfer-Matrix Method to study the impact of the thickness of each layer, incidence angle, and light polarization on the resonance band wavelength and H2 sensitivity. The optimized structure was then fabricated, exhibiting a wavelength shift of 9.5 nm to 4 vol % of H2, a response time of 30 s, and no cross-sensitivity to methane or ammonia. The sensor also demonstrated high stability and resistance to environmental degradation up to eight days. These results emphasize the advantages of TPR structures for gas sensing in the infrared spectral range, opening new avenues for remote plasmonic sensing. © 2026 The Authors. Published by American Chemical Society

Abstract
Detection of leaks in hydrogen (H2) infrastructure is required on a large scale to enable a safe widespread use of this clean energy source. Sensing solutions must be low-cost, use scalable fabrication methods and allow multiplexed detection while providing reliable safety alarms as fast as possible. Optical methods can make this possible while avoiding the risk of ignition due to electronics at the point of detection. Metal hydride-based micro-mirror configurations benefit from a simple interrogation scheme, as long as the sensitive element can produce a large optical response. Magnesium thin films undergo a drastic variation of properties when hydrogenated, making them suitable for this application. In this work, a micro-mirror device using single-mode fibers capable of detecting the presence of H2 with a loading t10 and t90 of 1.2 and 3.0 s, respectively, is demonstrated. A complete interrogation unit was developed, presenting a solution suited for widespread deployment using industry-standard optical components and equipment.

Abstract
Abstract The development of computing paradigms alternative to von Neumann architectures has recently fueled significant progress in novel all-optical processing solutions. In this work, we investigate how the coherence properties can be exploited for computing by expanding information onto a higher-dimensional space in the photonic extreme learning machine framework. A theoretical framework is provided based on the transmission matrix formalism, mapping the input plane onto the output camera plane, resulting in the establishment of the connection with complex extreme learning machines and derivation of upper bounds for the hidden space dimensionality as well as the form of the activation functions. Experiments using free-space propagation through a diffusive medium, performed in low-dimensional input space regimes, validate the model and the proposed estimator for the dimensionality. Overall, the framework presented and the findings enclosed have the potential to foster further research in a multitude of directions, from the development of robust general-purpose all-optical hardware to a full-stack integration with optical sensing devices toward edge computing solutions.

Abstract
Speckle-based fiber optic sensors are well-known to offer high sensitivity but are strongly limited on the in terrogation side by low camera frame rates and dynamic range. To address this limitation, we present a novel interrogation framework that explores event-based vision to achieve high throughput, high bandwidth, and low-latency speckle analysis of a multimode optical fiber sensor. In addition, leveraging an optimized decomposition of the raw event streams through multi-point calibration and machine learning optimization, our approach also proves capable of isolating simultaneous deformations applied at distinct points. The experimental results vali date the methodology by separating the signals of four piezoelectric actuators over a 400 Hz-20 kHz range with minimal crosstalk applied over varying distances from 3 cm to 75 cm. Overall, these results establish event-driven speckle interrogation as a new versatile platform for real-time, multi-point acoustic sensing and pave the way for its application in complex and unstructured environments in future works.