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Tomás Lopes

Publications and source records attributed to Tomás Lopes.

6 recordsLinked to original sources

Characterization of Event-Based Vision Sensors for High-Speed Optical Instrumentation

Event-based vision sensors provide asynchronous event generation and microsecond timestamp resolution, which may be useful for high-speed optical measurements. However, precise event timestamps do not necessarily guarantee accurate reconstruction of temporally varying optical signals, particularly under dense and spatially extended illumination, imposing operational limits when used as optical interrogators that remain underexplored in the literature. To address this knowledge gap, this work presents a systematic, quantitative characterization of the temporal response and waveform reconstruction fidelity of an IMX636-based event camera under both controlled sinusoidal and pulsed optical excitation. For this, frequency-domain measurements are first used to evaluate modulation response, event-rate behavior, polarity balance, and spectral reconstruction fidelity over a wide range of illumination conditions and region-of-interest geometries. Then, complementary pulse-based measurements quantify first-event latency, response duration, recovery dynamics, and pulse-width reconstruction accuracy under rapidly repeated excitation, showing that optical transitions can be detected with first-event latencies below 5 microseconds. However, the complete event response extends over significantly longer timescales due to photoreceptor dynamics, refractory behavior, and readout serialization. Under high-frequency modulation and short-pulse excitation, the reconstructed waveforms progressively degrade because of temporal spreading and imbalance between positive and negative event generation. The measurements further demonstrate that the temporal fidelity of the reconstructed signal depends strongly on the geometry and spatial activity of the selected region of interest.

physics.optics

Towards Neuromorphic Event-Based Sensing for High-Speed Multi-Spectral Classification and Tracking of Microparticles

Conventional image-based microfluidic systems face an inherent trade-off between throughput, imaging speed, and data bandwidth, limiting their ability to monitor high-velocity flows without significant motion blur or prohibitive data generation. Event-based sensing has emerged as a high-speed, low-power alternative, but has so far been largely restricted to tracking monodisperse, spherical particles. In this work, we introduce a microfluidic sensing platform that enables the simultaneous extraction of kinematic and spectral information from polydisperse microparticles using a neuromorphic imaging approach. By integrating a spatially multiplexed RGB filter mask with an asynchronous event-based sensor, spectral signature and motion are encoded directly at the sensing stage, eliminating the need for image reconstruction or learning-based inference. The system achieves sub-millisecond temporal resolution and maintains robust classification performance across a broad range of particle sizes and flow velocities, including under non-laminar conditions, reaching up to 82% accuracy for classification of colored particles within the 0.08-0.18 mm range. The event-driven architecture reduces data bandwidth by >240x compared to conventional high-speed imaging, while sustaining an area throughput of 460 mm^2/s. By providing a computationally efficient and low-latency particle characterization, this framework paves the way for a scalable solution towards high-speed, label-free screening of heterogeneous analytes in clinical diagnostics and environmental monitoring.

physics.optics

All-optical Edge Computing for Speckle Sensing Interrogation

Speckle-based sensing exploits the rich environmental information of its high-dimensional spatial intensity patterns. However, the requirement for camera-based acquisition and subsequent electronic digitization introduces significant latency and bandwidth bottlenecks that forbid real-time operation and higher temporal resolutions. Aiming to bypass this imaging processing pipeline, this manuscript presents an optically reconfigurable edge-computing platform for speckle-based sensors that performs task-specific computation directly in the optical domain. This is achieved by projecting output speckle patterns onto a digital micromirror device, using it as a programmable optical layer whose parameters are trained in situ using an evolutionary optimization strategy solely from detector feedback. We demonstrate the concept with a multi-point optical fiber sensing task, where multiple piezoelectric actuators simultaneously perturb the fiber, modifying the speckle pattern. Optimizing a set of masks to decouple these concurrent signals, the system successfully achieves real-time signal separation, achieving a target signal enhancement exceeding 4 dB while suppressing crosstalk leakage below -10 dB. Operating with bandwidths limited only by the photodetector, this approach paves the way for real-time and ultrafast optical sensing via an all-optical edge computing solution.

physics.optics

Multimodal Speckle-polarization Fiber-optic Sensing for Localized and High-bandwidth Vibration Monitoring

High-bandwidth and multi-point acoustic and vibration sensing is a critical asset for real-time condition monitoring, maintenance, and surveillance applications. In the case of large scales and harsh environments, optical fiber distributed sensing has emerged as a compelling alternative to electronic transducers, featuring lower installation and maintenance costs, along with compact footprints and enhanced robustness. Yet, current distributed fiber-optic sensing solutions are typically costly and face a resolution-bandwidth tradeoff. In this work, we present an alternative fiber-optic vibration sensing strategy that harnesses a multimodal architecture combining speckle and polarization interrogation. The experimental results demonstrate the concept by achieving speckle-based signal source localization with centimeter-range spatial resolution, while obtaining a high-fidelity waveform reconstruction over at least 100 Hz-40 kHz bandwidth via the polarimetric sensing part. Overall, the work establishes a general and promising blueprint to harness multimodality in fiber sensing and break single-modality constraints.

physics.optics

Event-based Speckle Interrogation for High-Bandwidth Multi-point Optical Fiber Sensing

Speckle-based fiber optic sensors are well-known to offer high sensitivity but are strongly limited on the interrogation 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 a tensor-based 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 validate the methodology by separating the signals of four piezoelectric actuators over a 400Hz-20kHz range with minimal crosstalk applied over varying distances from 3cm to 75cm. Finally, extending the impact of the work with an acoustic sensing proof-of-concept, we have coupled the fiber to two plastic enclosures and recovered separable audio signals between 400 and 1.8 kHz with minimal waveform distortion. Overall, these results establish event-driven speckle interrogation as a new versatile platform for real-time, multi-point acoustic sensing and pave for its application in complex and unstructured environments in future works.

physics.optics

Impact of electroweak group representation in models for $B$ and $g-2$ anomalies from Dark Loops

We discuss two models which are part of a class providing a common explanation for lepton flavor universality violation in $b \to s l^+ l^- $ decays, the dark matter (DM) problem and the muon $(g-2)$ anomaly. The $B$ meson decays and the muon $(g-2)$ anomalies are explained by additional one-loop diagrams with DM candidates. The models have one extra fermion field and two extra scalar fields relative to the Standard Model (SM). The $SU(3)$ quantum numbers are fixed by the interaction with the SM fermions in a new Yukawa Lagrangian that connects the dark and the visible sectors. We compare two models, one where the fermion is a singlet and the scalars are doublets under $SU(2)_L$ and another one where the fermion is a doublet and the scalars are singlets under $SU(2)_L$. We conclude that both models can explain all new physics phenomena simultaneously, while satisfying all other flavor and DM constraints. However, there are crucial differences between how the DM constraints affect the two models leading to a noticeable difference in the allowed DM mass range.

hep-ph