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We demonstrate that a software architecture using innovations in machine learning and adaptive control provides an ideal integration platform for self-tuning optics. For mode-locked lasers, commercially availab...

In the recent years, a dramatic boost of the research is observed at the junction of photonics, machine learning and artificial intelligence. A new methodology can be applied to the description of a variety of photonic s...

Over the past decade, artificially engineered optical materials and nanostructured thin films have revolutionized the area of photonics by employing novel concepts of metamaterials and metasurfaces where spatially varyin...

Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applications, including telecommunications, imagin...

Digital in-line holographic microscopy (DIHM) is a widely used interference technique for real-time reconstruction of living cells’ morphological information with large space-bandwidth product and compact setup. Howeve...

The intrinsic complexity of nonlinear optical phenomena offers a fundamentally new resource to analog brain-inspired computing, with the potential to address the pressing energy requirements of artificial intelligence. W...

Abstract Model instability remains a core challenge for data‐driven parameterizations, especially those developed with supervised algorithms, and rigorous methods to address it are lacking. Here, by integrating machine...

This study investigates the role of the principle of historicism in physics education, emphasizing its impact on students’ scientific competencies. By integrating historical elements into secondary school physics curri...

Single-pixel imaging (SPI) is a prominent scattering media imaging technique that allows image transmission via one-dimensional detection under structured illumination, with applications spanning from long-range imaging ...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

While physics models for predicting system states can reveal fundamental insights owing to their parsimonious structure, they may not always yield the most accurate predictions, particularly for complex systems. As an al...

Voltage stability in modern smart grids faces increasing challenges due to the widespread use of renewable energy and diminished reactive-power margins. While power flow analysis remains the most precise method, it is of...

The popularity of deep learning has boosted computer-generated holography (CGH) as a vibrant research field, particularly physics-driven unsupervised learning. Nevertheless, present unsupervised CGH models have not yet e...

IntroductionVision-based fall analysis has advanced rapidly, yet a key bottleneck remains: visually similar motions can correspond to markedly different physical outcomes, as subtle differences in contact mechanics and p...

Nanophotonics has been an active research field over the past two decades, triggered by the rising interests in exploring new physics and technologies with light at the nanoscale. As the demands of performance and integr...

Abstract As global warming continues, the Earth's cryosphere is experiencing severe degradation. This study leverages a novel combination of distributed acoustic sensing (DAS) and artificial intelligence to monitor and d...

Esta investigación tiene como objetivo describirlas creencias de un grupo de profesores chilenos de física en relación al aprendizaje de la ciencia en el contexto de la educación secundaria de la Región de Valparaí...

The question of the development of physical science in the Carpathian region (end of the 18th - beginning of the 21st century) was studied, starting from the Tsar's Royal Gymnasium, organized in 1784, to the creation of ...

Student difficulties with kinematics concepts and their representations by linear graphs are well known. Several specific learning difficulties have been identified and reported, mainly from studies at the introductory u...

La enseñanza y el aprendizaje de las Ciencias Naturales presentan en la actualidad dificultades que se evidencian, entre otras cosas, en los bajos resultados de los estudiantes en las evaluaciones. A fin de profundizar ...

Link performance functions (LPFs) underpin the estimation of travel times, delays, and congestion in transportation network models. As multimodal systems become increasingly data rich and feature connected and automated ...

Nowadays, the new technologies challenge the educational practices. When teachers face this new teaching and learning pattern they need to adopt a different attitude: of a mediator, in which one its main role is to exper...

Abstract The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons an...

As physics teachers we faced the challenge to introduce our freshmen engineering students not only into the world of Physics but also into the skills and abilities necessary to learn, analyze and criticize different situ...