The unification of the theory of relativity and quantum mechanics is a long-standing challenge in contemporary physics. Experimental techniques in quantum optics have only recently reached the maturity required for the investigation of quantum systems under the influence of non-inertial motion, such as being held at rest in gravitational fields, or subjected to uniform accelerations. Here, we report on experiments in which a genuine quantum state of an entangled photon pair is exposed to a series of different accelerations. We measure an entanglement witness for g-values ranging from 30 mg to up to 30 g—under free-fall as well on a spinning centrifuge—and have thus derived an upper bound on the effects of uniform acceleration on photonic entanglement.
This paper focuses on exploring ways to improve the performance of LiDAR imagers through fog. One of the known weaknesses of LiDAR technology is the lack of tolerance to adverse environmental conditions, such as the presence of fog, which hampers the future development of LiDAR in several markets. Within this paper, a LiDAR unit is designed and constructed to be able to apply temporal and polarimetric discrimination for detecting the number of signal photons received with detailed control of its temporal and spatial distribution under co-polarized and cross-polarized configurations. The system is evaluated using different experiments in a macro-scale fog chamber under controlled fog conditions. Using the complete digitization of the acquired signals, we analyze the natural light media response, to see that due to its characteristics it could be directly filtered out. Moreover, we confirm that there exists a polarization memory effect, which, by using a polarimetric cross-configuration detector, allows improvement of object detection in point clouds. These results are useful for applications related to computer vision, in fields like autonomous vehicles or outdoor surveillance where many variable types of environmental conditions may be present.
Whole eye visualization and morphometry are of high relevance in clinical practice. However, most standard ophthalmic OCT instruments are dedicated either to retinal or to anterior segment imaging. We demonstrate a swept source optical coherence tomography system (SS-OCT) that images both the whole anterior segment and the retina alternately using a single source and detector. A pilot population was imaged with the proof of concept prototype. We demonstrate the clinical potential of whole eye OCT screening for the description and early detection of relevant clinical features in the anterior segment and retina of several patients.
In recent times, there has been a surge of interest in LiDAR imaging systems, particularly in outdoor terrestrial applications associated with computer vision. However, a significant hurdle preventing their widespread implementation lies in their limited tolerance for adverse weather conditions, such as fog. To address this challenge, researchers have explored the capability of polarization in improving detection capabilities in such media. This paper explores the potential of LiDAR technology to obtain polarized images through fog and investigates the impact of fog on object detection using digitized temporal signals and point clouds. The study utilizes a LiDAR-polarized imaging system using circular polarization, which has been shown to enhance image contrast in highly-dispersive media. The analysis of the polarimetric information of the backscattered light signal in fog reveals its influence on object detection and evaluates the range difference between orthogonal polarimetric channels: coplanar and cross-configuration. The results demonstrate that cross-configuration detection provides larger range and more detailed point clouds compared to coplanar configuration, particularly benefiting metallic objects, for the same foggy conditions. By utilizing circularly polarized incident light and cross-configuration detection, the LiDAR system can improve the signal-to-noise ratio by filtering out the co-polarized fog responses. However, the range of the system may be reduced compared to nonpolarized detection. Overall, our findings indicate that utilizing a cross-polarization detection setup can effectively reduce the impact of fog backscatter while preserving the return signal from objects of interest in the majority of cases.
Automated systems increase their requirements in all fields, tightening their performance requirements in aspects like reliability, and ease of manipulation. Within this communication, we will present the development of a compact perception unit which includes a 3D lidar, RGB and thermal imaging for advanced perception purposes. The proposed unit intends to solve the usual hardware problems that software developers intend to solve in field applications. The basic features and performance of the system will be presented, and the applicability of the multimodal sensing approach presented to different applications in security, autonomous vehicles, and other application areas will be overviewed with examples.
The interest in LiDAR imaging systems has recently increased in outdoor ground-based applications related to computer vision, in fields like autonomous vehicles and surveillance. However, for the complete settling of the technology, there are still obstacles related to outdoor performance, being its use in adverse weather conditions one of the most challenging. When working in bad weather, data shown in point clouds is unreliable and its temporal behavior is unknown. That is why we have designed, constructed, and tested a scanning-pulsed LiDAR imaging system with outstanding characteristics related to optoelectronic modifications, in particular including digitization capabilities of each of the pulses. Our contribution is related to the digitization, analysis, and characterization of the acquired signal when steering to a target under foggy conditions, as well as the proposal of different strategies to improve point clouds generated in these conditions. The system performance was tested in a macro-scale fog chamber and, using the collected data, two relevant phenomena were identified. Firstly, the backscattering signal of light that first interacts with the media. It is usually responsible for the saturation of the sensor but signal analysis shows it may be easily filtered out. Secondly, false-positive points that appear due to the scattering properties of the media, which only add noise to the point cloud. Digitization of the complete signal can be used to develop algorithms to identify and get rid of them.
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