Computers Math

Scientists at the University of Bonn have built hair-thin optical fibre filters in a very simple way. They are not only extremely compact and stable, but also colour-tunable. This means they can be used in quantum technology and as sensors for temperature or for detecting atmospheric gases. The results have been published in the journal Optics Express.
Optical fibers not much thicker than a human hair today not only constitute the backbone of our world-wide information exchange. They are also the basis for building extremely compact and robust sensors with very high sensitivity for temperature, chemical analysis and much more.
Optical resonators or filters are important components cutting out very narrow spectral lines from white light sources. In the simplest case such filters are built from two opposing mirrors tossing light back and forth as precisely as the pendulum of a clock work. The color of the filtered light is set by the mirror separation.
Suitable mirrors with high quality have been integrated with the end of such hairlike fibers for some time. Researchers of the University of Bonn have succeeded to build in a simple way such hairlike optical fiber resonators. They are not only extremely compact and stable but also allow to tune their color: they have glued the fiber ends carrying the mirrors into a common ferrule which can be stretched by means of a piezo crystal and hence control the mirror separation.
“The miniaturised optical filter makes a further contribution to making photonics and quantum technologies the decisive technology of the 21st century,” says Prof. Dr. Dieter Meschede from the Institute of Applied Physics at University of Bonn. The scientist is a member of “Matter and light for quantum computing” (ML4Q) Cluster of Excellence of the Universities of Bonn and Cologne and RWTH Aachen University and is also a member of the Transdisciplinary Research Area “Building Blocks of Matter and Fundamental Interactions” at the University of Bonn.
Miniaturized highly stable optical precision filters are promising multiple applications: they can store light energy within such a small volume such that already single photons can be efficiently stored and manipulated. Their high sensitivity suggests to build extremely compact and selective sensors, e.g. for detecting atmospheric gases. Using even more stable materials for the ferrule tiny optical clock works with extremely high frequency stability may be built.

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Robots are widely used to build cars, paint airplanes and sew clothing in factories, but the assembly of microscopic components, such as those for biomedical applications, has not yet been automated. Lasers could be the solution. Now, researchers reporting in ACS Applied Materials & Interfaces have used lasers to create miniature robots from bubbles that lift, drop and manipulate small pieces into interconnected structures.
As manufacturing has miniaturized, objects are now being constructed that are only a few hundred micrometers long, or about the thickness of a sheet of paper. But it is hard to position such small pieces by hand. In previous studies, scientists created microscopic bubbles using light or sound to assemble 2D items. Also, in a recent experiment, microbubbles produced by lasers, focused and powerful beams of light, could rotate shapes in 3D space. Although these bubble microrobots could manipulate 2D and 3D objects, they could not connect independent components and then move them as a singular entity. So, Niandong Jiao, Lianquing Liu and colleagues wanted to build on their previous work with lasers to develop bubble microbots that can form inseparable shapes and control their movement.
The researchers created microbubbles in water by focusing a laser underneath a small part made of resin. The bubble’s size was controlled by rapidly switching the laser on and off, with a higher amount of time in the “on position” resulting in larger bubbles. Then, the team made a mobile bubble robot by shifting the laser’s location. Once the laser turned off, the bubbles dissolved slowly, dropping the resin in place. The team then combined multiple bubbles with different functions to produce microrobots that could lift and drop parts, move single pieces to designated positions, act as a rotational axis or push assembled objects. Unbreakable connections were made with various joints, producing three- and four-pronged gears, a snake-shaped chain and a miniature 3D vehicle. The bubble microrobots have implications for the future of manufacturing, including biological tissue engineering, the researchers say.

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A team of researchers from the Faculty of Pure and Applied Sciences at the University of Tsukuba filmed the ultrafast motion of electrons with sub-nanoscale spatial resolution. This work provides a powerful tool for studying the operation of semiconductor devices, which can lead to more efficient electronic devices.
The ability to construct ever smaller and faster smartphones and computer chips depends on the ability of semiconductor manufacturers to understand how the electrons that carry information are affected by defects. However, these motions occur on the scale of trillionths of a second, and they can only be seen with a microscope that can image individual atoms. It may seem like an impossible task, but this is exactly what a team of scientists at the University of Tsukuba was able to accomplish.
The experimental system consisted of Buckminsterfullerene carbon molecules — which bear an uncanny resemblance to stitched soccer balls — arranged in a multilayer structure on a gold substrate. First, a scanning tunneling microscope was set up to capture the movies. To observe the motion of electrons, an infrared electromagnetic pump pulse was applied to inject electrons into the sample. Then, after a set time delay, a single ultrafast terahertz pulse was used to probe the location of the elections. Increasing the time delay allowed the next “frame” of the movie to be captured. This novel combination of scanning tunneling microscopy and ultrafast pulses allowed the team to achieve sub-nanoscale spatial resolution and near picosecond time resolution for the first time. “Using our method, we were able to clearly see the effects of imperfections, such as a molecular vacancy or orientational disorder,” explains first author Professor Shoji Yoshida. Capturing each frame took only about two minutes, which allows the results to be reproducible. This also makes the approach more practical as a tool for the semiconductor industry.
“We expect that this technology will help lead the way towards the next generation of organic electronics” senior author Professor Hidemi Shigekawa says. By understanding the effects of imperfections, some vacancies, impurities, or structural defects can be purposely introduced into devices to control their function.

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Researchers have discovered a short-lived form of the famous Higgs boson — subject of a groundbreaking search at the Large Hadron Collider — within an iron-based superconductor. This Higgs mode can be accessed and controlled by laser light flashing on the superconductor at trillions of pulses per second. More

Computer scientists developed a deep learning method to create realistic objects for virtual environments that can be used to train robots. The researchers used TACC’s Maverick2 supercomputer to train the generative adversarial network. The network is the first that can produce colored point clouds with fine details at multiple resolutions. More

Following a series of studies on termite mound physiology and morphogenesis over the past decade, researchers have now developed a mathematical model to help explain how termites construct their intricate mounds. More

Scientists have successfully used satellite cameras coupled with deep learning to count animals in complex geographical landscapes, taking conservationists an important step forward in monitoring populations of endangered species. More

Researchers present an optical flow-based learning process that allows robots to estimate distances through the visual appearance (shape, color, texture) of the objects in view. This artificial intelligence (AI)-based learning strategy increases the navigation skills of small flying drones and entails a new hypothesis on insect intelligence. More