Topological quantum magnets are advanced materials that exhibit quantum behavior. Additionally, the magnetic spins of their particles are arranged in a way that creates stable and robust topological states.

These topological states are resistant to any external disturbances. Additionally, the spins in these materials can be entangled. This means they are deeply connected on a quantum level, and therefore don’t easily lose their quantum properties.

However, “So far, experiments have mostly explored non-interacting topological states, and the realization of many-body topological phases in solid-state platforms with atomic resolution has remained challenging,” the study authors note.

The ability to detect objects in settings with unfavorable lighting, for example at night, in shadowed locations or in foggy conditions, could greatly improve the reliability of autonomous vehicles and mobile robotic systems. Most widely employed computer vision methods, however, have been found to perform under poor lighting.

Researchers at the Hong Kong Polytechnic University recently introduced a new bio-inspired vision sensor that can adapt to the spectral features of the environments it captures, thus successfully detecting objects in a wider range of lighting conditions. This newly developed sensor, introduced in a paper published in Nature Electronics, is based on an array of photodiodes arranged back-to-back.

“In a previous paper in Nature Electronics, we presented a simple in-sensor light intensity adaptation approach to improve the recognition accuracy of machine vision systems,” Bangsen Ouyang, co-author of the paper, told Tech Xplore.

For centuries, we thought that the Universe was completely deterministic. But even if you know all the rules, you can’t get rid of chaos.

Bioacoustic technology detects early tuberculosis, transforming remote healthcare.

Google partners with Salcit Technologies to bring AI-powered disease detection to smartphones using 300 million audio samples.