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There is a long way to go before quantum information (QI) can have a real-world impact on machine learning applications. However, in the short term, QI presents a principled approach to unravel performance bounds and find hidden quantum-classical parallels for widely used machine learning algorithms...

Congratulations to Mohammad Ali Javidian on the selection of his paper titled “Tensor Rings for Learning Circular Hidden Markov Models” which was virtually presented at the second Workshop on Quantum Tensor Networks in Machine Learning.

A new approach to control forces and interactions between atoms and molecules, such as those employed by geckos to climb vertical surfaces, could bring advances in new materials for developing quantum light sources.

A newly described property related to the "spin" and momentum of light waves suggests potential practical applications in photonic communications and photonic circuits. Scientists already knew that light waves have an electric field that can rotate as they propagate, which is known as the polarization property of light, and that light waves carry momentum in their direction of motion. In new findings, researchers have discovered a "spin-momentum locking," meaning, for example, light waves that spin in a counterclockwise direction can only move forward, and vice versa.

Researchers at Purdue University have created a quantum spin wave for light. This can be a carrier of information for future nanotechnologies but with a unique twist: they only flow in one direction.

Manufacturers frequently use coatings to protect the structural stability of engines or power generators operating at high temperatures. Ceramic shields, however, have not been able to adequately address a critical, performance-limiting factor: heat radiation. A new ceramic coating from Purdue University acts as a kind of thermal antenna, using light-matter oscillations, or polaritrons, to control the direction and electromagnetic spectrum of thermal radiation.