Quantum computers still face a major hurdle on their pathway to practical use cases: their limited ability to correct the arising computational errors. To develop truly reliable quantum computers, researchers must be able to simulate quantum computations using conventional computers to verify their correctness – a vital yet extraordinarily difficult task. Now, in a world-first, researchers from Chalmers University of Technology in Sweden, the University of Milan, the University of Granada, and the University of Tokyo have unveiled a method for simulating specific types of error-corrected quantum computations – a significant leap forward in the quest for robust quantum technologies.

New research reveals a surprising geometric link between human and machine learning. A mathematical property called convexity may help explain how brains and algorithms form concepts and make sense of the world.

The strength of certain neural connections can predict how well someone can learn math, and mild electrically stimulating these networks can boost learning, according to a study published on July 1^st in the open-access journal PLOS Biology by Roi Cohen Kadosh from University of Surrey, United Kingdom, and colleagues.

MIT researchers developed a new system that enables a robot to use reflected Wi-Fi signals to identify the shape of a 3D object that is hidden from view, which could be especially useful in warehouse and factory settings. 

The research team proposed a novel discrete-modulated coherent-state quantum key distribution with basis encoding. In this scheme, Alice performs discrete modulation on the coherent state and sends it to Bob. Bob performs coherent detection and encodes the key in the base selection, ultimately publishing the measurement results.