Harnessing machine learning to analyze quantum material

Electrons and their behavior pose fascinating questions for quantum physicists, and recent innovations in sources, instruments and facilities allow researchers to potentially access even more of the information encoded in ...

A new age of 2.5D materials

Scientists are exploring new ways to artificially stack two-dimensional (2D) materials, introducing so-called 2.5D materials with unique physical properties. Researchers in Japan reviewed the latest advances and applications ...

Minimizing laser phase noise with machine learning

Ultra-precise lasers can be used for optical atomic clocks, quantum computers, power cable monitoring, and much more. But all lasers make noise, which researchers from DTU Fotonik want to minimize using machine learning.

Study: Machine learning a useful tool for quantum control

In the everyday world, we can perform measurements with nearly unlimited precision. But in the quantum world—the realm of atoms, electrons, photons, and other tiny particles—this becomes much harder. Every measurement ...

Breakthrough proof clears path for quantum AI

Convolutional neural networks running on quantum computers have generated significant buzz for their potential to analyze quantum data better than classical computers can. While a fundamental solvability problem known as ...

Machine-learning technique used to pinpoint quantum errors

Researchers at the University of Sydney and quantum control startup Q-CTRL today announced a way to identify sources of error in quantum computers through machine learning, providing hardware developers the ability to pinpoint ...

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