Unlocking the full potential of Auger electron spectroscopy

Auger electron spectroscopy (AES) is an incredibly useful technique for probing material samples—but current assumptions about the process ignore some of the key time-dependent effects it involves. So far, this has resulted ...

AI model directly compares properties of potential new drugs

Biomedical engineers at Duke University have developed an AI platform that autonomously compares molecules and learns from their variations to anticipate property differences critical to discovering new pharmaceuticals. The ...

A 'gold standard' for computational materials science codes

For the past few decades, physicists and materials scientists around the world have been busy developing computer codes that simulate the key properties of materials, and they can now choose from a whole family of such tools, ...

Machine learning provides a clearer window into ocean motion

Oceanographers use satellites to peer down at Earth and measure the elevation of the ocean's surface. This information can help them map the circulation of the ocean's currents and understand the role this movement plays ...

Exploring parameter shift for quantum Fisher information

In a recent publication in EPJ Quantum Technology, Le Bin Ho from Tohoku University's Frontier Institute for Interdisciplinary Sciences has developed a technique called time-dependent stochastic parameter shift in the realm ...

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