Quantum computers—systems that process information and perform computations by leveraging the principles of quantum mechanics—could solve some tasks faster and more effectively than classical computers. While some studies have demonstrated the advantages of these computers for specific tasks, ensuring their reliable operation in real-world settings has proved challenging.

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A study in the Journal of Cosmology and Astroparticle Physics explores how a machine-learning strategy known as transfer learning could dramatically reduce the computational cost of searching for new physics beyond the standard cosmological model—while also revealing an unexpected risk: Sometimes AI systems can become too reliant on what they already know.

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How are heavy elements formed in the universe? Extremely neutron-rich atomic nuclei and their beta-decay rates play an important role in this process. Until now, it has been very difficult to determine these rates experimentally. Researchers at TU Darmstadt have developed theoretical predictions for such processes and successfully compared them with experimental data, where they […]

How do you take measurements using one of the most sensitive scales in the world? Researchers at TU Wien have demonstrated how the measurement process affects not only the object being measured but also the scale itself, and where the absolute limits of precision lie.

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Researchers at Kanazawa University, in collaboration with Diamond and Carbon Applications (Germany), have developed a buried-growth process for nitrogen–vacancy (NV) centers in diamond using microwave plasma chemical vapor deposition (MPCVD). By employing nitrogen-radical selective etching, which simultaneously enhances metal-mask durability through nitridation, the team enabled a continuous etching–growth sequence within a single MPCVD process.

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When baseball fans watch a batter strike out with runners in scoring position, the reaction is often immediate: Shorten the swing. Put the ball in play. Stop swinging for the fences, they lament.

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Researchers from the University of Cambridge and GlitterinTech, a startup founded by the same research group, have unveiled a fundamentally new type of optical spectrometer that delivers laboratory-grade precision in a device small enough to be embedded in portable and wearable technologies. By rethinking how spectra are measured and processed, the team has demonstrated a […]

Assistant Professor Haocun Yu is something of a scientific diplomat. In a recent Physical Review Letters publication, she and her colleagues show how a tabletop experiment can bring together two bedrock physics theories that have never been fully reconciled.

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