Breakthrough could connect quantum computers at 200X the distance
Peer-Reviewed Publication
Updates every hour. Last Updated: 13-Nov-2025 08:11 ET (13-Nov-2025 13:11 GMT/UTC)
The American Physical Society (APS) – the world’s largest organization of physicists – has awarded the 2026 Aneesur Rahman Prize for Computational Physics to Stefano Baroni, Professor of Condensed Matter Physics at the Scuola Internazionale Superiore di Studi Avanzati (SISSA) and research associate at the Consiglio Nazionale delle Ricerche – Istituto Officina dei Materiali (CNR–IOM). The prize is regarded as the most prestigious international recognition in the field, awarded for outstanding achievements in computational physics.
The official citation recognizes his “seminal contributions to the development of first-principles methods for studying the electronic and thermal properties of condensed systems, and for the development and dissemination of open-source software for electronic-structure calculations, now widely adopted.”
Two formulations are at the heart of the study of turbulence: Kolmogorov’s universal framework for small-scale turbulence, which describes how energy propagates and dissipates through increasingly small eddies; and Taylor-Couette (TC) flows, which are very simple to create yet exhibit extremely complex behaviors, thereby setting the benchmark for the study of the fundamental characteristics of complex flows.
For the past many decades, a central contradiction between these potent formulations has plagued the field. Despite extensive experimental research and despite being found universal to almost all turbulent flows, Kolmogorov’s framework has apparently failed to apply to turbulent TC flows.
But now, after nine years developing a world-class TC setup at the Okinawa Institute of Science and Technology (OIST), researchers have finally resolved this tension by conclusively demonstrating that, contrary to the prevailing understanding, Kolmogorov’s framework does apply universally to the small scales of turbulent TC flows – precisely as predicted.
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