AI Breakthroughs
TrajCast skips forces so molecular sims take bigger time steps
By Arjun
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11 Aug 12:10 AM
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Via Nature Machine Intelligence
IBM researchers published TrajCast in Nature Machine Intelligence, an autoregressive equivariant network that updates atomic positions and velocities without computing forces at tiny steps. Across a small molecule, crystalline quartz, and liquid water, it matched reference molecular dynamics on structure, dynamics, and energy while allowing forecast intervals up to about 30 times larger than classical time steps. Reported runs generated more than 15 nanoseconds of trajectory per day for a solid with over 4,000 atoms. That matters for materials discovery stuck behind femtosecond ceilings. Caveat: it still needs careful validation before replacing force-based MD across chemistry regimes.
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