Berkeley Lab Computing Sciences
of Energy national user facilities — NERSC & ESnet — as well as conducts research in computer science, computational science and applied math to achieve transformational breakthroughs in science. Berkeley Lab's Computing Sciences organization researches, develops, and deploys new tools and technologies to advance research in such areas as global climate change, combustion, fusion energy, nanotechn
02/02/2026
From designing life-saving drugs to building smarter AI, progress often depends on our ability to simulate incredibly complex systems. But these large-scale probabilistic models—specifically a type known as Markov chains—are often a computational bottleneck. Now, researchers at Berkeley Lab have developed a framework that directly addresses this by building a smaller, faster model that operates by the same fundamental rules as the original, ensuring accuracy is never sacrificed for speed.
This method mathematically identifies the core dynamics of a system, creating a compact model that faithfully mirrors the original's long-term behavior and output. This provides equally reliable predictions with significantly faster run-times and improved interpretability, accelerating the entire cycle of simulation, analysis, and discovery.
Learn more: https://bit.ly/MCcompression
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