Unlocking Nature's Secrets: How Algorithms Predict Physical Phenomena 🔍
Explore how computational algorithms reveal universal patterns in nature and improve our ability to predict complex physical systems, based on Nigel Goldenfeld's insights.

Institute for Advanced Study
756 views • Aug 30, 2016

About this video
Nigel Goldenfeld
University of Illinois at Urbana-Champaign
December 1, 2010
Can we use computational algorithms to make accurate predictions of physical phenomena? In this talk, intended for non-experts, I will give examples where complicated space-time phenomena can be exquisitely captured with simple computational algorithms, that not only produce patterns resembling those seen in experiment, but also make accurate predictions about probes of dynamics and spatial organisation, such as correlation functions. I use examples from condensed matter physics, as well as from geophysics.
Because many patterns involve structure on multiple length and time scales, I also discuss how one can develop multiscale methods for real materials processing from the nanoscale on up. I show that a computationally-efficient multiscale approach can be developed systematically by using renormalization group or equivalent techniques to derive appropriate coupled phase and amplitude equations, which can then be solved by adaptive mesh refinement algorithms.
For more videos, visit http://video.ias.edu
University of Illinois at Urbana-Champaign
December 1, 2010
Can we use computational algorithms to make accurate predictions of physical phenomena? In this talk, intended for non-experts, I will give examples where complicated space-time phenomena can be exquisitely captured with simple computational algorithms, that not only produce patterns resembling those seen in experiment, but also make accurate predictions about probes of dynamics and spatial organisation, such as correlation functions. I use examples from condensed matter physics, as well as from geophysics.
Because many patterns involve structure on multiple length and time scales, I also discuss how one can develop multiscale methods for real materials processing from the nanoscale on up. I show that a computationally-efficient multiscale approach can be developed systematically by using renormalization group or equivalent techniques to derive appropriate coupled phase and amplitude equations, which can then be solved by adaptive mesh refinement algorithms.
For more videos, visit http://video.ias.edu
Video Information
Views
756
Likes
17
Duration
01:02:20
Published
Aug 30, 2016
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