Title:
Sloppy models, differential geometry, and why science works
Sloppy models, differential geometry, and why science works
| dc.contributor.author | Sethna, James P. | |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Physics | en_US |
| dc.contributor.corporatename | Cornell University. Dept. of Physics | en_US |
| dc.date.accessioned | 2020-10-05T16:32:55Z | |
| dc.date.available | 2020-10-05T16:32:55Z | |
| dc.date.issued | 2020-09-28 | |
| dc.description | Presented online on September 28, 2020 at 3:00 p.m. | en_US |
| dc.description | James Sethna is a Professor of Physics at Cornell University. He has recently been interested how multiparameter models in many fields of physics (from systems biology to cosmology) have collective behavior which depends only loosely on their parameters; these sloppy models work in some ways for the same reasons that underlie continuum limits and the renormalization group. | en_US |
| dc.description | Runtime: 61:49 minutes | en_US |
| dc.description.abstract | Models of systems biology, climate change, ecology, complex instruments, and macroeconomics have parameters that are hard or impossible to measure directly. If we fit these unknown parameters, fiddling with them until they agree with past experiments, how much can we trust their predictions? We have found that predictions can be made despite huge uncertainties in the parameters – many parameter combinations are mostly unimportant to the collective behavior. We will use ideas and methods from differential geometry and approximation theory to explain sloppiness as a ‘hyperribbon’ structure of the manifold of possible model predictions. We show that physics theories are also sloppy – that sloppiness may be the underlying reason why the world is comprehensible. We will present new methods for visualizing this model manifold for probabilistic systems – such as the space of possible universes as measured by the cosmic microwave background radiation. | en_US |
| dc.format.extent | 61:49 minutes | |
| dc.identifier.uri | http://hdl.handle.net/1853/63772 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.relation.ispartofseries | Physics Colloquium | |
| dc.subject | Data visualization | en_US |
| dc.subject | Information geometry | en_US |
| dc.subject | Statistics | en_US |
| dc.title | Sloppy models, differential geometry, and why science works | en_US |
| dc.type | Moving Image | |
| dc.type.genre | Lecture | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | College of Sciences | |
| local.contributor.corporatename | School of Physics | |
| local.relation.ispartofseries | Physics Colloquium | |
| relation.isOrgUnitOfPublication | 85042be6-2d68-4e07-b384-e1f908fae48a | |
| relation.isOrgUnitOfPublication | 2ba39017-11f1-40f4-9bc5-66f17b8f1539 | |
| relation.isSeriesOfPublication | 5fcf4984-0912-45ae-91c5-2c6de98772b0 |
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