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SUMMARY:Sloppy models\, differential geometry\, and why science works
DTSTART:20241111T161500
DTEND:20241111T171500
DTSTAMP:20260509T055154Z
UID:a06d3f4315409436a54f0bc821d796cdeff78bd35b4e34be1aa95ec2
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. James Sethna\, Cornell University\nModels of systems bi
 ology\, climate change\, ecology\, complex instruments\, and macroeconomic
 s have parameters that are hard or impossible to measure directly. If we f
 it these unknown parameters\, fiddling with them until they agree with pas
 t experiments\, how much can we trust their predictions? We have found tha
 t predictions can be made despite huge uncertainties in the parameters –
  many parameter combinations are mostly unimportant to the collective beha
 vior. We will use ideas and methods from differential geometry and approxi
 mation theory to explain sloppiness as a ‘hyperribbon’ structure of th
 e manifold of possible model predictions. We show that physics theories ar
 e also sloppy – that sloppiness may be the underlying reason why the wor
 ld is comprehensible. We will describe how to use these hyperribbon to sys
 tematically coarse-grain complex systems into human-comprehensible form. W
 e will present new methods for visualizing this model manifold for probabi
 listic systems – such as the space of possible universes as measured by 
 the cosmic microwave background radiation.
LOCATION:CE 1 2 https://plan.epfl.ch/?room==CE%201%202
STATUS:CONFIRMED
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