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CATEGORIES:Colloquia / Seminar / Lecture
DESCRIPTION:The problems of causality\, modeling\, and control for chaotic\
, high-dimensional dynamical systems are formulated in the language of info
rmation theory. The central quantity of interest is the Shannon entropy\, w
hich measures the amount of information in the states of the system. Within
this framework\, causality in the dynamical system is quantified by the in
formation flux among the variables of interest. Reduced-order modeling is p
osed as a problem on the conservation of information\, in which models aim
at preserving the maximum amount of relevant information from the original
system. Similarly\, control theory is cast in information-theoretic terms b
y envisioning the tandem sensor-actuator as a device reducing the unknown i
nformation of the state to be controlled. The new formulation is applied to
address three problems in the causality\, modeling\, and control of turbul
ence\, which stands as a primary example of a chaotic\, high dimensional dy
namical system. The applications include the causality of the energy transf
er in the turbulent cascade\, subgrid-scale modeling for large-eddy simulat
ion\, and flow control for drag reduction in wall-bounded turbulence.
DTEND:20230309T210000Z
DTSTAMP:20240524T052250Z
DTSTART:20230309T200000Z
GEO:42.378796;-71.117354
LOCATION:Maxwell Dworkin\, G125
SEQUENCE:0
SUMMARY:Information-theoretic formulation of chaotic systems: causality\, m
odeling and control
UID:tag:localist.com\,2008:EventInstance_42226317970411
URL:https://events.seas.harvard.edu/event/information-theoretic_formulation
_of_chaotic_systems_causality_modeling_and_control
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