title: Predicting two-dimensional turbulence.
abstract: Prediction is a fundamental objective of science. It is more difficult for chaotic and complex systems like turbulence. Here we use information theory to quantify spatial prediction using experimental data from a turbulent soap film. At high Reynolds number, Re, where a cascade exists, turbulence becomes easier to predict as the inertial range broadens. The development of a cascade at low Re is also detected.
authors.affiliation: Department of Physics and Astronomy, University of Pittsburgh, 3941 O'Hara Street, Pittsburgh, Pennsylvania 15260, USA.|Fluid Mechanics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa 904-0495, Japan.
authors.forename: R T
authors.initials: RT
authors.lastname: Cerbus
authors.affiliation: Department of Physics and Astronomy, University of Pittsburgh, 3941 O'Hara Street, Pittsburgh, Pennsylvania 15260, USA.
authors.forename: W I
authors.initials: WI
authors.lastname: Goldburg