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model and biological membranes. The experimental data will be paired with results from molecular dynamics simulations to provide a complete characterization of the biophysical properties of the imaged
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dynamical structure directly from time-series data. This includes methodological work on nonlinear state-space reconstruction, system identification, reservoir computing and related recurrent architectures
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narratives to engage with more powerful actors towards transformative change. In addition, this project aims to include the element of ‘surprise’ by engaging with the non-linear dynamics (feedback loops and
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closely related) geometries and dual field theories—to map out the underlying duality structure and to illuminate non-perturbative phenomena with connections to black hole physics and quantum field theory