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Data-driven geometric phase in biological locomotion
adaptation-and-self-organizing-systemsbiological-physicscell-behaviordata-analysissoft-condensed-matterstatistics-and-probability
Geometric phase quantifies net locomotion in dissipative media via gauge theory, but linking this theoretical quantity to noisy, sparse, and weakly periodic biological shape data is challenging. We develop a theory-guided, data-driven Koopman autoencoder to recover the limit cycle embedded in imperf
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