Reinforcement learning of a biflagellate model microswimmer

Many microswimmers are able to swim through viscous fluids by employing periodic non-reciprocal deformations of their appendages. Here we use a simple microswimmer model inspired by swimming biflagellates which consists of a spherical cell body and two small spherical beads representing the motion of the two flagella. Using reinforcement learning, we identify for different microswimmer morphologies quasi-optimized swimming strokes. For all studied cases, the identified strokes result in symmetric and quasi-synchronized beating of the two flagella beads. Interestingly, the stroke-averaged flow fields are of pusher type, and the observed swimming gaits outperform previously used biflagellate microswimmer models relying on predefined circular flagella-bead motion.

• Publication year

  2025

• Venue

  The European Physical Journal E : Soft matter

• Publication date

  2025-08-13

• Fields of study

  Medicine, Physics, Computer Science

• Identifiers
  DOI 10.1140/epje/s10189-025-00513-3arXiv 2508.15561PMID 40804567PMCID 12350500
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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