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Somnath Paramanick

Publications and source records attributed to Somnath Paramanick.

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Spontaneous Emergence of Run-and-Tumble-Like Dynamics in a Robotic Analog of \textit{Chlamydomonas}: Experiment and Theory

Run-and-tumble (RT) motion is commonly observed in flagellated microswimmers, arising from synchronous and asynchronous flagellar beating. One such example is a biflagellated alga, called \textit{Chlamydomonas reinhardtii}. Its flagellar synchronization is not only affected by hydrodynamic interactions but also through contractile stress fibers that mechanically couple the flagella, enabling adaptable swimming behavior. To explore this, we design a macroscopic mechanical system that comprises dry, self-propelled robots linked by a rigid rod to model this organism. By varying the attachment points of the two ends of the rod on each robot, the model incorporates the effect of fiber contractility observed in the real organism. To mimic a low Reynolds number environment, we program each robot to undergo overdamped active Brownian (AB) motion. We find that such a system exhibits RT-like behavior, characterized by sharp, direction-reversing tumbles and exponentially distributed run times, consistent with the real organism. Moreover, we quantify tumbling frequency and demonstrate its tunability across experimental parameters. Additionally, we provide a theoretical model that reproduces our results, elucidating physical mechanisms governing RT dynamics. Thus, our robotic system not only replicates RT motion but also captures several subtle characteristics, offering valuable insights into the underlying physics of microswimmer motility.

cond-mat.soft

Programming tunable active dynamics in a self-propelled robot

We present a scheme for producing tunable active dynamics in a self-propelled robotic device. The robot moves using the differential drive mechanism where two wheels can vary their instantaneous velocities independently. These velocities are calculated by equating robot's equations of motion in two dimensions with well-established active particle models and encoded into the robot's microcontroller. We demonstrate that the robot can depict active Brownian, run and tumble, and Brownian dynamics with a wide range of parameters. The resulting motion analyzed using particle tracking shows excellent agreement with the theoretically predicted trajectories. Finally, we demonstrate that its motion can be switched between different dynamics using light intensity as an external parameter. This work opens an avenue for designing tunable active systems with the potential of revealing the physics of active matter and its application for bio- and nature-inspired robotics.

cond-mat.soft