Abstract
Feedback traps use closed-loop control to trap or manipulate small particles and molecules in solution. They have been applied to the measurement of physical and chemical properties of particles and to explore fundamental questions in the non-equilibrium statistical mechanics of small systems. These applications have been hampered by drifts in the electric forces used to manipulate the particles. Although the drifts are small for measurements on the order of seconds, they dominate on time scales of minutes or slower. Here, we show that a recursive maximum likelihood (RML) algorithm can allow real-time measurement and control of electric and stochastic forces over time scales of hours. Simulations show that the RML algorithm recovers known parameters accurately. Experimental estimates of diffusion coefficients are also consistent with expected physical properties.
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Notes
- 1.
The drag \(\gamma \) is also referred as the friction coefficient in the literature [10].
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Gavrilov, M. (2017). Real-Time Calibration of a Feedback Trap. In: Experiments on the Thermodynamics of Information Processing. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-63694-8_3
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