Optical tweezers calibration with Bayesian inference

We present a new method for calibrating an optical-tweezer setup that is based on Bayesian inference¹. This method employs an algorithm previously used to analyze the confined trajectories of receptors within lipid rafts^2,3. The main advantages of this method are that it does not require input parameters and is insensitive to systematic errors like the drift of the setup. Additionally, it exploits a much larger amount of the information stored in the recorded bead trajectory than standard calibration approaches. The additional information can be used to detect deviations from the perfect harmonic potential or detect environmental influences on the bead. The algorithm infers the diffusion coefficient and the potential felt by a trapped bead, and only requires the bead trajectory as input. We demonstrate that this method outperforms the equipartition method and the power-spectrum method in input information required (bead radius and trajectory length) and in output accuracy. Furthermore, by inferring a higher order potential our method can reveal deviations from the assumed second-order potential. More generally, this method can also be used for magnetic-tweezer calibration.