Optical tweezers calibration with Bayesian inference

Silvan Türkcan; Maximilian U. Richly; Antoine Le Gall; Nicolas Fiszman; Jean-Baptiste Masson; Nathalie Westbrook; Karen Perronet; Antigoni Alexandrou

doi:10.1117/12.2064375

16 September 2014 Optical tweezers calibration with Bayesian inference

Silvan Türkcan, Maximilian U. Richly, Antoine Le Gall, Nicolas Fiszman, Jean-Baptiste Masson, Nathalie Westbrook, Karen Perronet, Antigoni Alexandrou

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Proceedings Volume 9164, Optical Trapping and Optical Micromanipulation XI; 916415 (2014) https://doi.org/10.1117/12.2064375
Event: SPIE NanoScience + Engineering, 2014, San Diego, California, United States

Abstract

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.

Citation Download Citation

Silvan Türkcan, Maximilian U. Richly, Antoine Le Gall, Nicolas Fiszman, Jean-Baptiste Masson, Nathalie Westbrook, Karen Perronet, and Antigoni Alexandrou "Optical tweezers calibration with Bayesian inference", Proc. SPIE 9164, Optical Trapping and Optical Micromanipulation XI, 916415 (16 September 2014); https://doi.org/10.1117/12.2064375

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KEYWORDS

Calibration

Bayesian inference

Optical tweezers

Diffusion

Optical calibration

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