2012/08/06 by Matthias Grimm, Thomas Franosch, Sylvia Jeney · 67 citations
Engineering · Mathematics · Physics and Astronomy · #Autocorrelation #Brownian motion #Classical mechanics #Computational physics #Displacement (psychology) #Electrowetting and Microfluidic Technologies #Mathematics #Mean squared displacement #Microfluidic and Bio-sensing Technologies #Optical tweezers #Optics #Orbital Angular Momentum in Optics #Physics #Position (finance) #Quantum mechanics #Statistical physics #Statistics #cond-mat.soft #physics.bio-ph
paper · pdf · doi:10.1103/physreve.86.021912
published in Physical Review E 86(2), 021912 (American Physical Society)
arxiv created 2012/08/06 · openalex publication_date 2012/08/13 · arxiv updated 2012/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We have developed an in situ method to calibrate optical tweezers experiments and simultaneously measure the size of the trapped particle or the viscosity of the surrounding fluid. The positional fluctuations of the trapped particle are recorded with a high-bandwidth photodetector. We compute the mean-square displacement, as well as the velocity autocorrelation function of the sphere, and compare it to the theory of Brownian motion including hydrodynamic memory effects. A careful measurement and analysis of the time scales characterizing the dynamics of the harmonically bound sphere fluctuating in a viscous medium directly yields all relevant parameters. Finally, we test the method for different optical trap strengths, with different bead sizes and in different fluids, and we find excellent agreement with the values provided by the manufacturers. The proposed approach overcomes the most commonly encountered limitations in precision when analyzing the power spectrum of position fluctuations in the region around the corner frequency. These low frequencies are usually prone to errors due to drift, limitations in the detection, and trap linearity as well as short acquisition times resulting in poor statistics. Furthermore, the strategy can be generalized to Brownian motion in more complex environments, provided the adequate theories are available.