Improving holographic particle characterization by modeling spherical aberration

TL;DR

This paper demonstrates that incorporating spherical aberration into holographic microscopy models significantly improves the accuracy and robustness of 3D colloidal particle characterization, reducing systematic errors caused by optical aberrations.

Contribution

The authors develop a new generative model that accounts for spherical aberration, enhancing the precision of holographic particle measurements under varying optical conditions.

Findings

Spherical aberration causes about 2% systematic errors in inferred particle parameters.

Modeling spherical aberration reduces errors by over 50%.

Inferred parameters become consistent across different aberration levels.

Abstract

Holographic microscopy combined with forward modeling and inference allows colloidal particles to be characterized and tracked in three dimensions with high precision. However, current models ignore the effects of optical aberrations on hologram formation. We investigate the effects of spherical aberration on the structure of single-particle holograms and on the accuracy of particle characterization. We find that in a typical experimental setup, spherical aberration can result in systematic shifts of about 2% in the inferred refractive index and radius. We show that fitting with a model that accounts for spherical aberration decreases this aberration-dependent error by a factor of two or more, even when the level of spherical aberration in the optical train is unknown. With the new generative model, the inferred parameters are consistent across different levels of aberration, making particle characterization more robust.