This PDF file contains the front matter associated with SPIE Proceedings Volume 11969, including the Title Page, Copyright information, and Table of Contents.

For sufficiently wide ranges of applied control signals (control voltages), MEMS and piezoelectric Deformable Mirrors (DMs), exhibit nonlinear behavior. The nonlinear behavior manifests itself in nonlinear actuator couplings, nonlinear actuator deformation characteristics, and in the case of piezoelectric DMs, hysteresis. Furthermore, in a number of situations, DM behavior can change over time, and this requires a procedure for updating the DM models on the basis of the observed data. If not properly modeled and if not taken into account when designing control algorithms, nonlinearities, and time-varying DM behavior, can significantly degrade the achievable closed-loop performance of Adaptive Optics (AO) systems. Widely used approaches for DM control are based on pre-estimated linear time-invariant DM models in the form of influence matrices. Often, these models are not being updated during system operation. Consequently, when nonlinear DM behavior is being excited by control signals with wide operating ranges, or when the DM behavior changes over time, the state-of-the-art DM control approaches relying upon linear control methods, might not be able to produce a satisfactory closed-loop performance of an AO system. Motivated by these key facts, we present a novel method for data-driven DM control. Our approach combines a simple open-loop control method with a recursive least squares method for dynamically updating the DM model. The DM model is constantly being updated on the basis of the dynamically changing DM operating points. That is, the proposed method updates both the control actions and the DM model during the system operation. We experimentally verify this approach on a Boston Micromachines MEMS DM with 140 actuators. Preliminary experimental results reported in this manuscript demonstrate good potential for using the developed method for DM control.

Microscopy through inhomogeneous media distorts the wavefront of the transmitted light and results in the loss of resolution and contrast. This wavefront distortion may be compensated by the use of adaptive optics (AO). The state-of-the-art AO systems for commercial microscopes generally use deformable mirrors for wavefront modulation, which are difficult to integrate as they require the use of folded imaging paths. Herein, we present a compact and miniaturized AO ’add-on’ that fits between an objective and the turret as a simpler ’plug-and-play’ alternative. The AO add-on features a deformable phase plate - a transmissive, optofluidic wavefront modulator that is capable of wavefront correction up to 7th radial Zernike modes within a clear aperture of 10 mm, and open-loop control based-on sensorless wavefront estimation.

Adaptive optics (AO) normally concerns the feedback correction of phase aberrations. Such correction has been of benefit in various optical systems, with applications ranging in scale from astronomical telescopes to super-resolution microscopes. Here we extend this powerful tool into the vectorial domain, encompassing feedback correction of both polarisation and phase. This technique is termed vectorial adaptive optics (V-AO). We show that V-AO can be implemented using sensor feedback, where an imaging polarimeter is used as the analog to the wavefront sensor used in phase AO. Alternatively, correction can be performed indirectly using so-called “sensorless” AO, which for phase AO does not employ a wavefront sensor but uses indirect optimization of the optical performance. Sensorless V-AO takes a similar approach optimizing the vectorial state through indirect optimization in the focal plane. An intermediate quasi-sensorless V-AO method is also shown. We validate improvements in both vector field state and the focal quality of an optical system, through correction for commonplace vectorial aberration sources, ranging from objective lenses to biological samples. This technique pushes the boundaries of traditional scalar beam shaping with feedback by providing control of extra vectorial degrees of freedom, which also paves the way for next generation AO functionality by manipulating the complex vectorial field.