Quantitative Phase Imaging is the method of choice to observe unlabelled biological cells, enabling the exploration of their intricate structures and dynamics. Differential Phase Contrast (DPC) is a fast and flexible approach but is limited to brightfield measurements, which limits the achievable resolution. In this study, we revisit DPC as a perturbative approach for high-resolution phase imaging with a minimal number of images. Our methodology combines both a perturbative phase retrieval algorithm and ring-shaped darkfield illumination patterns. The proposed approach leverages the advantages of DPC, such as its minimal image requirement, while addressing its inability to extend to darkfield imaging. By reducing the number of acquired images, our technique offers a rapid solution for examining dynamic systems.
Phase imaging is a widely used tool in biology with clinical applications. Various phase sensitive imaging techniques exist, ranging from phase contrast microscopy to quantitative schemes such as spatial light interference microscopy and off-axis holography. Here, we discuss these techniques in terms of the Fisher information content they provide, and the resulting Cramer Rao bounds of phase measurement accuracy [1]. We introduce the theoretical framework assuming that shot-noise is the dominant source of noise, and deduce the necessary conditions required to perform optimal phase estimations. This approach brings insights to design maximally sensitive microscopes for photon-limited applications, such as high-speed measurements, or the imaging of ultra-cold atoms or fragile biostructures. We further discuss how local wavefront shaping, adapted to the sample under study, can maximize Fisher information and enable optimal phase estimations [1,2]. We observe the largest improvement when imaging thick samples and demonstrate it experimentally. [1] Fundamental bounds on the precision of classical phase microscopes, D. Bouchet, D. Maestre, J. Dong, and T. Juffmann, https://arxiv.org/abs/2011.04799 [2] Local Optimization of Wave-fronts for optimal sensitivity PHase Imaging (LowPhi), T. Juffmann, A. de los Ríos Sommer & S. Gigan, Opt. Commun., 454, 124484 (2020), DOI: 10.1016/j.optcom.2019.124484
Combining synthetic aperture approaches with reference-less setups, ptychography is a promising phase retrieval technique for label-free quantitative phase imaging. Within the phase retrieval community, spectral methods are known to accelerate gradient descent schemes, however their positive effect on experimental ptychographic datasets has not been proved.
Inspired by the latest theories on optimal spectral estimation, we achieved 3 times faster ptychographic reconstructions than with a standard gradient descent algorithm, in both simulations and experiments. The algorithms and experimental parameters crucially impacting the convergence speed are discussed.
We believe that spectral methods will help improve both theoretical understanding and experimental implementations of ptychography.
There have been a number of rapid advances in the prediction of the dynamics of chaotic systems using a technique known as Reservoir Computing. These techniques are mostly not effective for large networks, as the complexity of the task increases quadratically both in time and memory. We report new advances in Optical Reservoir Computing using multiple light scattering to accelerate the recursive computation of the reservoir states. Different approaches to information encoding based on phase or amplitude spatial light modulations are compared. We demonstrate the scalability and the good prediction performance of our approach using the Kuramoto-Sivashinsky equation as an example of a spatiotemporally chaotic system.
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