arXiv subjects

YoonSeok Baek

Publications and source records attributed to YoonSeok Baek.

9 recordsLinked to original sources

arXiv2025

Optical Computing with Spectrally Multiplexed Features in Complex Media

Artificial intelligence (AI) has rapidly evolved into a critical technology; however, electrical hardware struggles to keep pace with the exponential growth of AI models. Free space optical hardware provides alternative approaches for large-scale optical processing, and in-memory computing, with applications across diverse machine learning tasks. Here, we explore the use of broadband light scattering in free-space optical components, specifically complex media, which generate uncorrelated optical features at each wavelength. By treating individual wavelengths as independent predictors, we demonstrate improved classification accuracy through in-silico majority voting, along with the ability to estimate uncertainty without requiring access to the model's probability outputs. We further demonstrate that linearly combining multiwavelength features, akin to spectral shaping, enables us to tune output features with improved performance on classification tasks, potentially eliminating the need for multiple digital post-processing steps. These findings illustrate the spectral multiplexing or broadband advantage for free-space optical computing.

physics.optics↗

arXiv2025

Three-dimensional holographic imaging of incoherent objects through scattering media

Three-dimensional (3D) high-resolution imaging is essential in microscopy, yet light scattering poses significant challenges in achieving it. Here, we present an approach to holographic imaging of spatially incoherent objects through scattering media, utilizing a virtual medium that replicates the scattering effects of the actual medium. This medium is constructed by retrieving mutually incoherent fields from the object, and exploiting the spatial correlations between them. By numerically propagating the incoherent fields through the virtual medium, we non-invasively compensate for scattering, achieving accurate 3D reconstructions of hidden objects. Experimental validation with fluorescent and synthetic incoherent objects confirms the effectiveness of this approach, opening new possibilities for advanced 3D high-resolution microscopy in scattering environments.

physics.optics↗

arXiv2024

Optical next generation reservoir computing

Artificial neural networks with internal dynamics exhibit remarkable capability in processing information. Reservoir computing (RC) is a canonical example that features rich computing expressivity and compatibility with physical implementations for enhanced efficiency. Recently, a new RC paradigm known as next generation reservoir computing (NGRC) further improves expressivity but compromises its physical openness, posing challenges for realizations in physical systems. Here we demonstrate optical NGRC with computations performed by light scattering through disordered media. In contrast to conventional optical RC implementations, we drive our optical reservoir directly with time-delayed inputs. Much like digital NGRC that relies on polynomial features of delayed inputs, our optical reservoir also implicitly generates these polynomial features for desired functionalities. By leveraging the domain knowledge of the reservoir inputs, we show that the optical NGRC not only predicts the short-term dynamics of the low-dimensional Lorenz63 and large-scale Kuramoto-Sivashinsky chaotic time series, but also replicates their long-term ergodic properties. Optical NGRC shows superiority in shorter training length, increased interpretability and fewer hyperparameters compared to conventional optical RC based on scattering media, while achieving better forecasting performance. Our optical NGRC framework may inspire the realization of NGRC in other physical RC systems, new applications beyond time-series processing, and the development of deep and parallel architectures broadly.

physics.optics↗

arXiv2024

Replica-assisted super-resolution fluorescence imaging in scattering media

Far-field super-resolution fluorescence microscopy has been rapidly developed for applications ranging from cell biology to nanomaterials. However, it remains a significant challenge to achieve super-resolution imaging at depth in opaque materials. In this study, we present a super-resolution microscopy technique for imaging hidden fluorescent objects through scattering media, started by exploiting the inherent object replica generation arising from the memory effect, i.e. the seemingly informationless emission speckle can be regarded as a random superposition of multiple object copies. Inspired by the concept of super-resolution optical fluctuation imaging, we use temporally-fluctuating speckles to excite fluorescent signals and perform high-order cumulant analysis on the fluctuation, which can not only improve the image resolution, but also increase the speckle contrast to isolate only the bright object replicas. A super-resolved image can be finally retrieved by simply unmixing the sparsely distributed replicas with their location map. This methodology allows to overcome scattering and achieve robust super-resolution fluorescence imaging, circumventing the need of heavy computational steps.

physics.optics↗

arXiv2023

Phase conjugation with spatially incoherent light in complex media

Shaping light deep inside complex media, such as biological tissue, is critical to many research fields. Although the coherent control of scattered light via wavefront shaping has made significant advances in addressing this challenge, controlling light over extended or multiple targets without physical access inside a medium remains elusive. Here we present a phase conjugation method for spatially incoherent light, which enables the non-invasive light control based on incoherent emission from multiple target positions. Our method characterizes the scattering responses of hidden sources by retrieving mutually incoherent scattered fields from speckle patterns. By time-reversing scattered fluorescence with digital phase conjugation, we experimentally demonstrate focusing of light on individual and multiple targets. We also demonstrate maximum energy delivery to an extended target through a scattering medium by exploiting transmission eigenchannels. This paves the way to control light propagation in complex media using incoherent contrasts mechanisms.

physics.optics↗

arXiv2020

DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging using Deep Learning

Optical diffraction tomography measures the three-dimensional refractive index map of a specimen and visualizes biochemical phenomena at the nanoscale in a non-destructive manner. One major drawback of optical diffraction tomography is poor axial resolution due to limited access to the three-dimensional optical transfer function. This missing cone problem has been addressed through regularization algorithms that use a priori information, such as non-negativity and sample smoothness. However, the iterative nature of these algorithms and their parameter dependency make real-time visualization impossible. In this article, we propose and experimentally demonstrate a deep neural network, which we term DeepRegularizer, that rapidly improves the resolution of a three-dimensional refractive index map. Trained with pairs of datasets (a raw refractive index tomogram and a resolution-enhanced refractive index tomogram via the iterative total variation algorithm), the three-dimensional U-net-based convolutional neural network learns a transformation between the two tomogram domains. The feasibility and generalizability of our network are demonstrated using bacterial cells and a human leukaemic cell line, and by validating the model across different samples. DeepRegularizer offers more than an order of magnitude faster regularization performance compared to the conventional iterative method. We envision that the proposed data-driven approach can bypass the high time complexity of various image reconstructions in other imaging modalities.

eess.IV↗

arXiv2019

Reference-Free Single-Point Holographic Imaging and Realization of an Optical Bidirectional Transducer

One of the fundamental limitations in photonics is the lack of a bidirectional transducer that can convert optical information into electronic signals or vice versa. In acoustics or at microwave frequencies, wave signals can be simultaneously measured and modulated by a single transducer. In optics, however, optical fields are generally measured via reference-based interferometry or holography using silicone-based image sensors, whereas they are modulated using spatial light modulators. Here, we propose a scheme for an optical bidirectional transducer using a spatial light modulator. By exploiting the principle of time-reversal symmetry of light scattering, two-dimensional reference-free measurement and modulation of optical fields are realized. We experimentally demonstrate the optical bidirectional transducer for optical information consisting of 128 x 128 spatial modes at visible and short-wave infrared wavelengths.

physics.optics↗

arXiv2018

High-resolution long-working-distance reference-free holographic microscopy exploiting speckle-correlation scattering matrix

Using conventional refraction-based optical lens, it is challenging to achieve both high-resolution imaging and long-working-distance condition. To increase the numerical aperture of a lens, the working distance should be compensated, and vice versa. Here we propose and demonstrate a new concept in optical microscopy that can achieve both high-resolution imaging and long-working-distance conditions by utilising a scattering layer instead of refractive optics. When light passes through a scattering layer, it creates a unique interference pattern. To retrieve the complex amplitude image from the interference pattern without introducing a reference beam, we utilised a speckle-correlation scattering matrix method. This property enables holographic microscopy without any lens or external reference beam. Importantly, the proposed method allows high-resolution imaging with a long working distance beyond what a conventional objective lens can achieve. As an experimental verification, we imaged various microscopic samples and compared their performance with off-axis digital holographic microscopy.

physics.optics↗

arXiv2016

White-light Quantitative Phase Imaging Unit

We introduce the white light quantitative phase imaging unit (WQPIU) as a practical realization of quantitative phase imaging (QPI) on standard microscope platforms. The WQPIU is a compact stand-alone unit which measures sample induced phase delay under white-light illumination. It does not require any modification of the microscope or additional accessories for its use. The principle of the WQPIU based on lateral shearing interferometry and phase shifting interferometry provides a cost-effective and user-friendly use of QPI. The validity and capacity of the presented method are demonstrated by measuring quantitative phase images of polystyrene beads, human red blood cells, HeLa cells and mouse white blood cells. With speckle-free imaging capability due to the use of white-light illumination, the WQPIU is expected to expand the scope of QPI in biological sciences as a powerful but simple imaging tool.

physics.optics↗