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The photoacoustic tomography (PAT) is a hybrid modality that combines the optics and acoustics to obtain high resolution and high contrast imaging of heterogeneous media. In this work, our objective is to study the inverse problem in the…
Quantum optical photodetection has occupied a central role in understanding radiation-matter interactions. It has also contributed to the development of atomic physics and quantum optics, including applications to metrology, spectroscopy,…
Advances in quantum technologies are accelerating the demand for optical quantum state sensors that combine high precision, versatility, and scalability within a unified hardware platform. Quantum reservoir computing offers a powerful route…
X-ray phase-contrast imaging has recently led to a revolution in resolving power and tissue contrast in biomedical imaging, microscopy and materials science. The necessary high spatial coherence is currently provided by either large-scale…
The retrieval of phases from intensity measurements is a key process in many fields in science, from optical microscopy to x-ray crystallography. Here we study phase retrieval of a one-dimensional multi-phase object that is illuminated by…
Resolving single atoms in large-scale volumes has been a goal for atomic resolution microscopy for a long time. Electron microscopy has come close to this goal using a combination of advanced electron optics and computational imaging…
Quantum Transfer Learning (QTL) recently gained popularity as a hybrid quantum-classical approach for image classification tasks by efficiently combining the feature extraction capabilities of large Convolutional Neural Networks with the…
Dynamic light scattering techniques are routinely used for numerous industrial and research applications, because they can give access to the motion spectrum of micro- and nano-objects, and therefore to particle sizes or visco-elastic…
Accurately predicting enzyme functionality remains one of the major challenges in computational biology, particularly for enzymes with limited structural annotations or sequence homology. We present a novel multimodal Quantum Machine…
We propose a quantum tomography (QT) approach to retrieve the temporally evolving reduced density matrix in elecotronic state basis, where the populations and coherence between ground state and excited state are reconstructed from the…
Three-dimensional molecular imaging of living cells is essential for unraveling cellular metabolism and response to therapies. However, existing volumetric methods, including fluorescence microscopy and quantitative phase imaging, either…
Quantum electrodynamics (QED) provides a highly accurate description of phenomena involving the interaction of atoms with light. We argue that the quantum theory describing the interaction of cold atoms with a vibrating membrane--quantum…
Holotomography (HT) has revolutionized quantitative label-free 3D imaging, yet conventional lens-based implementations are fundamentally constrained in field-of-view (FOV) and imaging depth, limiting their utility for critical…
Light-field imaging is an emerging paradigm in biomedical optics, offering the unique ability to capture volumetric information in a single snapshot by encoding both the spatial and angular components of light. Unlike conventional…
Three-dimensional (3D) imaging of thin, extended specimens at nanometer resolution is critical for applications in biology, materials science, advanced synthesis, and manufacturing. One route to 3D imaging is tomography, which requires a…
Transient absorption is a very powerful observable in attosecond experiments on atoms, molecules and solids and is frequently used in experiments employing phase-locked few-cycle infrared and XUV laser pulses derived from high harmonic…
Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves around primitive…
The field of autonomous vehicles (AVs) predominantly leverages multi-modal integration of LiDAR and camera data to achieve better performance compared to using a single modality. However, the fusion process encounters challenges in…
We present 3DeepCT, a deep neural network for computed tomography, which performs 3D reconstruction of scattering volumes from multi-view images. Our architecture is dictated by the stationary nature of atmospheric cloud fields. The task of…
Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of…