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Past millimeter-wave galaxy surveys have primarily probed the brightest starburst galaxies only and suffered heavily from confusion. The interpretation of existing surveys has also been hindered by the lack of reliable redshift indicators…
ALBUM is a general-purpose tool to visualize and screen large amounts of slitless spectra. It was developed for a search for emission-line stars in SMC and LMC clusters. The observations were obtained with ESO's Wide Field Imager (WFI) and…
Diffraction-limited radial velocity instruments offer a pathway towards improved precision and stability, and the exploration of new parameter spaces at high spatial and spectral resolution. However, achieving the necessary performance…
There are numerous advantages to exploiting diffraction-limited instrumentation at astronomical observatories, which include smaller footprints, less mechanical and thermal instabilities and high levels of performance. To realize such…
Recent advancements in neural network-based optical flow estimation often come with prohibitively high computational and memory requirements, presenting challenges in their model adaptation for mobile and low-power use cases. In this paper,…
We introduce DyNFL, a novel neural field-based approach for high-fidelity re-simulation of LiDAR scans in dynamic driving scenes. DyNFL processes LiDAR measurements from dynamic environments, accompanied by bounding boxes of moving objects,…
We present the 'simage' software suite for the simulation of artificial extragalactic images, based empirically around real observations of the Hubble Ultra Deep Field (UDF). The simulations reproduce galaxies with realistic and complex…
The emergence of multiparametric diffusion models combining diffusion and relaxometry measurements provide powerful new ways to explore tissue microstructure with the potential to provide new insights into tissue structure and function.…
Light fields (LFs), conducive to comprehensive scene radiance recorded across angular dimensions, find wide applications in 3D reconstruction, virtual reality, and computational photography.However, the LF acquisition is inevitably…
Reconfigurable intelligent surfaces (RISs) are envisioned as a key enabler for next-generation wireless networks, offering programmable control over propagation environments. While extensive research focuses on planar RIS architectures,…
Incoherent Diffraction Imaging - IDI - is a diffraction-based imaging technique that has been recently proposed to exploit the partial coherence of incoherently scattered light to retrieve structural information from the scattering centers.…
This paper explores the application of data-driven system identification techniques in the frequency domain to obtain simplified, control-oriented models of photosynthesis regulation under oscillating light conditions. In-silico datasets…
We present the results of our work on developing fully integrated devices (photonic dicers) for reformatting multimode light to a diffraction limited pseudo-slit. These devices can be used to couple a seeing-limited telescope…
Diffusion and flow-based models have become the de facto approaches for generating continuous data, e.g., in domains such as images and videos. Their success has attracted growing interest in applying them to language modeling. Unlike their…
Accurate spatio-temporal and spatio-spectral metrology is critical to the characterization and use of ultra-short, high-power lasers. The emergence of few cycle pulses, with bandwidths of tens or hundreds of nanometers, poses a significant…
Conventional infrared (IR) imaging techniques depend on IR cameras based on narrow-bandgap semiconductors, which offer limited spectral bandwidth, coupled with a separate lens. Recently, advances in nonlinear flat optics have opened a novel…
In this work, we present a methodology and a corresponding code-base for constructing mock integral field spectrograph (IFS) observations of simulated galaxies in a consistent and reproducible way. Such methods are necessary to improve the…
Creating responsible artificial intelligence (AI) systems is an important issue in contemporary research and development of works on AI. One of the characteristics of responsible AI systems is their explainability. In the paper, we are…
Observations of extrasolar planets using Integral Field Spectroscopy (IFS), if coupled with an extreme Adaptive Optics system and analyzed with a Simultaneous Differential Imaging technique (SDI), are a powerful tool to detect and…
We present a Deep Differentiable Simplex Layer (DDSL) for neural networks for geometric deep learning. The DDSL is a differentiable layer compatible with deep neural networks for bridging simplex mesh-based geometry representations (point…