Related papers: TIPTOP: cone effect for single laser adaptive opti…
Most convolutional neural networks (CNNs) for image classification use a global average pooling (GAP) followed by a fully-connected (FC) layer for output logits. However, this spatial aggregation procedure inherently restricts the…
The point spread function (PSF) is fundamental to any type of microscopy, most importantly so for single-molecule localization techniques, where the exact PSF shape is crucial for precise molecule localization at the nanoscale. However,…
The Laser Guide Star Facility for the VLT will be commissioned during 2003. This, of course, can only be the first step towards enhancing the scientific output of the VLT through adaptive optics. So in this contribution we propose the…
Diffusion models are generative models with impressive text-to-image synthesis capabilities and have spurred a new wave of creative methods for classical machine learning tasks. However, the best way to harness the perceptual knowledge of…
Object detection has gained great progress driven by the development of deep learning. Compared with a widely studied task -- classification, generally speaking, object detection even need one or two orders of magnitude more FLOPs (floating…
In this paper, we report the first experimental demonstration of a Temporal HyperTelescope (THT). Our breadboard including 8 telescopes is firstly tested in a manual cophasing configuration on a 1D object. The Point Spread Function (PSF) is…
A ground-layer adaptive optics system (GLAO) uses a single adaptive mirror to partially correct the wavefront for atmospheric and telescope aberrations over a wide field of view. Instead of reaching diffraction limit on a narrow field, the…
Q-LET is a FORTRAN 77 code that enables a quick estimate of the gravitational lensing effects on a point- or an extended source. The user provided input consists of the redshifts, angular positions relative to the source, mass or velocity…
In the context of the GRAVITY+ upgrade, the adaptive optics (AO) systems of the GRAVITY interferometer are undergoing a major lifting. The current CILAS deformable mirrors (DM, 90 actuators) will be replaced by ALPAO kilo-DMs (43x43, 1432…
Anytime neural networks (AnytimeNNs) are a promising solution to adaptively adjust the model complexity at runtime under various hardware resource constraints. However, the manually-designed AnytimeNNs are biased by designers' prior…
This paper introduces an adaptive convolutional neural network (CNN) architecture capable of automating various topology optimization (TO) problems with diverse underlying physics. The proposed architecture has an encoder-decoder-type…
We present a new matched filter algorithm for direct detection of point sources in the immediate vicinity of bright stars. The stellar Point Spread Function (PSF) is first subtracted using a Karhunen-Lo\'eve Image Processing (KLIP)…
We developed a 2D Finite-Difference Time-Domain (FDTD) method for modeling a space-time modulated guidestar targeting wavefront shaping applications in disordered media. Space-time modulation in general (a particular example being the…
lightcurver is a photometric pipeline for time series astronomical imaging data, designed for the semi-automatic extraction of precise light curves from small, blended targets. Such targets include, but are not limited to, lensed quasars,…
Both lucky imaging techniques and adaptive optics require natural guide stars, limiting sky coverage, even when laser guide stars are used. Lucky imaging techniques become less successful on larger telescopes unless adaptive optics is used,…
Access to knowledge of the point spread function (PSF) of adaptive optics(AO)-assisted observations is still a major limitation when processing AO data. This limitation is particularly important when image analysis requires the use of…
Dataset condensation is a newborn technique that generates a small dataset that can be used in training deep neural networks to lower training costs. The objective of dataset condensation is to ensure that the model trained with the…
With the Extremely Large Telescope-generation telescopes come new challenges. The complexity of these telescopes' pupil creates new problems for Adaptive Optics. In particular, the large spiders necessary to support the massive optics of…
The modern time-delay cosmography aims to infer the cosmological parameters with a competitive precision from observing a multiply imaged quasar. The success of this technique relies upon a robust modeling of the lens mass distribution.…
Single-photon avalanche diodes (SPADs) are growing in popularity for depth sensing tasks. However, SPADs still struggle in the presence of high ambient light due to the effects of pile-up. Conventional techniques leverage fixed or…