Euclid preparation XXV. The Euclid Morphology Challenge: Towards model-fitting photometry for billions of galaxies

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Strong gravitational lensing has become one of the main astrophysical probes of the extragalactic universe. It allows precise measurements of deflector galaxy masses. It acts as a cosmic telescope, revealing sources otherwise too dim or small to study. Whe ...

We study the intracluster light (ICL) and intracluster globular clusters (ICGCs) in the nearby Perseus cluster of galaxies using Euclid’s Early Release Observations. By modelling the isophotal and iso-density contours, we mapped the distributions and prope ...

We report the spectroscopic confirmation of a merging pair of massive quiescent galaxies at z = 3.44. Using JWST observations, we confirm that the two galaxies lie at a projected separation of 4.5 kpc with a velocity offset of similar to 680 km s(-1) (delt ...

The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches generally issue predictions using data from a single modality. This stan ...

Deep neural networks often fail to generalize when deployed in dynamic and unpredictable real-world environments, where data distributions at test time can differ significantly from those encountered during training. Since simulating all possible distribut ...

Context. Observations have revealed that the Milky Way, Andromeda, Centaurus A, and possibly other galaxies host spatially thin and kinematically coherent planes of satellites. Such structures are highly improbable within the standard ΛCDM cosmological mod ...

Known for their large amplitude radial pulsations, classical Cepheids are critical standard candles in astrophysics. However, they also exhibit various pulsational irregularities and additional signals that provide deeper insights into their structure and ...

Animal motor control arises from the intricate interplay between neural circuits, biomechanics, and sensory feedback. Deciphering how these components interact is essential for uncovering the fundamental principles of movement generation. This dissertation ...

DARTS-NETGAB is a unified framework for real-time simulation and automated design of gas-bearing supported turbocompressors, facilitating efficient transition from optimization to manufacturable designs. The framework integrates ensemble artificial neural ...

This paper studies the probability of error associated with the social machine learning framework, which involves an independent training phase followed by a cooperative decision-making phase over a graph. This framework addresses the problem of classifyin ...

Lensless cameras relax the design constraints of traditional cameras by shifting image formation from analog optics to digital post-processing. While new camera designs and applications can be enabled, lensless imaging is very sensitive to unwanted interfe ...

We present ∼300 stellar metallicity measurements in two faint M31 dwarf galaxies, Andromeda XVI (M V = −7.5) and Andromeda XXVIII (M V = -8.8), derived using metallicity-sensitive calcium H and K narrowband Hubble Space Telescope imaging. These are the fir ...

We present a combined strong and weak gravitational-lensing analysis of the massive galaxy cluster MACS J1423.8+2404 (z = 0.545, MACS J1423 hereafter), one of the most dynamically relaxed and massive cool-core clusters discovered in the MAssive Cluster Sur ...

Previous methods for predicting room acoustic parameters and speech quality metrics have focused on the single-channel case, where room acoustics and Mean Opinion Score (MOS) are predicted for a single recording device. However, quality-based device select ...

This study introduces a Machine Learning (ML) approach for estimating the T2 spectrum and myelin water fraction (MWF) using multi-echo T2 (MET2) data from preclinical 7T Magnetic Resonance Imaging (MRI) scanners. ML methods have shown promise in MWF estima ...

Multiple drug concentrations concurrent detection and quantification based on electrochemical sensors are of great importance for therapeutic drug monitoring (TDM) and the development of personalized therapy. Cyclic voltammogram (CV) results obtained by el ...

Deep learning has achieved remarkable success in diverse fields in recent years. However, this growth presents significant challenges, particularly in terms of energy consumption during both training and inference phases. While there have been efforts to i ...

Euclid preparation XXV. The Euclid Morphology Challenge: Towards model-fitting photometry for billions of galaxies

Chattez avec Graph Search

Finding gravitational lenses at the dawn of the new generation of wide-field surveys

Euclid: Early Release Observations – The intracluster light and intracluster globular clusters of the Perseus cluster

A Merging Pair of Massive Quiescent Galaxies at z=3.44 in the Cosmic Vine

Automated Ensemble Multimodal Machine Learning for Healthcare

Adaptive Test-Time Learning Under Domain Shift: From Augmentation to Prolonged Adaptation

The effect of measurement uncertainties on the inferred stability of planes of satellite galaxies

The VELOCE modulation zoo III. Detecting additional pulsation modes in optical spectra of classical Cepheids using semi-partial distance correlation periodograms

An integrative computational modeling approach for Drosophila motor control

DARTS-NETGAB: Design Automation and Real-Time Simulation Using Neural Network Ensembles for Turbocompressors on Gas-Bearings

Non-asymptotic performance of social machine learning under limited data

Let There Be Light: Robust Lensless Imaging Under External Illumination With Deep Learning

Stellar Metallicities and Gradients in the Faint M31 Satellites Andromeda XVI and Andromeda XXVIII

The KALEIDOSCOPE survey: a new strong and weak gravitational lensing view of the massive galaxy cluster MACS J1423.8+2404

Multi-Channel Mosra: Mean Opinion Score and Room Acoustics Estimation Using Simulated Data and A Teacher Model

In-Silico Trained AI for Enhanced T2Spectrum Imaging and Myelin Water Fraction Mapping in Preclinical 7T MRI

Automatic simulation of electrochemical sensors by machine learning for drugs quantification

Backpropagation-free Training of Analog AI Accelerators