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Euclid preparation XXII. Selection of quiescent galaxies from mock photometry using machine learning

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New insight on the nature of cosmic reionizers from the CEERS survey

Michaela Hirschmann

The Epoch of Reionization (EoR) began when galaxies grew in abundance and luminosity, so their escaping Lyman continuum (LyC) radiation started ionizing the surrounding neutral intergalactic medium (IGM). Despite significant recent progress, the nature and ...

Edp Sciences S A2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Evolution of the Size-Mass Relation of Star-forming Galaxies Since z=5.5 Revealed by CEERS

Michaela Hirschmann

We combine deep imaging data from the CEERS early release JWST survey and Hubble Space Telescope imaging from CANDELS to examine the size-mass relation of star-forming galaxies and the morphology-quenching relation at stellar masses M-star >= 10(9.5)M(circ ...

Iop Publishing Ltd2024

Euclid preparation: XLIX. Selecting active galactic nuclei using observed colours

Frédéric Courbin, Georges Meylan

The Euclid space mission will cover over 14 000 deg2 with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our ...

2024

The AGORA High-resolution Galaxy Simulations Comparison Project. V. Satellite Galaxy Populations in a Cosmological Zoom-in Simulation of a Milky Way-Mass Halo

Yves Revaz, Loïc Hausammann

We analyze and compare the satellite halo populations at z similar to 2 in the high-resolution cosmological zoom-in simulations of a 1012 M circle dot target halo (z = 0 mass) carried out on eight widely used astrophysical simulation codes (Art-I, Enzo, Ra ...

Iop Publishing Ltd2024

Searching for Strong Gravitational Lenses

Frédéric Courbin, Cameron Alexander Campbell Lemon

Strong gravitational lenses provide unique laboratories for cosmological and astrophysical investigations, but they must first be discovered - a task that can be met with significant contamination by other astrophysical objects and asterisms. Here we revie ...

Springer2024

Meta-learning to address diverse Earth observation problems across resolutions

Devis Tuia, Marc Conrad Russwurm, Benjamin Alexander Kellenberger

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

Springernature2024

Gaia's brightest very metal-poor (VMP) stars Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra

Nicolas Lawrence Etienne Longeard

Context. Gaia DR3 has offered the scientific community a remarkable dataset of approximately one million spectra acquired with the radial velocity spectrometer (RVS) in the calcium II triplet region, which is well suited to identify very metal-poor (VMP) s ...

Edp Sciences S A2024

Strong gravitational lensing's 'external shear' is not shear

David Richard Harvey

The distribution of mass in galaxy-scale strong gravitational lenses is often modelled as an elliptical power-law plus 'external shear', which notionally accounts for neighbouring galaxies and cosmic shear along our line of sight. A small amount of externa ...

Oxford Univ Press2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Predicting the long-term collective behaviour of fish pairs with deep learning

Francesco Mondada, Alexandre Massoud Alahi, Vaios Papaspyros

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

2024

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

David Atienza Alonso, Marina Zapater Sancho, Ali Pahlevan, Darong Huang, Luis Maria Costero Valero

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

2024

XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

Maurizio Martinelli, Frédéric Courbin, Georges Meylan, Malte Tewes, Slobodan Ilic, Gianluca Castignani, Alessandro Pezzotta

Context. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Univ ...

Edp Sciences S A2024

SUNBIRD : a simulation-based model for full-shape density-split clustering

Daniel Felipe Forero Sanchez

Combining galaxy clustering information from regions of different environmental densities can help break cosmological parameter degeneracies and access non-Gaussian information from the density field that is not readily captured by the standard two-point c ...

2024

Hydrodynamical simulations of merging galaxy clusters: giant dark matter particle colliders, powered by gravity

David Richard Harvey

Terrestrial particle accelerators collide charged particles, then watch the trajectory of outgoing debris - but they cannot manipulate dark matter. Fortunately, dark matter is the main component of galaxy clusters, which are continuously pulled together by ...

Oxford Univ Press2024

Euclid: Improving the efficiency of weak lensing shear bias calibration

Frédéric Courbin, Georges Meylan, Malte Tewes

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and ...

Edp Sciences S A2024

The effect of pressure-anisotropy-driven kinetic instabilities on magnetic field amplification in galaxy clusters

Salim Bennouna, Yoan Rappaz

Context. The intracluster medium (ICM) is the low-density diffuse gas that fills the space between galaxies within galaxy clusters. It is primarily composed of magnetized plasma, which reaches virial temperatures of up to 10(8) K, probably due to mergers o ...

Edp Sciences S A2024