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Grégoire Aufort

Publications and source records attributed to Grégoire Aufort.

2 recordsLinked to original sources

Clumpiness of galaxies revealed in the near-infrared with COSMOS-Web

Clumps in the rest-frame UV emission of galaxies have been observed for decades. Since the launch of the James Webb Space Telescope (JWST), a large population is detected in the rest-frame near-infrared (NIR), raising questions about their formation mechanism. We investigate the presence and properties of NIR over-densities (hereafter substructures) in star-forming and quiescent galaxies at 1 < z < 4 to understand their link to the evolution of their host galaxy. We identify substructures in JWST/NIRCam F277W and F444W residual images at a rest-frame wavelength of 1 um. The fraction of galaxies with substructures with M* > 10^9 Msun has been steadily decreasing with cosmic time from 40% at z = 4 to 10% at z = 1. Clumps, the main small substructures in the rest-frame NIR, are the most common type and are much fainter (2% of the flux) than similar UV clumps in the literature. Nearly all galaxies at the high-mass end of the main sequence (MS), starburst, and green valley regions have substructures. However, we do not find substructures in low-mass galaxies in the green valley and red sequence. Although massive galaxies on the MS and in the green valley have a 40% probability of hosting multiple clumps, the majority of clumpy galaxies host only a single clump. The fraction of clumpy galaxies in the rest-frame NIR is determined by the stellar mass and SFR of the host galaxies. Its evolution with redshift is due to galaxies moving towards lower SFRs at z < 2 and the build-up of low-mass galaxies in the green valley and red sequence. Based on their spatial distribution in edge-on galaxies, we infer that most of substructures are produced in-situ via disk fragmentation. Galaxy mergers may still play an important role at high stellar masses, especially at low SFR.

astro-ph.GA↗

Tempered, Anti-trunctated, Multiple Importance Sampling

Importance sampling is a Monte Carlo method that introduces a proposal distribution to sample the space according to the target distribution. Yet calibration of the proposal distribution is essential to achieving efficiency, thus the resort to adaptive algorithms to tune this distribution. In the paper, we propose a new adpative importance sampling scheme, named Tempered Anti-truncated Adaptive Multiple Importance Sampling (TAMIS) algorithm. We combine a tempering scheme and a new nonlinear transformation of the weights we named anti-truncation. For efficiency, we were also concerned not to increase the number of evaluations of the target density. As a result, our proposal is an automatically tuned sequential algorithm that is robust to poor initial proposals, does not require gradient computations and scales well with the dimension.

stat.CO↗