arXiv subjects

G. Aufort

Publications and source records attributed to G. Aufort.

5 recordsLinked to original sources

arXiv2026

COSMOS-Web: From early star-formation enhancement to late suppression in galaxy groups

Galaxy groups trace dense environments where interactions, gas removal, and reduced accretion may drive quenching. Common diagnostics trace star formation over short timescales ($\lesssim 100$ Myr), so time-resolved star formation histories (SFHs) are needed to separate brief changes from longer-term evolution at fixed mass and redshift. Using COSMOS-Web data, we test how group environment correlates with star formation, how this evolves with cosmic time and group-centric distance, and how high-richness group galaxies differ from field galaxies. We combine COSMOS2025/COSMOS-Web stellar masses and non-parametric SFHs with AMICO group detections and probabilistic memberships. Using stacked SFHs and evolution diagnostics, we compare group and matched field galaxies as a function of normalized group-centric distance ($R_{\rm norm}$), using the richest groups as reference. The clearest suppression appears at $z<1.5$ and low-to-intermediate mass ($8.1<\log(M_\star/M_\odot)<10.5$), reaching a group-field SFH deficit up to 0.8 dex. At $z>1.5$, SFHs show weak suppression or occasional enhancement, a more heterogeneous contrast despite possible systematics. The radial signal also evolves: low-redshift profiles are broadly quenching-oriented across radius, while a clear inner-outer contrast emerges at $z\gtrsim 1$, though ordering at $z\gtrsim 2$ remains tentative given growing uncertainty in AMICO centroids. These results suggest an evolving picture: at early epochs groups are more mixed, with both suppressed and elevated SFHs; from $z\lesssim 1.5$, suppression dominates, most clearly for low-to-intermediate-mass galaxies. This fits inner-region galaxies spending more time within the group potential, undergoing more passages through dense intra-group regions, and receiving less pristine cold gas, making quenching progressively clearer with cosmic time.

astro-ph.GA↗

arXiv2025

Stochastic star formation activity of galaxies within the first billion years probed by JWST

In this work, we aim at characterizing the burstiness level of high-redshift galaxy SFHs and its evolution. We implement a stochastic SFH in CIGALE using PSD, to estimate the burstiness level of star formation in galaxies at 6 6 galaxies, while smoother assumptions introduce biases when applied to galaxies with bursty star-formation activity. The assumed stochasticity level of the SFH also affects the constraints on galaxies' physical properties, including the main sequence. Successively assuming different levels of burstiness, we determined the best-suited SFH for each 6 10. Our results add further evidence that a combination with other mechanisms is likely responsible for the high-z UVLF. The stochastic SFH module is public as part of CIGALE version 2025.1.

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arXiv2025

COSMOS-Web: A history of galaxy migrations over the stellar mass-star formation rate plane

The stellar mass-star formation rate ($\mathrm{M_*}$-$\mathrm{SFR}$) plane is a fundamental diagnostic for distinguishing galaxy populations. However, the evolutionary pathways of galaxies within this plane across cosmic time remain poorly understood. This study aims to observationally characterize galaxy migration in the $\mathrm{M_*}$-$\mathrm{SFR}$ plane using reconstructed star formation histories (SFHs) of galaxies at $z < 4$. Our goal is to provide insights into the physical processes governing star formation and quenching. We analyze a sample of 299,131 galaxies at $z < 4$ from the COSMOS-Web NIRCam survey ($m_{\mathrm{F444W}} < 27$, 0.54 deg$^2$). Using non-parametric SFH modeling with CIGALE, we derive physical properties and reconstruct SFHs. To trace galaxy evolution, we define migration vectors, quantifying their direction ($Φ_{\mathrm{dt}}$ [deg]) and velocity norm ($r_{\mathrm{dt}}$ [dex/Gyr]) on the $\mathrm{M_*}$-$\mathrm{SFR}$ plane. The reliability of these vectors is assessed using the Horizon-AGN simulation. We find that main-sequence galaxies exhibit low-amplitude migration with scattered directions, suggesting oscillations within the main sequence. Their progenitors predominantly lie on the main sequence 1 Gyr earlier. Starburst galaxies show rapid mass assembly ($50\%$ within 350 Myr) and originate from the main sequence, while passive galaxies display uniformly declining SFHs. Massive passive galaxies emerge as early as $3.5 < z < 4$, increasing in number density over time. Only $<20\%$ of passive galaxies were starbursts 1 Gyr prior, indicating diverse quenching pathways. By reconstructing SFHs to $z < 4$, we present a coherent picture of galaxy migration in the $\mathrm{M_*}$-$\mathrm{SFR}$ plane, linking evolutionary phases to their star formation signatures.

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arXiv2024

Reconstructing galaxy star formation histories from COSMOS2020 photometry using simulation-based inference

We propose a novel method to reconstruct the full posterior distribution of the star formation histories (SFHs) of galaxies from broad-band photometry. Our method combines simulation-based inference (SBI) using a neural network trained with SFHs and photometry from the {\sc Horizon-AGN} hydrodynamical cosmological simulation. We apply it to reconstruct SFHs using COSMOS2020 photometry at redshift $0 9$ had a first event of mass assembly around $z\sim 3$, independent of mass. This work represents a pilot study for the future analysis of the \textit{Euclid} Deep fields that will reach similar depths in alike set of photometric bands, but with over an order-of-magnitude larger area, opening the possibility of deriving SFHs for millions of galaxies in a robust manner.

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arXiv2020

Constraining the recent star formation history of galaxies : an Approximate Bayesian Computation approach

[Abridged] Although galaxies are found to follow a tight relation between their star formation rate and stellar mass, they are expected to exhibit complex star formation histories (SFH), with short-term fluctuations. The goal of this pilot study is to present a method that will identify galaxies that are undergoing a strong variation of star formation activity in the last tens to hundreds Myr. In other words, the proposed method will determine whether a variation in the last few hundreds of Myr of the SFH is needed to properly model the SED rather than a smooth normal SFH. To do so, we analyze a sample of COSMOS galaxies using high signal-to-noise ratio broad band photometry. We apply Approximate Bayesian Computation, a state-of-the-art statistical method to perform model choice, associated to machine learning algorithms to provide the probability that a flexible SFH is preferred based on the observed flux density ratios of galaxies. We present the method and test it on a sample of simulated SEDs. The input information fed to the algorithm is a set of broadband UV to NIR (rest-frame) flux ratios for each galaxy. The method has an error rate of 21% in recovering the right SFH and is sensitive to SFR variations larger than 1 dex. A more traditional SED fitting method using CIGALE is tested to achieve the same goal, based on fits comparisons through Bayesian Information Criterion but the best error rate obtained is higher, 28%. We apply our new method to the COSMOS galaxies sample. The stellar mass distribution of galaxies with a strong to decisive evidence against the smooth delayed-$τ$ SFH peaks at lower M* compared to galaxies where the smooth delayed-$τ$ SFH is preferred. We discuss the fact that this result does not come from any bias due to our training. Finally, we argue that flexible SFHs are needed to be able to cover that largest SFR-M* parameter space possible.

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