The rate and contribution of mergers to mass assembly from NIRCam observations of galaxy candidates up to 13.3 billion years ago

TL;DR

The paper investigates the role of mergers in early galaxy assembly by applying morphology-based merger identification to deep JWST NIRCam data in the Abell 2744 field, extending merger analyses to the epoch of reionization up to $z\sim9$. By computing Gini, M20, and asymmetry on high-resolution cutouts and applying two merger criteria, the authors define Silver and Gold samples, finding a robust, nearly redshift-independent merger fraction for the stricter Gold class of $f_m = 0.11\pm0.04$, with a higher Silver value of $f_m = 0.39\pm0.06$. The analysis further shows no significant excess in the specific star formation rate for mergers relative to non-mergers across $4.0\le z<9$, suggesting that smooth accretion or minor mergers drive the main growth and star formation in this era. The study demonstrates the feasibility and significance of constraining merger-driven mass assembly during reionization and outlines the need for larger, multi-field JWST datasets and follow-up spectroscopy to refine merger statistics and their impact on galaxy evolution.

Abstract

We present an analysis of the galaxy merger rate in the redshift range $4.0<z<9.0$ (i.e. about 1.5 to 0.5 Gyr after the Big Bang) based on visually identified galaxy mergers from morphological parameter analysis. Our dataset is based on high-resolution NIRCam JWST data (a combination of F150W and F200W broad-band filters) in the low-to-moderate magnification ($μ<2$) regions of the Abell 2744 cluster field. From a parent set of 675 galaxies $(M_{U}\in[-26.6,-17.9])$, we identify 64 merger candidates from the Gini, $M_{20}$ and Asymmetry morphological parameters, leading to a merger fraction $f_m=0.11\pm0.04$. There is no evidence of redshift evolution of $f_m$ even at the highest redshift considered, thus extending well into the epoch of reionization the constant trend seen previously at $z\lesssim 6$. Furthermore, we investigate any potential redshift dependent differences in the specific star formation rates between mergers and non-mergers. Our analysis reveals no significant correlation in this regard, with deviations in the studied redshift range typically falling within $(1-1.5)σ$ from the null hypotesis that can be attributed to sample variance and measurement errors. Finally, we also demonstrate that the classification of a merging system is robust with respect to the observed (and equivalently rest-frame) wavelength of the high-quality JWST broad-band images used. This preliminary study highlights the potential for progress in quantifying galaxy assembly through mergers during the epoch of reionization, with significant sample size growth expected from upcoming large JWST infrared imaging datasets.

Figures (13)

• Figure 1: NIRCam scientific map in the F150W filter. The red region represents the area where the magnification is $\mu\geq2.0$. The galaxies detected in this region of the survey are excluded from the parent sample.
• Figure 2: Illustrative representations from various redshift ranges, featuring extracted cutouts alongside corresponding morphological metrics, ID and photometric redshift. These snapshots are derived from a composite hres map ($20$mas per pixel), integrating data from F150W and F200W bands. The upper row highlights non-merging galaxies, while the lower row presents merger candidates. Each cutout stamp is $2.2\arcsec$ on a side, while the horizontal bar is $0.5 \arcsec$ wide and the white contour represents the $2\sigma$ segmentation map boundary.
• Figure 3: Visual representation of the classification method adopted in this study for five different z-bins (see Sec.\ref{['subsec: merger identification']}). Galaxies located above the horizontal dashed line (representing Eq.\ref{['eq: gini classical merger criteria']}) are labelled with blue triangles and are classified in the Silver sample. Among these, the subset to the right of the vertical dashed line (representing Eq.\ref{['eq: asimmetry classical merger criteria']}) is highlighted in red, representing the galaxies in the Gold sample. We used high-resolution reduction of the F150W and F200W NIRCam imaging (see Sec.\ref{['sec:data selection']}).
• Figure 4: Demography for the galaxy (merger) samples versus redshift. Points correspond to those in Fig.\ref{['fig: GM20 vs A - hres - mu2.0']}. Black squares indicate the total number of candidates considered in each redshift bin (bold number in column (2) in Tab.\ref{['tab:candidates']}). Blue triangles represent galaxies in the Silver sample, while red triangles denote those classified in the Gold sample.
• Figure 5: Rest frame U-magnitude (left) and stellar mass (right) as a function of photometric redshift for the Gold sample (red) and for all other, non-Gold galaxies (grey). Solid lines represent the corresponding median evolution in respect to the mean redshift in each bin