arXiv subjects

Kiyoaki C. Omori

Publications and source records attributed to Kiyoaki C. Omori.

4 recordsLinked to original sources

arXiv2026

Interaction-induced star formation boosts stellar mass assembly in $z\sim5$ galaxies

Galaxy interactions are a key ingredient in galaxy evolution; not only are they a primary pathway of galaxy growth and mass assembly, but also a key driver of processes such as star formation and quenching. We investigate the impact of galaxy-galaxy interactions on stellar mass assembly using JWST/NIRCam observations of a spectroscopically selected sample of galaxies at $5.0<z_{spec}<5.6$ from the Canadian NIRISS Unbiased Cluster Survey (CANUCS). Of the 48 galaxies in our parent sample, we visually classify 21 ($44\%$) as closely-interacting ($\lesssim$ 5 kpc) systems with two or more components. We evaluate the non-parametric star formation histories (SFHs) of these systems' components using the spectral energy distribution fitting code \textsc{Dense Basis}. We find that the components in these systems experience brief intervals ($\sim0.2$ Gyr) of strongly enhanced star formation that grow their stellar mass by $\sim2.66\pm0.85\times$, forming $\sim1.71\pm0.37\times$ of excess mass than expected compared to if there was no burst. Attributing these star formation rate enhancements to interactions and assuming that the components will merge, we find that mergers are responsible for $\sim42^{+20}_{-25}\%$ of the total stellar mass growth of galaxies at $z\sim5$. While about half of this contribution comes from the merging of the pre-existing stellar masses of the merging galaxies, half is due to stellar mass that is newly-formed during the interaction. We conclude that mergers, and their associated star formation bursts, are an important pathway for stellar mass growth in high-$z$ galaxies.

astro-ph.GA↗

arXiv2025

MINERVA: A NIRCam Medium Band and MIRI Imaging Survey to Unlock the Hidden Gems of the Distant Universe

We present an overview of the MINERVA survey, a 259.8 hour (prime) and 127 hour (parallel) Cycle 4 treasury program on the James Webb Space Telescope (JWST). MINERVA is obtaining 8 filter NIRCam medium band imaging (F140M, F162M, F182M, F210M, F250M, F300M, F360M, F460M) and 2 filter MIRI imaging (F1280W, F1500W) in four of the five CANDELS Extragalactic fields: UDS, COSMOS, AEGIS and GOODS-N. These fields were previously observed in Cycle 1 with 7 - 9 NIRCam filters by the PRIMER, CEERS and JADES programs. MINERVA reaches a 5$σ$ depth of 28.1 mag in F300M and covers $\sim$ 542 arcmin$^2$, increasing the area of existing JWST medium-band coverage in at least 8 bands by $\sim$ 7$\times$. The MIRI imaging reaches a 5$σ$ depth of 23.9 mag in F1280W and covers $\sim$ 275 arcmin$^2$ in at least 2 MIRI filters. When combined with existing imaging, these data will provide a photometric catalog with 20-26 JWST filters (depending on field) and 26-35 filters total, including HST. This paper presents a detailed breakdown of the filter coverage, exposure times, and field layout relative to previous observations, as well as an overview of the primary science goals of the project. These include uncovering the physics of enigmatic sources hiding in current broadband catalogs, improving systematics on stellar mass functions and number densities by factors of $\gtrsim$ 3, and resolved mapping of stellar mass and star formation at 1 $< z <$ 6. When complete, MINERVA will become an integral part of the treasury deep field imaging datasets, significantly improving population studies with well-understood completeness, robust photometric redshifts, stellar masses, and sizes, and facilitating spectroscopic follow up for decades to come.

astro-ph.GA↗

arXiv2025

CANUCS/Technicolor Data Release 1: Imaging, Photometry, Slit Spectroscopy, and Stellar Population Parameters

We present the first data release of the CAnadian NIRISS Unbiased Cluster Survey (CANUCS), a JWST Cycle 1 GTO program targeting 5 lensing clusters and flanking fields in parallel (Abell 370, MACS0416, MACS0417, MACS1149, MACS1423; survey area \tilda100 arcmin$^{2}$), with NIRCam imaging, NIRISS slitless spectroscopy, and NIRSpec prism multi-object spectroscopy. Fields centered on cluster cores include imaging in 8 bands from 0.9-4.4$μ$m, alongside continuous NIRISS coverage from 1.15-2$μ$m, while the NIRCam flanking fields provide 5 wide and 9 medium band filters for exceptional spectral sampling, all to \tilda29 mag$_{AB}$. We also present JWST in Technicolor, a Cycle 2 follow-up GO program targeting 3 CANUCS clusters (Abell 370, MACS0416, MACS1149). The Technicolor program adds NIRISS slitless spectroscopy in F090W to the cluster fields while adding 8 wide, medium, and narrow band filters to the flanking fields. This provides NIRCam imaging in all wide and medium band filters over \tilda30 arcmin$^{2}$. This paper describes our data reduction and photometry methodology. We release NIRCam, NIRISS, and HST imaging, PSFs, PSF-matched imaging, photometric catalogs, and photometric and spectroscopic redshifts. We provide lens models and stellar population parameters in up to 19 filters for \tilda53,000 galaxies in the cluster fields, and \tilda44,000 galaxies in up to 29 filters in the flanking fields. We further present 733 NIRSpec spectra and redshift measurements up to $z=10.8$. Comparing against our photometric redshifts, we find catastrophic outlier rates of only 4-7\% and scatter of $σ_{\rm NMAD}$ of 0.01-0.03.

astro-ph.GA↗

arXiv2024

Katachi: Decoding the Imprints of Past Star Formation on Present Day Morphology in Galaxies with Interpretable CNNs

The physical processes responsible for shaping how galaxies form and quench over time leave imprints on both the spatial (galaxy morphology) and temporal (star formation history; SFH) tracers that we use to study galaxies. While the morphology-SFR connection is well studied, the correlation with past star formation activity is not as well understood. To quantify this we present Katachi, an interpretable convolutional neural network (CNN) framework that learns the connection between the factors regulating star formation in galaxies on different spatial and temporal scales. Katachi is trained on 9904 galaxies at 0.02$<$z$<$0.1 in the SDSS-IV MaNGA DR17 sample to predict stellar mass (M$_*$; RMSE 0.22 dex), current star formation rate (SFR; RMSE 0.31 dex) and half-mass time (t$_{50}$; RMSE 0.23 dex). This information allows us to reconstruct non-parametric SFHs for each galaxy from \textit{gri} imaging alone. To quantify the morphological features informing the SFH predictions we use SHAP (SHapley Additive exPlanations). We recover the expected trends of M$_*$ governed by the growth of galaxy bulges, and SFR correlating with spiral arms and other star-forming regions. We also find the SHAP maps of D4000 are more complex than those of M$_*$ and SFR, and that morphology is correlated with t$_{50}$ even at fixed mass and SFR. Katachi serves as a scalable public framework to predict galaxy properties from large imaging surveys including Rubin, Roman, and Euclid, with large datasets of high SNR imaging across limited photometric bands.

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