Unveiling Extended Components of 'Little Red Dots' in Rest-Frame Optical
Yiyang Zhang, Xuheng Ding, Lilan Yang, Erini Lambrides, Hollis Akins, Andrew J. Battisti, Caitlin M. Casey, Chang-hao Chen, Isa Cox, Andreas Faisst, Maximilien Franco, Aryana Haghjoo, Luis C. Ho, Kohei Inayoshi, Shuowen Jin, Mitchell Karmen, Anton M. Koekemoer

TL;DR
This study uses JWST data to detect faint extended emission in high-redshift 'Little Red Dots', revealing their host galaxy properties and black hole growth, thus shedding light on early galaxy evolution.
Contribution
First large, homogeneous sample analysis revealing extended components in high-redshift LRDs and their implications for galaxy and black hole co-evolution.
Findings
Detection of faint extended emission (~200 pc) in LRDs at z~6.5.
Host galaxies are more compact than similar-mass star-forming galaxies.
Black hole masses are significantly above local relations.
Abstract
Recent JWST observations have revealed a population of red, compact, high-redshift objects called 'Little Red Dots'(LRD), whose host components have remained largely unconstrained, possibly due to their extreme compactness. Current morphological studies have been limited by small samples, as well as by insufficient imaging depth, which may not allow reliable separation between point-like and extended components, leaving the existence and properties of extended components in LRD largely unconstrained. Here, we perform the image stacking analysis of 217 LRDs in four NIRCam bands, representing the largest and homogeneous sample observed from COSMOS-Web survey to date. Our results reveal an unambiguous detection of faint extended emission in the F444W band, with a typical size of ~200 parsecs and magnitude of ~27.7 AB at z~6.5. We perform four-band photometric SED fitting based on galaxy…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
