Abstract
The 3D geometries of high-redshift galaxies remain poorly understood. We build a differentiable Bayesian model and use Hamiltonian Monte Carlo to efficiently and robustly infer the 3D shapes of star-forming galaxies in James Webb Space Telescope Cosmic Evolution Early Release Science observations with log M * / M ⊙ = 9.0 - 10.5 at z = 0.5-8.0. We reproduce previous results from the Hubble Space Telescope Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey in a fraction of the computing time and constrain the mean ellipticity, triaxiality, size, and covariances with samples as small as ∼50 galaxies. We find high 3D ellipticities for all mass-redshift bins, suggesting oblate (disky) or prolate (elongated) geometries. We break that degeneracy by constraining the mean triaxiality to be ∼1 for log M * / M ⊙ = 9.0 - 9.5 dwarfs at z > 1 (favoring the prolate scenario), with significantly lower triaxialities for higher masses and lower redshifts indicating the emergence of disks. The prolate population traces out a “banana” in the projected b / a - log a diagram with an excess of low-b/a, large- log a galaxies. The dwarf prolate fraction rises from ∼25% at z = 0.5-1.0 to ∼50%-80% at z = 3-8. Our results imply a second kind of disk settling from oval (triaxial) to more circular (axisymmetric) shapes with time. We simultaneously constrain the 3D size-mass relation and its dependence on 3D geometry. High-probability prolate and oblate candidates show remarkably similar Sérsic indices (n ∼ 1), nonparametric morphological properties, and specific star formation rates. Both tend to be visually classified as disks or irregular, but edge-on oblate candidates show more dust attenuation. We discuss selection effects, follow-up prospects, and theoretical implications.
| Original language | English |
|---|---|
| Article number | 54 |
| Pages (from-to) | 54 |
| Journal | The Astrophysical Journal |
| Volume | 963 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Mar 2024 |
Funding
We thank Lucy Reading-Ikkanda at the Simons Foundation for creating Figure . We thank Daniel Angles-Alcazar, Shmuel Bialy, Alberto Bolatto, James Bullock, Rachel Cochrane, Emily Cunningham, Julianne Dalcanton, Benedikt Diemer, Claude-Andre Faucher-Giguere, Shy Genel, Sultan Hassan, Chris Hayward, Marla Geha, Farhanul Hasan, David Helfand, Susan Kassin, Erin Kado-Fong, Andrey Kravtsov, David Law, Tim Miller, Rohan Naidu, Erica Nelson, Jerry Ostriker, Ekta Patel, Mary Putman, Brant Robertson, Aaron Romanowsky, David Schiminovich, Harrison Souchereau, Tjitske Starkenburg, Jonathan Stern, Wren Suess, Peter Teuben, Frank van den Bosch, Arjen van der Wel, Ben Wandelt, Bob Williams, and Jessica Zebrowski for helpful discussions. We are grateful to the anonymous referee for a thorough and helpful report. We thank the Scientific Computing Core at the Flatiron Institute for maintaining the supercomputer on which much of this work was performed. We thank the PyMC developers for creating an easy-to-use package for probabilistic programming and HMC. We also thank the UC Santa Cruz Galaxy Workshop and Kavli Institute for Theoretical Physics at UC Santa Barbara for facilitating this work. V.P. thanks the Osterbrock Leadership Program for the opportunity to shadow the formation of the CEERS team in 2016–2017. This research was supported in part by the National Science Foundation under grant Nos. PHY-1748958 and PHY-2309135. Support for V.P. was provided by NASA through the NASA Hubble Fellowship grant HST-HF2-51489 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555. This research made use of SourceXtractor++ , an open-source software package developed for the Euclid satellite project.
| Funders | Funder number |
|---|---|
| National Science Foundation | PHY-2309135, PHY-1748958 |
| National Aeronautics and Space Administration | HST-HF2-51489 |
| Space Telescope Science Institute | NAS5-26555 |