| Co-Investigators |
- Lamiya Mowla (Wellesley College)
- Vince Estrada-Carpenter (Arizona State University)
- Rachel Somerville (Center for Computational Astrophysics)
- Stephanie Tonnesen (Center for Computational Astrophysics)
- Amanda Lue (Columbia University)
- Greg Bryan (Columbia University)
- Laura Sommovigo (Columbia University)
- Matt Ho (Columbia University)
- Shy Genel (Columbia University)
- Viraj Pandya (Columbia University)
- Charlotte Olsen (City University of New York College)
- Gabe Brammer (Niels Bohr Institute, University of Copenhagen)
- Kate Gould (Niels Bohr Institute, University of Copenhagen)
- Maya Merchant (Niels Bohr Institute, University of Copenhagen)
- Imad Pasha (Dragonfly Focused Research Organization)
- Mike Smith (Harvard-Smithsonian Center for Astrophysics)
- FNU Abudrro’uf (Indiana University)
- Marc Huertas-Company (Instituto de Astrofisica De Canarias)
- Mikaeel Yunus (Johns Hopkins University)
- Chris Lovell (University of Cambridge)
- Anna-Christina Eilers (Massachusetts Institute of Technology)
- Ivelina Momcheva (Max Planck Institute for Astronomy)
- Yang Cheng (Max Planck Institute for Astronomy)
- Tim Miller (Northwestern University)
- Tjitske Starkenburg (Northwestern University)
- Chris Willott (NRC Herzberg)
- Jenny Greene (Princeton University)
- Eric Gawiser (Rutgers, The State University of New Jersey)
- Marcin Sawicki (Saint Mary's University)
- Rosi Merida (Saint Mary's University)
- Hansen Jiang (Sidrat Research)
- Jennifer Scora (Sidrat Research)
- Mubdi Rahman (Sidrat Research)
- Henry Ferguson (Space Telescope Science Institute)
- Aaron Yung (Space Telescope Science Institute / STScI)
- Anton Koekemoer (Space Telescope Science Institute / STScI)
- Cami Pacifici (Space Telescope Science Institute / STScI)
- Dan Coe (Space Telescope Science Institute / STScI)
- Gael Noirot (Space Telescope Science Institute / STScI)
- John Wu (Space Telescope Science Institute / STScI)
- Josh Peek (Space Telescope Science Institute / STScI)
- Ioana Ciuca (Stanford University)
- Juan Alfonzo (Tohoku University)
- Danilo Marchesini (Tufts University)
- Valentina Torre (Tufts University)
- Kate Whitaker (University of Massachusetts, Amherst)
- Anan Lu (University of British Columbia)
- Sandra Faber (University of California, Santa Cruz)
- Anishya Harshan (University of Cambridge)
- Erica Nelson (University of Colorado, Boulder)
- Guillaume Desprez (University of Groningen)
- Marusa Bradac (University of Ljubljana)
- Nick Martis (University of Ljubljana)
- Roberta Tripodi (University of Ljubljana)
- Vladan Markov (University of Ljubljana)
- Rachel Cochrane (University of Manchester)
- Rachel Bezanson (University of Pittsburgh)
- Steve Finkelstein (University of Texas, Austin)
- Biprateep Dey (University of Toronto)
- Bob Abraham (University of Toronto)
- Jacqueline Antwi-Danso (University of Toronto)
- Josh Speagle (University of Toronto)
- Seiji Fujimoto (University of Toronto)
- Yoshi Asada (University of Toronto)
- Shashwat Sourav (Washington University)
- Alejandra Rodriguez (Wellesley College)
- Crystal McArdle-Ventura (Wellesley College)
- Jonathan Kemp (Wellesley College)
- Julia Sherman (Wellesley College)
- Pieter Van (Yale University)
- Adam Muzzin (York University, Toronto)
- Sunna Withers (York University, Toronto)
- Vivian Tan (York University, Toronto)
- Norman Grogin (Space Telescope Science Institute / STScI)
- Austen Gabrielpillai (Columbia University)
|
| Abstract |
The physical mechanisms linking galaxy star formation histories (SFHs), morphologies, and large-scale environment remain poorly constrained beyond the local Universe, requiring simultaneous depth, area, resolution, and spectral coverage to measure the joint distribution of these properties across cosmic environments. To quantify the extent to which internal (feedback, baryon cycling, dynamical features) and environmental (halo-scale inflows, cluster pre-processing) processes play a role in regulating galaxy growth from cosmic noon to present day, we propose R-HIVE, which leverages Roman's Hubble-like NIR resolution, wide field of view, grism redshifts, and synergies with Rubin, Euclid, and DESI to infer non-parametric SFHs, pixel-level morphology, and multi-scale environment descriptors. Combining traditional and modern methods, R-HIVE will conduct the largest systematic study of the SFH-morphology-environment correlation out to z~3, addressing:
1. What environmental or morphological factors drive the stochasticity of star formation in galaxies?
2. Does quenching precede or follow morphological transformation, and does this ordering depend on environment, redshift and stellar mass?
3. What is the physical origin of galaxies that push the boundaries of our theoretical models (post-starburst galaxies, ultra-diffuse galaxies, close pairs, and ultra-compact dwarfs and other rare populations that make up <1% of any sample)?
Apart from our primary science goals, R-HIVE will deliver a suite of Level 5 community-contributed value-added catalogs (VACs) with full Bayesian posteriors for SED, morphological, and environmental metrics for ~ 20 million galaxies across HLWAS's medium and deep tiers, alongside a novel multimodal latent space that continuously maps the joint SFH-morphology-environment manifold and enables systematic identification of rare galaxy subpopulations. |
