John Wu's ISM@ST intro talk

Transcript

1. John F. Wu JHU/STScI github.com/jwuphysics jfwu@jhu.edu jwuphysics.github.io Picture Credit: Andrew Baker
2. Metallicity Stellar mass Galaxy clusters LBG analogs Star-forming galaxies in massive clusters Compact z~0.2 starbursts Deep learning gas metallicity and HI 30” 1” + LADUMA survey (detecting HI in galaxies out to z < 1.44) + Cool CGM stuff in low-z galaxies with Josh
3. Star-forming, gas-rich, high-z cluster galaxies
4. Four nearby clusters as seen by their stars Picture Credit: A. Block Massive clusters are full of red and dead galaxies.
5. Four nearby clusters as seen by their stars and their hot intracluster medium NASA, Chandra Bernal et al. 17 Massive clusters are full of red and dead galaxies.
6. HST PACS 160 μm ALMA CO (4 - 3) ALMA dust z = 0.861 [C I] (3P 1 - 3P 0 ) also detected Star-forming galaxies residing in the most massive clusters: - Increasing star-formation from 0.3 < z < 1.1 - Massive molecular gas and dust reservoirs - Depressed sSFR relative to field galaxies - No environmental trends in cluster cores z = 0.28 z = 0.42 z = 0.87 z = 1.07 Spitzer/IRAC Wu et al. 2018, ApJ, 853, 195
7. Low-z analogs of Lyman break galaxies (LBG analogs)
8. SDSS × GALEX-selected z ~ 0.2 galaxies strongly resemble high-z LBGs F150LP F606W VLT/SINFONI spectroscopy centered around Pa line for sample of seven LBG analogs. - Kinematics - Dust attenuation - Ionized He/H: AGN, IMF, massive binaries? - PDRs vs shocks (H 2 ro-vibrational emission) Wu et al. 2019, ApJ, 887, 251 Overzier+ 09 Warm H 2 Pa
9. Deep learning and galaxy evolution
10. NGC 55 (Martin Pugh) low Z NGC 4569 (SDSS DR14) high Z Can we learn a galaxy’s gas metallicity from its optical imaging? 2 kpc 10 kpc
11. Metallicity Stellar mass Mass-metallicity relation (MZR) convnet spectroscopy Yes, and we can recover the MZR with zero extra scatter! Wu & Boada 2019, MNRAS, 484, 4683 Lowest Z Highest Z Random ΔZ ~ 0.085 dex
12. We can also predict HI mass fraction accurately... Predicted M HI / M HI mass fraction Measured
13. xGASS 4030 gas-poor p = 0.979 … visualize what we’ve learned... gas-poor features gas-rich features gas-poor features gas-rich features AGC 4540 gas-rich p = 0.817
14. Random baseline Voids Field Groups Validation error … and probe the impacts of galaxy overdensity. The physics that govern the HI-morphology relationship are different in overdense environments: ram pressure, tidal effects, and other gas depletion processes Wu 2020 arXiv: 2001.00018