CLASSY. XV. Kinematics and Spatial Distributions of Outflows in Local Highly Star-Forming Galaxies

Star-forming galaxies drive massive outflows that play an important role in galaxy evolution by regulating feedback and influencing the dynamics of surrounding media. Measuring galactic outflow rates is essential for quantifying feedback efficiency and the amount of mass, momentum, and energy deposited into the circumgalactic medium. In this paper, we examine 17 galactic outflows from the CLASSY survey with radiative transfer modeling of UV absorption lines presented in M. Huberty et al. (2024), to study their spatial distributions and kinematic properties. We study the Si ii, Si iii, and Si iv ionization states that trace the cool and warm phases of the outflows and find that Si ii traces-winds generally behaves differently than the warmer Si iii and Si iv traced-winds. We derive the mass, momentum, and energy loading factors, which we find scale inversely proportional to stellar mass. We find that our measurements of the mass and momentum loading factors are in agreement with the hydrodynamic FIRE-2 simulations. We model the velocity profiles of the winds, with profiles reaching a maximum velocity of 620 km s−1 on average, in agreement with hydrodynamic simulations from CGOLS. We also investigate the relationship between outflow properties and the age of the stellar population from SED fitting. We find that outflows associated with young (< 5 Myr) star forming regions are more likely to have a column density dominated by cooler gas and have mass outflow rates which decrease with radius.

Improvements to AI Systems:

1. Multiphase Outflow Tracer Integration

• Improve AI models to jointly analyze UV absorption lines (Si ii, Si iii, Si iv) as separate tracers of cool vs. warm gas phases, rather than treating outflows as a single-phase medium.

• The improved system can automatically classify outflow kinematics and column densities by ionization state, enabling phase-resolved mass, momentum, and energy loading factor calculations.

2. Stellar-Mass-Dependent Loading Factor Prediction

• Train AI regression models on the inverse scaling of mass/momentum/energy loading factors with stellar mass (as derived from the 17 CLASSY outflows).

• The improved system can predict loading factors for arbitrary star-forming galaxies given only stellar mass and SFR, without full radiative transfer modeling.

3. Simulation-to-Observation Calibration

• Use the FIRE-2 and CGOLS agreement (mass/momentum loading and max velocity 620 km/s) to fine-tune AI emulators of hydrodynamic simulations.

• The improved system can generate synthetic UV absorption spectra from simulation outputs, directly comparable to CLASSY data, accelerating model validation.

4. Stellar-Age–Outflow Property Coupling

• Incorporate SED-derived stellar ages (<5 Myr vs. older) as a conditioning variable in generative AI models of outflow structure.

• The improved system can predict whether an outflow is cool-gas-dominated and has radially decreasing mass outflow rates based on the age of the associated star-forming region, enabling time-resolved feedback models.

5. Automated Velocity Profile Extraction

• Build AI vision models to extract maximum outflow velocities (up to 620 km/s) from absorption line profiles, accounting for line saturation and blending.

• The improved system can automatically parameterize velocity profiles (e.g., power-law or exponential forms) for large galaxy surveys, replacing manual fitting.

6. Uncertainty-Aware Loading Factor Estimator

• Develop Bayesian neural networks that output posterior distributions for mass, momentum, and energy loading factors, incorporating measurement errors from UV line optical depths and stellar masses.

• The improved system can provide robust error bars on feedback efficiencies, critical for comparing to simulations and theoretical models.

Star-forming galaxies drive massive outflows that play an important role in galaxy evolution by regulating feedback and influencing the dynamics of surrounding media. Measuring galactic outflow rates is essential for quantifying feedback efficiency and the amount of mass, momentum, and energy deposited into the circumgalactic medium. In this paper, we examine 17 galactic outflows from the CLASSY survey with radiative transfer modeling of UV absorption lines presented in M. Huberty et al. (2024), to study their spatial distributions and kinematic properties. We study the SiII, SiIII, and SiIV ionization states that trace the cool and warm phases of the outflows and find that SiII traced winds generally behave differently than the warmer SiIII and SiIV traced winds. We derive the mass, momentum, and energy loading factors, which we find scale inversely proportional to stellar mass. We find that our measurements of the mass and momentum loading factors are in agreement with the hydrodynamic FIRE-2 simulations. We model the velocity profiles of the winds, with profiles reaching a maximum velocity of 620 km/s on average, in agreement with hydrodynamic simulations from CGOLS. We also investigate the relationship between outflow properties and the age of the stellar population from SED fitting. We find that outflows associated with young star forming regions are more likely to have a column density dominated by cooler gas and have mass outflow rates which decrease with radius.