arXiv subjects

Gwen Rudie

Publications and source records attributed to Gwen Rudie.

3 recordsLinked to original sources

arXiv2026

Scaling Relations of Galactic Outflows Across Cosmic Time: New Insights from Cosmic Noon

Galactic outflows play a significant role in regulating galaxy evolution. Scaling relations between stellar mass ($M_\ast$), star formation (SFR), and outflow properties have been extensively studied at low redshifts ($z<1$) but less so beyond $z \sim 2$. We construct a joint sample of 387 galaxies from $z \sim$ 0-9, including 98 new Cosmic Noon galaxies from the Keck Baryonic Structure Survey and the Keck Lyman Continuum Spectroscopic Survey. Using high signal-to-noise emission lines (SNR $>$ 50 for H$α$ or [OIII] $\lambda5007$) from Keck/MOSFIRE spectra, we detect warm-ionized outflows by decomposing lines into narrow and broad components. With the joint sample, we explore the redshift evolution of outflow scaling relations. On average, outflows at Cosmic Noon have higher maximum velocities than those at low$-z$ by up to a factor of 3 for a fixed $M_\ast$, SFR, or SFR surface density. They also have higher mass outflow rates for a fixed $M_\ast$. Despite faster and stronger outflows, there is no evolution in the mass loading factor for a fixed $M_\ast$. We find evidence for galactic fountains, as the majority of outflowing gas is recycled at a radius of $\sim$0.03 R$_\textrm{vir}$. We also constrain the overall outflow occurrence rate in our galaxy sample to be at least 30$\%$ when taking galaxy orientation and outflow geometry into account. By analyzing the largest sample of warm-ionized outflows at Cosmic Noon to date and compiling large galaxy samples across all redshifts, we present a comprehensive analysis of galactic outflows throughout cosmic time.

astro-ph.GA↗

arXiv2022

Harvesting the Lyα forest with convolutional neural networks

We develop a machine learning based algorithm using a convolutional neural network (CNN) to identify low HI column density Ly$α$ absorption systems ($\log{N_{\mathrm{HI}}}/{\rm cm}^{-2}<17$) in the Ly$α$ forest, and predict their physical properties, such as their HI column density ($\log{N}_{\mathrm{HI}}/{\rm cm}^{-2}$), redshift ($z_{\mathrm{HI}}$), and Doppler width ($b_{\mathrm{HI}}$). Our CNN models are trained using simulated spectra (S/N $\simeq10$), and we test their performance on high quality spectra of quasars at redshift $z\sim2.5-2.9$ observed with the High Resolution Echelle Spectrometer on the Keck I telescope. We find that $\sim78\%$ of the systems identified by our algorithm are listed in the manual Voigt profile fitting catalogue. We demonstrate that the performance of our CNN is stable and consistent for all simulated and observed spectra with S/N $\gtrsim10$. Our model can therefore be consistently used to analyse the enormous number of both low and high S/N data available with current and future facilities. Our CNN provides state-of-the-art predictions within the range $12.5\leq\log{N_{\mathrm{HI}}}/\mathrm{cm^{-2}}<15.5$ with a mean absolute error of $Δ(\log{N}_{\mathrm{HI}}/{\rm cm}^{-2})=0.13$, $Δ(z_{\mathrm{HI}})=2.7\times{10}^{-5}$, and $Δ(b_{\mathrm{HI}})=4.1\ \mathrm{km\ s^{-1}}$. The CNN prediction costs $<3$ minutes per model per spectrum with a size of 120\,000 pixels using a laptop computer. We demonstrate that CNNs can significantly increase the efficiency of analysing Ly$α$ forest spectra, and thereby greatly increase the statistics of Ly$α$ absorbers.

astro-ph.GA↗

arXiv2017

A comparison of observed and simulated absorption from HI, CIV, and SiIV around $z\approx2$ star-forming galaxies suggests redshift-space distortions are due to inflows

We study HI and metal-line absorption around $z\approx2$ star-forming galaxies by comparing an analysis of data from the Keck Baryonic Structure Survey to mock spectra generated from the EAGLE cosmological, hydrodynamical simulations. We extract sightlines from the simulations and compare the properties of the absorption by HI, CIV and SiIV around simulated and observed galaxies using pixel optical depths. We mimic the resolution, pixel size, and signal-to-noise ratio of the observations, as well as the distributions of impact parameters and galaxy redshift errors. We find that the EAGLE reference model is in excellent agreement with the observations. In particular, the simulation reproduces the high metal-line optical depths found at small galactocentric distances, the optical depth enhancements out to impact parameters of 2 proper Mpc, and the prominent redshift-space distortions which we find are due to peculiar velocities rather than redshift errors. The agreement is best for halo masses $\sim10^{12.0}$ M$_\odot$, for which the observed and simulated stellar masses also agree most closely. We examine the median ion mass-weighted radial gas velocities around the galaxies, and find that most of the gas is infalling, with the infall velocity depending on halo rather than stellar mass. From this we conclude that the observed redshift-space distortions are predominantly caused by infall rather than outflows.

astro-ph.GA↗