Multivariate Predictors of Lyman Continuum Escape. I. A Survival Analysis of the Low-redshift Lyman Continuum Survey

To understand how galaxies reionized the Universe, we must determine how the escape fraction of Lyman continuum (LyC) photons (f(esc)) depends on galaxy properties. Using the z similar to 0.3 Low-redshift Lyman Continuum Survey (LzLCS), we develop and analyze new multivariate predictors of f(esc). These predictions use the Cox proportional hazards model, a survival analysis technique that incorporates both detections and upper limits. Our best model predicts the LzLCS f(esc) detections with an rms scatter of 0.31 dex, better than single-variable correlations. According to ranking techniques, the most important predictors of f(esc) are the equivalent width (EW) of Lyman-series absorption lines and the UV dust attenuation, which track line-of-sight absorption due to H i and dust. The H i absorption EW is uniquely crucial for predicting f(esc) for the strongest LyC emitters, which show properties similar to weaker LyC emitters and whose high f(esc) may therefore result from favorable orientation. In the absence of H i information, star formation rate surface density (Sigma(SFR)) and [O iii]/[O ii] ratio are the most predictive variables and highlight the connection between feedback and f(esc). We generate a model suitable for z > 6, which uses only the UV slope, Sigma(SFR), and [O iii]/[O ii]. We find that Sigma(SFR) is more important in predicting f(esc) at higher stellar masses, whereas [O iii]/[O ii] plays a greater role at lower masses. We also analyze predictions for other parameters, such as the ionizing-to-nonionizing flux ratio and Ly alpha escape fraction. These multivariate models represent a promising tool for predicting f(esc) at high redshift.