Published in

Cambridge University Press (CUP), Proceedings of the International Astronomical Union, S333(12), p. 254-258, 2017

DOI: 10.1017/s1743921317011322

Links

Tools

Export citation

Search in Google Scholar

Constraining Lyman continuum escape using Machine Learning

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

AbstractThe James Webb Space Telescope (JWST) will observe the rest-frame ultraviolet/optical spectra of galaxies from the epoch of reionization (EoR) in unprecedented detail. While escaping into the intergalactic medium, hydrogen-ionizing (Lyman continuum; LyC) photons from the galaxies will contribute to the bluer end of the UV slope and make nebular emission lines less prominent. We present a method to constrain leakage of the LyC photons using the spectra of high redshift (z ≳ 6) galaxies. We simulate JWST/NIRSpec observations of galaxies at z =6–9 by matching the fluxes of galaxies observed in the Frontier Fields observations of galaxy cluster MACS-J0416. Our method predicts the escape fraction fesc with a mean absolute error Δfesc ≈ 0.14. The method also predicts the redshifts of the galaxies with an error $\left〈 \frac{\Delta z}{(1+z)}\right〉 ≈ 0.0003$.

Beta version