The James Webb Space Telescope ( JWST ) NIRSpec instrument will allow rest-frame ultraviolet/optical spectroscopy of galaxies in the epoch of reionization ( EoR ) .
Some galaxies may exhibit significant leakage of hydrogen-ionizing photons into the intergalactic medium , resulting in faint nebular emission lines .
We present a machine learning framework for identifying cases of very high hydrogen-ionizing photon escape from galaxies based on the data quality expected from potential NIRSpec observations of EoR galaxies in lensed fields .
We train our algorithm on mock samples of JWST/NIRSpec data for galaxies at redshifts z = 6 –10 .
To make the samples more realistic , we combine synthetic galaxy spectra based on cosmological galaxy simulations with observational noise relevant for z \gtrsim 6 objects of a brightness similar to EoR galaxy candidates uncovered in Frontier Fields observations of galaxy cluster Abell-2744 and MACS-J0416 .
We find that ionizing escape fractions ( f _ { \mathrm { esc } } ) of galaxies brighter than m _ { \mathrm { AB, 1500 } } \approx 27 mag may be retrieved with mean absolute error \Delta f _ { \mathrm { esc } } \approx 0.09 ( 0.12 ) for 24h ( 1.5h ) JWST/NIRSpec exposures at resolution R=100 .
For 24h exposure time , even fainter galaxies ( m _ { \mathrm { AB, 1500 } } < 28.5 mag ) can be processed with \Delta f _ { \mathrm { esc } } \approx 0.14 .
This framework simultaneously estimates the redshift of these galaxies with a relative error less than 0.03 for both 24h ( m _ { \mathrm { AB, 1500 } } < 28.5 mag ) and 1.5h ( m _ { \mathrm { AB, 1500 } } < 27 mag ) exposure times .
We also consider scenarios where just a minor fraction of galaxies attain high f _ { \mathrm { esc } } and present the conditions required for detecting a subpopulation of high f _ { \mathrm { esc } } galaxies within the dataset .