  In current models used to interpret exoplanet atmospheric observations, the
planet mass is treated as a prior and is estimated independently with external
methods, such as RV or TTV techniques. This approach is necessary as available
spectroscopic data do not have sufficient wavelength coverage and/or SNR to
infer the planetary mass. We examine here the impact of mass uncertainties on
spectral retrieval analyses for a host of atmospheric scenarios. Our approach
is both analytical and numerical: we first use simple approximations to extract
analytically the influence of each parameter to the wavelength-dependent
transit depth. We then adopt a fully Bayesian retrieval model to quantify the
propagation of the mass uncertainty onto other atmospheric parameters. We found
that for clear-sky, gaseous atmospheres the posterior distributions are the
same when the mass is known or retrieved. The retrieved mass is very accurate,
with a precision of more than 10%, provided the wavelength coverage and S/N are
adequate. When opaque clouds are included in the simulations, the uncertainties
in the retrieved mass increase, especially for high altitude clouds. However
atmospheric parameters such as the temperature and trace-gas abundances are
unaffected by the knowledge of the mass. Secondary atmospheres are more
challenging due to the higher degree of freedom for the atmospheric main
component, which is unknown. For broad wavelength range and adequate SNR, the
mass can still be retrieved accurately and precisely if clouds are not present,
and so are all the other atmospheric/planetary parameters. When clouds are
added, we find that the mass uncertainties may impact substantially the
retrieval of the mean molecular weight: an independent characterisation of the
mass would therefore be helpful to capture/confirm the main atmospheric
constituent.
