We have a developed a new method for fitting spectral energy distributions (SEDs) to identify and constrain the physical properties of high-redshift (4 < z < 8) galaxies. Our approach uses an implementation of Bayesian based Markov Chain Monte Carlo (PiMC^2) that allows us to compare observations to arbitrarily complex models and to compute 95% credible intervals that provide robust constraints for the model parameters. The work is presented in 2 sections. In the first, we test PiMC^2 using simulated SEDs to not only confirm the recovery of the known inputs but to assess the limitations of the method and identify potential hazards of SED fitting when applied specifically to high redshift (z>4) galaxies. Our tests reveal five critical results: 1) the ability to confidently constrain metallicity, population ages, and Av all require photometric accuracy better than what is currently achievable (i.e. less than a few percent); 2) the ability to confidently constrain stellar masses (within a factor of two) can be achieved without the need for high-precision photometry; 3) the addition of IRAC photometry does not guarantee that tighter constraints of the stellar masses and ages can be defined; 4) different assumptions about the star formation history can lead to significant biases in mass and age estimates; and 5) we are able to constrain stellar age and Av of objects that are both young and relatively dust free. In the second part of the paper we apply PiMC^2 to 17 4<z<8 objects, including the GRAPES Ly alpha sample (4<z<6), supplemented by HST/WFC3 near-IR observations, and several broad band selected z>6 galaxies. Using PiMC^2, we are able to constrain the stellar mass of these objects and in some cases their stellar age and find no evidence that any of these sources formed at a redshift much larger than z_f=8, a time when the Universe was ~ 0.6 Gyr old.
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