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We present improved methods for using stars found in astronomical exposuresto calibrate both star and galaxy colors as well as to adjust the instrumentflat field. By developing a spectroscopic model for the SDSS stellar locus incolor-color space, synthesizing an expected stellar locus, and simultaneouslysolving for all unknown zeropoints when fitting to the instrumental locus, weincrease the calibration accuracy of stellar locus matching. We also use a newcombined technique to estimate improved flat-field models for the SubaruSuprimeCam camera, forming `star flats' based on the magnitudes of starsobserved in multiple positions or through comparison with available SDSSmagnitudes. These techniques yield galaxy magnitudes with reliable colorcalibration (< 0.01 - 0.02 mag accuracy) that enable us to estimate photometricredshift probability distributions without spectroscopic training samples. Wetest the accuracy of our photometric redshifts using spectroscopic redshiftsz_s for ~5000 galaxies in 27 cluster fields with at least five bands ofphotometry, as well as galaxies in the COSMOS field, finding sigma((z_p -z_s)/(1 + z_s)) ~ 0.03 for the most probable redshift z_p. We show that thefull posterior probability distributions for the redshifts of galaxies withfive-band photometry exhibit good agreement with redshifts estimated fromthirty-band photometry in the COSMOS field. The growth of shear with increasingdistance behind each galaxy cluster shows the expected redshift-distancerelation for a flat Lambda-CDM cosmology. Photometric redshifts and calibratedcolors are used in subsequent papers to measure the masses of 51 galaxyclusters from their weak gravitational shear. We make our Python code forstellar locus matching available at http://big-macs-calibrate.googlecode.com;the code requires only a catalog and filter functions.

Weighing the Giants II: Improved Calibration of Photometry from Stellar Colors and Accurate Photometric Redshifts