These are HST ACS/SBC F150LP far-UV (~1610 Angstrom) images of the HDF-North and the UDF outlined in Teplitz et al. (2006) and Siana et al. (2007), respectively. Due to varying coverage across the images, the depths vary, but the majority of the area is deeper than m_AB = 28.0 (3sigma, 1" diameter aperture, See Figure 6 in Siana et al. 2007). Both fields (HDF-N and UDF) have three released images, listed below. HDF-North hdf_f150lp.fits Science image hdf_f150lp_wgt.fits Weight map hdf_f150lp_exptime.fits Exposure time map UDF udf_f150lp.fits Science image udf_f150lp_wgt.fits Weight map udf_f150lp_exptime.fits Exposure time map The science images are in counts/sec and the zeropoint is 22.45 (AB). Thus, to convert a total flux (in counts/sec) to a magnitude, m_150lp(AB) = 22.45-2.5*log(flux). The weight map can be used to get the error based on the background (dark current). The error (in counts/sec) at each pixel is 1/sqrt(wgt). To get an error for the entire aperture, simply add the individual pixel errors in quadrature. Using the weight map will only give an error based on the background, and will not include the Poisson error from the flux of the detected objects. If you need Poisson errors on objects detected at very high significance, than you'll have to convert the object flux (in counts/sec) to total counts using the exposure time map (units in seconds). With this, the total counts can be computed to determine a Poisson error.