Diana H. Bacon

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Carbon sequestration in geologic reservoirs is an important approach for mitigating greenhouse gases emissions to the atmosphere. This study first develops an integrated Monte Carlo method for simulating CO2 and brine leakage from carbon sequestration and subsequent geochemical interactions in shallow aquifers. Then, we estimate probability distributions of(More)
Weak gravitational lensing allows one to reconstruct the spatial distribution of the projected mass density across the sky. These " mass maps " provide a powerful tool for studying cosmology as they probe both luminous and dark matter. In this paper, we present a weak lensing mass map reconstructed from shear measurements in a 139 deg 2 area from the Dark(More)
We present measurements of weak gravitational lensing cosmic shear two-point statistics using Dark Energy Survey Science Verification data. We demonstrate that our results are robust to the choice of shear measurement pipeline, either NGMIX or IM3SHAPE, and robust to the choice of two-point statistic, including both real and Fourier-space statistics. Our(More)
We present measurements of weak gravitational lensing cosmic shear two-point statistics using Dark Energy Survey Science Verification data. We demonstrate that our results are robust to the choice of shear measurement pipeline, either ngmix or im3shape, and robust to the choice of two-point statistic, including both real and Fourier-space statistics. Our(More)
We present the first constraints on cosmology from the Dark Energy Survey (DES), using weak lensing measurements from the preliminary Science Verification (SV) data. We use 139 square degrees of SV data, which is less than 3% of the full DES survey area. Using cosmic shear 2-point measurements over three redshift bins we find σ 8 (Ω m /0.3) 0.5 = 0.81 ±(More)
We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ∼116 deg 2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later reexamined in a companion paper with rigorous simulation tests(More)