Published paper includes contribution from DiRAC Researchers: Graham Melissa, Connolly Andrew, Morrison Christopher B., Ivezić Željko, Daniel Scott, Jones R. Lynne, Jurić Mario, Yoachim Peter, Bryce Kalmbach J. Published Date: April 2020.

Abstract

Accurate photometric redshift (photo-zz) estimates are essential to the cosmological science goals of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). In this work we use simulated photometry for mock galaxy catalogs to explore how LSST photo-zz estimates can be improved by the addition of near-infrared (NIR) and/or ultraviolet (UV) photometry from the Euclid, WFIRST, and/or CASTOR space telescopes. Generally, we find that deeper optical photometry can reduce the standard deviation of the photo-zz estimates more than adding NIR or UV filters, but that additional filters are the only way to significantly lower the fraction of galaxies with catastrophically under- or over-estimated photo-zz. For Euclid, we find that the addition of JHJH 5σ5σ photometric detections can reduce the standard deviation for galaxies with z>1z>1 (z>0.3z>0.3) by ∼20%∼20% (∼10%∼10%), and the fraction of outliers by ∼40%∼40% (∼25%∼25%). For WFIRST, we show how the addition of deep YJHKYJHK photometry could reduce the standard deviation by ≳50%≳50% at z>1.5z>1.5 and drastically reduce the fraction of outliers to just ∼2%∼2% overall. For CASTOR, we find that the addition of its UVUV and uu-band photometry could reduce the standard deviation by ∼30%∼30% and the fraction of outliers by ∼50%∼50% for galaxies with z<0.5z<0.5. We also evaluate the photo-zz results within sky areas that overlap with both the NIR and UV surveys, and when spectroscopic training sets built from the surveys’ small-area deep fields are used.

Dr. Stephen Portillo, DiRAC Postdoctoral Fellow, coauthored paper “Photometric Biases in Modern Surveys” published in March 2020.

Many surveys use maximum-likelihood (ML) methods to fit models when extracting photometry from images. We show that these ML estimators systematically overestimate the flux as a function of the signal-to-noise ratio and the number of model parameters involved in the fit. 

Paper published by DiRAC Researcher, Dr. Sarah Greenstreet. Dr. Greenstreet is a joint postdoctoral fellow with the Asteroid Institute, a program of B612, and the DiRAC Institute at the University of Washington. Her research interests include the study of orbital dynamics and impacts of small bodies in the Solar System.

Months ago, a team of scientists led by Sarah Greenstreet (B612 Asteroid Institute and University of Washington) conducted a study in which they made predictions for the crater count they expected to find on MU69’s surface. Greenstreet and collaborators used observations of Pluto and Charon’s surfaces and models of known Kuiper-belt populations to explore the bombardment of MU69 over the solar system’s life span and calculate the number of craters of different sizes its surface should host.

The authors’ results were intriguing: they found that, despite getting bombarded for 4+ billion years, MU69 should be marred by very few craters. Greenstreet and collaborators estimate that MU69 should have only ~25–50 craters larger than ~200 m in size, which is the smallest size we’re likely be able to see with the full-resolution New Horizons images.

Read full article provided by aasnova.org here.

DiRAC Researcher, Gwendolyn Eadie, published a paper in the Astrophysical Journal. In a series of three papers, Eadie et al. developed a hierarchical Bayesian method to estimate the Milky Way Galaxy’s mass given a physical model for the potential, a measurement model, and kinematic data of test particles such as globular clusters (GCs) or halo stars in the Galaxy’s halo.