<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>A compendium of distances to molecular clouds in the Star Formation Handbook</dc:title><dc:creator>Zucker, Catherine; Speagle, Joshua S.; Schlafly, Edward F.; Green, Gregory M.; Finkbeiner, Douglas P.; Goodman, Alyssa; Alves, João</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Accurate distances to local molecular clouds are critical for understanding the star and planet formation process, yet distance measurements are often obtained inhomogeneously on a cloud-by-cloud basis. We have recently developed a method that combines stellar photometric data with              Gaia              DR2 parallax measurements in a Bayesian framework to infer the distances of nearby dust clouds to a typical accuracy of ∼5%. After refining the technique to target lower latitudes and incorporating deep optical data from DECam in the southern Galactic plane, we have derived a catalog of distances to molecular clouds in Reipurth (2008, Star Formation Handbook, Vols. I and II) which contains a large fraction of the molecular material in the solar neighborhood. Comparison with distances derived from maser parallax measurements towards the same clouds shows our method produces consistent distances with ≲10% scatter for clouds across our entire distance spectrum (150 pc−2.5 kpc). We hope this catalog of homogeneous distances will serve as a baseline for future work.</dc:description><dc:publisher/><dc:date>2020-01-01</dc:date><dc:nsf_par_id>10189725</dc:nsf_par_id><dc:journal_name>Astronomy &amp; Astrophysics</dc:journal_name><dc:journal_volume>633</dc:journal_volume><dc:journal_issue/><dc:page_range_or_elocation>A51</dc:page_range_or_elocation><dc:issn>0004-6361</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1051/0004-6361/201936145</dc:doi><dcq:identifierAwardId>1908419; 1739657</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>