- Lectures
- Institute of Astronomy and Astrophysics
- Location
R1412 of the Astronomy-Mathematics Building, National Taiwan University
- Speaker Name
Gregory Green, Max Planck Institute for Astronomy
- State
Definitive
- Url
Abstract:
The nature of interstellar dust is a 100-year-old question. Though there has been progress towards an answer, basic properties of the dust - such as its chemical composition - remain highly uncertain. The wavelength dependence of dust extinction, typically parameterized by the variable R(V), is thought to reflect the grain-size distribution and composition of the dust, and is therefore one piece of evidence that can be used to empirically constrain the dust properties. Over the last decade, while there have been major advances in mapping dust density throughout our Galaxy, there have been comparatively few measurements of R(V). In this talk, I will discuss recent measurements of the dust extinction curve along 130 million sightlines in the Milky Way and Magellanic Clouds, using low-resolution, flux-calibrated BP/RP spectra from Gaia. Using these measurements, we have created the first large-scale, detailed map of R(V) variation in the Milky Way. This map contains hints that star formation plays a major role in shaping the dust grain population, and that polycyclic aromatic hydrocarbons (PAHs) drive much of the observed variation in R(V). We find that the optical extinction curve is not fully described by R(V), but rather contains at least three additional degrees of freedom, indicating more complex variations in dust chemistry. We also detect optical extinction features, which are of unknown origin. We find that the extinction curve is correlated with the strengths and shapes of various diffuse interstellar bands (DIBs), indicating that extinction features on different wavelength scales are connected. This large quantity of detailed measurements of extinction-curve variation throughout the Milky Way and Magellanic Clouds, enabled by Gaia, not only allows for more precise extinction corrections, but also provides a qualitatively new empirical basis for the development of dust models.