This workshop gathers together ~30 SN researchers of LSST institutions and from the broad SN community to discuss about the new problems and needs that people working with LSST data will have to face, and also on developing a plan of how to collaborate to cover future analysis/tests.
This workshop will serve specially to engage SN researchers from LSST institutions that do not have started to work in LSST-related science but that are willing to start investing part of their time in it. In addition, it will serve as a first taste of what LSST can provide for their research projects, provide the chance to learn about how to use current tools, and discuss with other SN researchers about what is needed, and to what they can contribute.
Speaker(s)
Kyle Barbary
I am a Cosmology Data Science Fellow at the Berkeley Center for Cosmological Physics. As a cosmologist, I study the "Universe at large": how the Universe has expanded over time and the properties of dark energy, its largest component. I do this using Type Ia supernovae, a type of stellar explosion that can be used as an indicator of distance. These distance indicators allow us to measure how the universe has expanded over the past 10 billion years, looking back to the first third of the Universe's existence!
I'm a member of two supernova experiments: the Nearby Supernova Factory (SNfactory) and the Dark Energy Survey (DES). SNfactory is an experiment on a telescope in Hawaii and is designed to study nearby Type Ia supernovae in great detail in order to enhance their use in cosmology. DES is a five-year imaging program on a telescope in Chile designed to discover distant supernovae and to measure dark energy with unprecedented precision.
My recent research focus has been on writing reusable open-source scientific software for astrophysics research. I'm a core contributor to the AstroPy project, a community-developed astronomy library for Python. I also develop a Python package specifically for supernova cosmology research called SNCosmo. I've also started developing packages for the Julia programming language, including both astronomy packages and general purpose scientific packages. I’m particularly interested in making it as easy as possible for scientists to find, use, and understand the software they need to accomplish their research.