Hosted by NOAO and the University of Arizona, the LSSTC's Data Science Fellowship Program's cohort met in LSSTC’s hometown of Tucson, AZ.
31 May-2 June 2017; Northwestern University, Evanston, IL
This workshop will bring together expert and young researchers working on all types of supernovae, with an aim of exploring key issues from the LSST survey perspective. A subsidiary goal of this session is to engage the public in urban and suburban Chicago through a public lecture highlighting the unique role of supernovae in understanding the evolution of the universe.
LSSTC Support: $30,000 ($7,000 from Simonyi-Gates Matching Grant)
12-16 June 2017; IN2P3 Computing Center, Lyon, France
This workshop will cover a number of topics: Scientific performance of the LSST image processing stack, the processing or reprocessing of CFHT and Subaru HSC images, latest advances and methods in astronomical image processing in terms of photometry and astrometry, data management and data access in the LSST era, as well as more technical issues such as efficient use of parallel computing infrastructures. Expected participants include staff from LSST-DM (Data Management) as well as the LSST and DESC Science Working groups.
LSSTC Support: $15,000
The search for the faintest and most distant Milky Way companions in deep surveys is an extremely challenging data analysis problem and will benefit from years of sustained effort. This workshop will bring together an international mix of senior and early career scientist, including a critical mass of contributors to key technologies. It will provide an opportunity to communicate developments and bring recognition to developers, to share existing tools, and imagine new ones. We aim to inform both LSST Project software development and community efforts at developing tools for LSST dwarf galaxy science.
Contact: Knut Olsen
LSST Support: $22,100
10 - 14 July 2017; Brookhaven National Laboratory / Stony Brook University, NY
LSSTC will support several meetings of the LSST Dark Energy Science Collaboration (DESC), which is actively working to prepare for a multi-probe dark energy analysis of LSST data. This is the first of three meetings planned in 2017 and 2018.
Contact: Rachel Mandelbaum for more information
LSSTC Support: $28,000 for three meetings
Summer 2017; CIERA at Northwestern University/Adler Planetarium; Evanston, IL
Recent classification efforts have focused on either crowdsourcing visual examination to citizen scientists or automated methods, such as machine learning. Neither approach alone will be sufficient for LSST – instead, we propose to efficiently integrate the two, maximizing the citizen scientists' time while providing the machine learning algorithms with the most useful information available. For variables, significant progress cannot be made prior to the expansion of existing training sets, collections of variables with definitive classifications. The project will enable LSST to develop the first-ever variable-star citizen-science project, which will connect LSST to more than a million members of the public.
Contact: Adam Miller at firstname.lastname@example.org for more information
LSSTC Support: $40,000
12-13 May 2017; Columbia University, Pupin Hall
A workshop will be held at Columbia University to begin the scientific preparation for the detection of optical counterparts of gravitational wave events with LSST. LSST is uniquely suited to find optical counterparts of gravitational waves. Gravitational waves have been detected at high significance by LIGO. Observation of optical counterparts of gravitational wave events, including mergers of black holes and neutron stars as well as other phenomena will provide a more precise measurement on the direction, redshift and other properties of the event, necessary for its full characterization. This is essential for testing cosmology, general relativity and probing the properties of matter at supranuclear densities in neutron stars.
LSSTC Support: $4,800
13-15 March 2017; SLAC; Menlo Park, CA
Blind analyses are an effective way to reduce or eliminate experimenter's bias, the unintended biasing of a result by the scientists making a measurement. While blind analysis methods have become common in certain subfields of physics and astronomy, they are not yet widespread in the community of scientists preparing for LSST data and future CMB surveys. This workshop will bring together members of LSST science collaborations (DESC, transients, statistics) and CMB collaborations with interdisciplinary blinding experts, and blinding critics.
Workshop information: http://kipac.github.io/Blinding/
LSSTC Support: $9,000
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