CCAPP Seminar: Peter Melchior (Princeton)

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April 7, 2020
11:30AM - 12:30PM
Location
Zoom Virtual Seminar

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Add to Calendar 2020-04-07 11:30:00 2020-04-07 12:30:00 CCAPP Seminar: Peter Melchior (Princeton) Data Fusion for Astronomy and Cosmology Astronomical data grow in quality and quantity, and yet many scientific questions cannot be answered by a single data set alone. While independent analyses are currently the norm, they miss out on substantial scientific synergies offered by the spatial overlap of current and future surveys. In my talk I will show how to build a coherent hyperspectral model from multiple data sets of the same celestial scene: imaging and spectroscopy observed from ground and space. By combining several novel methods from constrained optimization, statistics and machine learning, my group is building the analysis framework to carry out this data fusion. I will present its benefits for cosmological analyses such as gravitational lensing and studies of galaxy clusters, AGNs, and the evolution of galaxies. I will also discuss the challenges that lie ahead, which will require data-driven decision making. And I will conclude with an outlook on how the upcoming surveys LSST and WFIRST will support data fusion for the entire astronomical community, enabling inference and discovery at an unprecedented scale. We will use this zoom link: https://osu.zoom.us/j/326952803 Zoom Virtual Seminar Center for Cosmology and AstroParticle Physics (CCAPP) ccapp@osu.edu America/New_York public
Description

Data Fusion for Astronomy and Cosmology

Astronomical data grow in quality and quantity, and yet many scientific questions cannot be answered by a single data set alone. While independent analyses are currently the norm, they miss out on substantial scientific synergies offered by the spatial overlap of current and future surveys. In my talk I will show how to build a coherent hyperspectral model from multiple data sets of the same celestial scene: imaging and spectroscopy observed from ground and space. By combining several novel methods from constrained optimization, statistics and machine learning, my group is building the analysis framework to carry out this data fusion. I will present its benefits for cosmological analyses such as gravitational lensing and studies of galaxy clusters, AGNs, and the evolution of galaxies. I will also discuss the challenges that lie ahead, which will require data-driven decision making. And I will conclude with an outlook on how the upcoming surveys LSST and WFIRST will support data fusion for the entire astronomical community, enabling inference and discovery at an unprecedented scale.

We will use this zoom link: https://osu.zoom.us/j/326952803

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