The Euclid, LSST and WFIRST projects will undertake flagship optical/near-infrared surveys in the next decade. By mapping thousands of square degrees of sky and covering the electromagnetic spectrum between 0.3 and 2 microns with sub-arcsec resolution, these projects will detect several tens of billions of sources, enable a wide range of astrophysical investigations and provide unprecedented constraints on the nature of dark energy and dark matter. The ultimate cosmological, astrophysical and time-domain science yield from these missions will require “joint survey processing” (JSP) functionality at the pixel level that is outside the scope of the individual survey projects.
JSP is an IPAC-led initiative with the goal to optimally combine future LSST, Euclid, and WFIRST survey datasets at the pixel level and to provide an interface to the community to use these high-quality data products. JSP is planned as a collaborative effort with support from NASA, DOE and NSF, and participation by the survey projects, NASA science centers, DOE laboratories and the community at large.
Within JSP we work on defining, creating, and implementing tools to combine data at space (~0.1-0.2") and ground-based (>0.7") resolution at the pixel level and at different wavelengths (near-infrared and optical). This enables a range of new science in the areas of Cosmology, Reionization and Galaxy Evolution, Microlensing and the Search for Planets and Stellar Mass Black Holes, and Stellar Populations and their Proper Motions.
Specifically, JSP focuses on the following science cases:
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Precision dark energy studies through weak lensing and photometric redshifts
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Precision Hubble constant measurements through strong lensing time delays
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The search for the most distant galaxies by combining multi-wavelength data
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Rotation curves of galaxies through stellar motions
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Deconfusion to enable the detection of exoplanets through microlensing
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Orbit derivation and composition of Solar System objects
On the technical side, JSP is developing science platforms, leveraging high-performance networking, in order to enable distributed co-processing of petabyte-sized datasets.
More information on JSP can be found in our Astro2020 JSP Science White Paper.
