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We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night); multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.
The terrain that theorists cover in this CMB golden age is described. We ponder early universe physics in quest of the fluctuation generator. We extoll the virtues of inflation and defects. We transport fields, matter and radiation into the linear (p
In the 21st Century information environment, adversarial actors use disinformation to manipulate public opinion. The distribution of false, misleading, or inaccurate information with the intent to deceive is an existential threat to the United States
Often fairness assumptions need to be made in order to establish liveness properties of distributed systems, but in many situations these lead to false conclusions. This document presents a research agenda aiming at laying the foundations of a theo
The Large Synoptic Survey Telescope (LSST) is a large-aperture, wide-field, ground-based survey system that will image the sky in six optical bands from 320 to 1050 nm, uniformly covering approximately $18,000$deg$^2$ of the sky over 800 times. The L
Participation on social media platforms has many benefits but also poses substantial threats. Users often face an unintended loss of privacy, are bombarded with mis-/disinformation, or are trapped in filter bubbles due to over-personalized content. T