Detecting heat from minor planets in the outer solar system is challenging, yet it is the most efficient means for constraining the albedos and sizes of Kuiper Belt Objects (KBOs) and their progeny, the Centaur objects. These physical parameters are critical, e.g., for interpreting spectroscopic data, deriving densities from the masses of binary systems, and predicting occultation tracks. Here we summarize Spitzer Space Telescope observations of 47 KBOs and Centaurs at wavelengths near 24 and 70 microns. We interpret the measurements using a variation of the Standard Thermal Model (STM) to derive the physical properties (albedo and diameter) of the targets. We also summarize the results of other efforts to measure the albedos and sizes of KBOs and Centaurs. The three or four largest KBOs appear to constitute a distinct class in terms of their albedos. From our Spitzer results, we find that the geometric albedo of KBOs and Centaurs is correlated with perihelion distance (darker objects having smaller perihelia), and that the albedos of KBOs (but not Centaurs) are correlated with size (larger KBOs having higher albedos). We also find hints that albedo may be correlated with with visible color (for Centaurs). Interestingly, if the color correlation is real, redder Centaurs appear to have higher albedos. Finally, we briefly discuss the prospects for future thermal observations of these primitive outer solar system objects.

Although the final observations of the Spitzer Warm Mission are currently scheduled for March 2019, it can continue operations through the end of the decade with no loss of photometric precision. As we will show, there is a strong science case for extending the current Warm Mission to December 2020. Spitzer has already made major impacts in the fields of exoplanets (including microlensing events), characterizing near Earth objects, enhancing our knowledge of nearby stars and brown dwarfs, understanding the properties and structure of our Milky Way galaxy, and deep wide-field extragalactic surveys to study galaxy birth and evolution. By extending Spitzer through 2020, it can continue to make ground-breaking discoveries in those fields, and provide crucial support to the NASA flagship missions JWST and WFIRST, as well as the upcoming TESS mission, and it will complement ground-based observations by LSST and the new large telescopes of the next decade. This scientific program addresses NASA's Science Mission Directive's objectives in astrophysics, which include discovering how the universe works, exploring how it began and evolved, and searching for life on planets around other stars.

We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachón in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg 2 field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320-1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg 2 region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r ∼27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.