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We publicly release ATM, a Python package designed to model asteroid flux measurements to estimate an asteroid's size, surface temperature distribution, and emissivity. A number of the most popular static asteroid thermal models (NEATM, STM, FRM) are implemented with the reflected solar light contribution and Kirchhoff's law accounted for. Priors for fitted parameters can be easily specified and the solution, including the full multi-dimensional posterior probability density function, is found using Markov Chain Monte Carlo (MCMC). We describe the package's architecture and discuss model and fitting validation. Data files with ~10 million WISE flux measurements for ~150,000 unique asteroids and additional Minor Planet Center data are also included with the package, as well as Python Jupyter Notebooks with examples of how to select subsamples of objects, filter and process data, and use ATM to fit for the desired model parameters. The entirety of the analysis presented here, including all the figures, tables, and catalogs, can be easily reproduced with these publicly released Notebooks. We show that ATM can match the best-fit size estimates for well-observed asteroids published in 2016 by the NEOWISE team (Mainzer et al., 2016) with a sub-percent bias and a scatter of only 6%. Our analysis of various sources of random and systematic size uncertainties shows that for the majority of over 100,000 objects with WISE-based size estimates random uncertainties (precision) are about 10%; systematic uncertainties within the adopted model framework, such as NEATM, and with assumed emissivity for WISE W3 and W4 bands, are likely in the range of 10–20%. Hence, the accuracy of WISE-based asteroid size estimates is approximately in the range of 15–20% for most objects, except for unknown errors due to a possibly over-simplified modeling framework (e.g., spherical asteroid approximation). We compare model families to data in WISE color-color diagrams and derive a simple method to estimate size that only uses WISE W3 band flux; we show that it matches estimates based on all four WISE bands to within 10%. We also study optical data collected by the Sloan Digital Sky Survey (SDSS) and show that correlations of optical colors and WISE-based best-fit model parameters indicate robustness of the latter. Our analysis gives support to the claim by Harris & Drube (2014) that candidate metallic asteroids can be selected using the best-fit temperature parameter and infrared albedo. We investigate a correlation between SDSS colors and optical albedo derived using WISE-based size estimates and show that this correlation can be used to estimate asteroid sizes with optical data alone, with a precision of about 17% relative to WISE-based size estimates. After accounting for systematic errors, the difference in accuracy between infrared and optical color-based size estimates becomes less than a factor of two. • An open-source Python package for asteroid thermal modeling using STM, FRM and NEATM models • NEOWISE best-fit diameters are matched to within sub-percent bias and with scatter of 6% using ATM. • A new simple method for estimating asteroid diameters using only WISE W3 data, precise to within 10% • Optical SDSS colors and absolute magnitude can be used to estimate asteroid diameters to within 21% compared to WISE-based estimates. • A sample of 13 good metallic asteroid candidates [ABSTRACT FROM AUTHOR]

We describe the construction and analysis of simulated SPHEREx spectra of Main Belt and Trojan asteroids. SPHEREx will deliver the first all-sky spectral survey at 96 spectral channels between 0.75 μ m and 5.0 μ m. We have developed a method for correcting SPHEREx asteroid spectra for intrinsic rotational variability that does not require light curves and can enable studies before LSST light curves become available for this purpose. Using these spectra, we predict that SPHEREx will deliver meaningful flux measurements for about 100,000 asteroids, including close to 10,000 objects with high-quality spectra; this dataset will represent an increase over our current sample size by more than an order of magnitude. The main SPHEREx contribution to asteroid science will be derived from taxonomic classifications, detailed spectroscopic analyses involving a number of diagnostic spectral features associated with olivine, pyroxene, hydroxyl, water ice, and organics, and constraints on thermal properties. We argue that all asteroids with currently known orbits, about a million objects, should be included in the SPHEREx forced photometry object list to maximize its science impact. Our tools and the library of simulated spectra are made publicly available. • Simulated SPHEREx spectra (0.75–5.0 micron) of Main Belt and Trojan asteroids. • A method for correcting SPHEREx asteroid spectra for intrinsic rotational variability. • A prediction that SPHEREx will deliver meaningful flux measurements for about 100,000 asteroids. • All the tools and a library of simulated spectra are made publicly available on GitHub. [ABSTRACT FROM AUTHOR]