Abstract We used 22 μm (W4) Wide-field Infrared Survey Explorer (WISE) observations of 4420 asteroids to analyze lightcurves, and determined spin period estimates for 1929 asteroids. We fit second-order Fourier models at a large number of trial frequencies to the W4 data and analyzed the resulting periodograms. We initially excluded rotational frequencies exceeding 7.57 rotations per day (P < 3.17 hr), which are not sampled adequately by WISE, and periods that exceed twice the WISE observation interval, which is typically 36 hr. We found that three solutions accurately capture the vast majority of the rotational frequencies in our sample: the best-fit frequency and its mirrors around 3.78 and 7.57 rotations per day. By comparing our solutions with a high-quality control group of 752 asteroid spin periods, we found that one of our solutions is accurate (within 5%) in 88% of the cases. The best-fit, secondary, and tertiary solutions are accurate in 55%, 27%, and 6% of the cases, respectively. We also observed that suppression of aliased solutions was more effective with nonuniform sampling than with quasi-uniform sampling.

We used 22 $\mu$m (W4) Wide-field Infrared Survey Explorer (WISE) observations of 4420 asteroids to analyze lightcurves and determined spin period estimates for 1929 asteroids. We fit second-order Fourier models at a large number of trial frequencies to the W4 data and analyzed the resulting periodograms. We initially excluded rotational frequencies exceeding 7.57 rotations per day (P < 3.17 hr), which are not sampled adequately by WISE, and periods that exceed twice the WISE observation interval, which is typically 36 hr. Three solutions accurately capture the vast majority of the rotational frequencies in our sample: the best-fit frequency and its mirrors around 3.78 and 7.57 rotations per day. By comparing our solutions to a high-quality control group of 752 asteroid spin periods, we found that one of our solutions is accurate (within 5%) in 88% of the cases. The best-fit, secondary, and tertiary solutions are accurate in 55%, 27%, and 6% of the cases, respectively. We also observed that suppression of aliased solutions was more effective with non-uniform sampling than with quasi-uniform sampling.

Abstract: We used the reparameterized Near-Earth Asteroid Thermal Model to model observations of a curated set of over 4000 asteroids from the Wide-field Infrared Survey Explorer in two wavelength bands (W2–3 or W3–4) and compared the results to previous results from all four wavelength bands (W1–4). This comparison was done with the goal of elucidating unique aspects of modeling two-band observations so that any potential biases or shortcomings for planned two-band surveys (e.g., the NASA Near-Earth Object Surveyor Mission) can be anticipated and quantified. The W2–3 two-band fits usually yielded slightly smaller diameters than the four-band fits, with a median diameter difference of −10%, with the 5% and 95% quantiles of the distribution at −32% and −1.5%, respectively. We conducted similar comparisons for W3–4, in part because the longest wavelength bands are expected to provide the best two-band results. We found that the W3–4 two-band diameters are slightly larger than the four-band results, with a median diameter difference of 11% and the 5% and 95% quantiles of the distribution at −2.1% and 26%, respectively. The diameter uncertainty, obtained with bootstrap analysis, is larger by 30% and 35% (median values) for the W2–3 and W3–4 fits, respectively, than for the corresponding four-band fits. Using 23 high-quality stellar occultation diameters as a benchmark, we found that the median errors of W2–3 and W3–4 diameter estimates are −15% and +12%, respectively, whereas the median error of the four-band fits is 9.3%. Although the W2–3 and W3–4 diameters appear to have greater systematic errors and uncertainties than their four-band counterparts, two-band estimates remain useful because they improve upon diameter estimates obtained from visible photometry alone.

The spectroscopic characterization of terrestrial exoplanets over a wide spectral range from the near- to the mid-infrared will be made possible for the first time with the JWST. One challenge is that it is not known a priori whether such planets possess optically thick atmospheres or even any atmospheres altogether. However, this challenge also presents an opportunity, the potential to detect the surface of an extrasolar world. This study explores the feasibility of characterizing with the JWST the atmosphere and surface of LHS 3844b, the highest signal-to-noise rocky thermal emission target among planets that are cool enough to have nonmolten surfaces. We model the planetary emission, including the spectral signal of both the atmosphere and surface, and we explore all scenarios that are consistent with the existing Spitzer 4.5 μm measurement of LHS 3844b from Kreidberg et al. In summary, we find a range of plausible surfaces and atmospheres that are within 3σ of the observationless reflective metal-rich, iron-oxidized, and basaltic compositions are allowed, and atmospheres are restricted to a maximum thickness of 1 bar, if near-infrared absorbers at ≳100 ppm are included. We further make predictions on the observability of surfaces and atmospheres and find that a small number (∼3) of eclipse observations should suffice to differentiate between surface and atmospheric features. We also perform a Bayesian retrieval analysis on simulated JWST data and find that the surface signal may make it harder to precisely constrain the abundance of atmospheric species and may falsely induce a weak H2O detection.