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Register a new userBayesian Dynamic Mapping of an Exo-Earth from Photometric Variability
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Photometric variability of a directly imaged exo-Earth conveys spatial information on its surface and can be used to retrieve a two-dimensional geography and axial tilt of the planet (spin-orbit tomography). In this study, we relax the assumption of the static geography and present a computationally tractable framework for dynamic spin-orbit tomography applicable to the time-varying geography. First, a Bayesian framework of static spin-orbit tomography is revisited using analytic expressions of the Bayesian inverse problem with a Gaussian prior. We then extend this analytic framework to a time-varying one through a Gaussian process in time domain, and present analytic expressions that enable efficient sampling from a full joint posterior distribution of geography, axial tilt, spin rotation period, and hyperparameters in the Gaussian-process priors. Consequently, it only takes 0.3 s for a laptop computer to sample one posterior dynamic map conditioned on the other parameters with 3,072 pixels and 1,024 time grids, for a total of $sim 3 times 10^6$ parameters. We applied our dynamic mapping method on a toy model and found that the time-varying geography was accurately retrieved along with the axial-tilt and spin rotation period. In addition, we demonstrated the use of dynamic spin-orbit tomography with a real multi-color light curve of the Earth as observed by the Deep Space Climate Observatory. We found that the resultant snapshots from the dominant component of a principle component analysis roughly captured the large-scale, seasonal variations of the clear-sky and cloudy areas on the Earth.
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Photometric variation of a directly imaged planet contains information on both the geography and spectra of the planetary surface. We propose a novel technique that disentangles the spatial and spectral information from the multi-band reflected light curve. This will enable us to compose a two-dimensional map of the surface composition of a planet with no prior assumption on the individual spectra, except for the number of independent surface components. We solve the unified inverse problem of the spin-orbit tomography and spectral unmixing by generalizing the non-negative matrix factorization (NMF) using a simplex volume minimization method. We evaluated our method on a toy cloudless Earth and observed that the new method could accurately retrieve the geography and unmix spectral components. Furthermore, our method is also applied to the real-color variability of the Earth as observed by Deep Space Climate Observatory (DSCOVR). The retrieved map explicitly depicts the actual geography of the Earth and unmixed spectra capture features of the ocean, continents, and clouds. It should be noted that, the two unmixed spectra consisting of the reproduced continents resemble those of soil and vegetation.
We develop a new retrieval scheme for obtaining two-dimensional surface maps of exoplanets from scattered light curves. In our scheme, the combination of the L1-norm and Total Squared Variation, which is one of the techniques used in sparse modeling, is adopted to find the optimal map. We apply the new method to simulated scattered light curves of the Earth, and find that the new method provides a better spatial resolution of the reconstructed map than those using Tikhonov regularization. We also apply the new method to observed scattered light curves of the Earth obtained during the two-year DSCOVR/EPIC observations presented by Fan et al. (2019). The method with Tikhonov regularization enables us to resolve North America, Africa, Eurasia, and Antarctica. In addition to that, the sparse modeling identifies South America and Australia, although it fails to find the Antarctica maybe due to low observational weights on the poles. Besides, the proposed method is capable of retrieving maps from noise injected light curves of a hypothetical Earth-like exoplanet at 5 pc with noise level expected from coronagraphic images from a 8-m telescope. We find that the sparse modeling resolves Australia, Afro-Eurasia, North America, and South America using 2-year observation with a time interval of one month. Our study shows that the combination of sparse modeling and multi-epoch observation with 1 day or 5 days per month can be used to identify main features of an Earth analog in future direct imaging missions such as the Large UV/Optical/IR Surveyor (LUVOIR).
We present the Dynamic Eclipse Mapping (DEM) method designed specifically to reconstruct the surface intensity patterns of non-radial stellar oscillations in eclipsing binaries. The method needs a geometric model of the binary, accepts the light curve and the detected pulsation frequencies on input, and on output yields estimates of the pulsation patterns, in form of images -- thus allowing a direct identification of the surface mode numbers$(ell,m)$. Since it has minimal modelling requirements and can operate on photometric observations in arbitrary wavelength bands, DEM is well suited to analyze the wide-band time series collected by space observatories. The method was extensively tested on simulated data, in which almost all photometrically detectable modes with a latitudinal complexity $ell-|m|le 4$ were properly restored. Multimode pulsations can be also reconstructed in a natural manner, as well as pulsations on components with tilted rotation axis of known direction. It can also be used in principle to isolate the contribution of hidden modes from the light curve. Sensitivity tests show that moderate errors in the geometric parameters and the assumed limb darkening can be partially tolerated by the inversion, in the sense that the lower degree modes are still recoverable. Tidally induced or mutually resonant pulsations, however, are an obstacle that neither the eclipse mapping, nor any other inversion technique can ever surpass. We conclude that, with reasonable assumptions, Dynamic Eclipse Mapping could be a powerful tool for mode identification, especially in moderately close eclipsing binary systems, where the pulsating component is not seriously affected by tidal interactions so that the pulsations are intrinsic to them, and not a consequence of the binarity.
Understanding the total flux and polarization signals of Earth-like planets and their spectral and temporal variability is essential for the future characterization of such exoplanets. We provide computed total (F) and linearly (Q and U) and circularly (V) polarized fluxes, and the degree of polarization P of sunlight that is reflected by a model Earth, to be used for instrument designs, optimizing observational strategies, and/or developing retrieval algorithms. We modeled a realistic Earth-like planet using one year of daily Earth-observation data: cloud parameters (distribution, optical thickness, top pressure, and particle effective radius), and surface parameters (distribution, surface type, and albedo). The Stokes vector of the disk-averaged reflected sunlight was computed for phase angles alpha from 0 to 180 degrees, and for wavelengths lambda from 350 to 865 nm. The total flux F is one order of magnitude higher than the polarized flux Q, and Q is two and four orders of magnitude higher than U and V, respectively. Without clouds, the peak-to-peak daily variations due to the planetary rotation increase with increasing lambda for F, Q, and P, while they decrease for U and V. Clouds modify but do not completely suppress the variations that are due to rotating surface features. With clouds, the variation in F increases with increasing lambda, while in Q, it decreases with increasing lambda, except at the largest phase angles. In earlier work, it was shown that with oceans, Q changes color from blue through white to red. The alpha where the color changes increases with increasing cloud coverage. Here, we show that this unique color change in Q also occurs when the oceans are partly replaced by continents, with or without clouds. The degree of polarization P shows a similar color change. Our computed fluxes and degree of polarization will be made publicly available.
The detections of small, rocky exoplanets have surged in recent years and will likely continue to do so. To know whether a rocky exoplanet is habitable, we have to characterise its atmosphere and surface. A promising characterisation method for rocky exoplanets is direct detection using spectropolarimetry. This method will be based on single pixel signals, because spatially resolving exoplanets is impossible with current and near-future instruments. Well-tested retrieval algorithms are essential to interpret these single pixel signals in terms of atmospheric composition, cloud and surface coverage. Observations of Earth itself provide the obvious benchmark data for testing such algorithms. The observations should provide signals that are integrated over the Earths disk, that capture day and night variations, and all phase angles. The Moon is a unique platform from where the Earth can be observed as an exoplanet, undisturbed, all of the time. Here, we present LOUPE, the Lunar Observatory for Unresolved Polarimetry of Earth, a small and robust spectropolarimeter to observe our Earth as an exoplanet.
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