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Register a new userTheory and simulation of spectral line broadening by exoplanetary atmospheric haze
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Atmospheric haze is the leading candidate for the flattening of expolanetary spectra, as its also an important source of opacity in the atmospheres of solar system planets, satellites, and comets. Exoplanetary transmission spectra, which carry information about how the planetary atmospheres become opaque to stellar light in transit, show broad featureless absorption in the region of wavelengths corresponding to spectral lines of sodium, potassium and water. We develop a detailed atomistic model, describing interactions of atomic or molecular radiators with dust and atmospheric haze particulates. This model incorporates a realistic structure of haze particulates from small nano-size seed particles up to sub-micron irregularly shaped aggregates, accounting for both pairwise collisions between the radiator and haze perturbers, and quasi-static mean field shift of levels in haze environments. This formalism can explain large flattening of absorption and emission spectra in haze atmospheres and shows how the radiator - haze particle interaction affects the absorption spectral shape in the wings of spectral lines and near their centers. The theory can account for nearly all realistic structure, size and chemical composition of haze particulates and predict their influence on absorption and emission spectra in hazy environments. We illustrate the utility of the method by computing shift and broadening of the emission spectra of the sodium D line in an argon haze. The simplicity, elegance and generality of the proposed model should make it amenable to a broad community of users in astrophysics and chemistry.
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Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using machine learning algorithms for atmospheric retrieval by implementing a random forest to perform retrievals in seconds that are consistent with the traditional, computationally-expensive nested-sampling retrieval method. We expand upon their approach by presenting a new machine learning model, texttt{plan-net}, based on an ensemble of Bayesian neural networks that yields more accurate inferences than the random forest for the same data set of synthetic transmission spectra. We demonstrate that an ensemble provides greater accuracy and more robust uncertainties than a single model. In addition to being the first to use Bayesian neural networks for atmospheric retrieval, we also introduce a new loss function for Bayesian neural networks that learns correlations between the model outputs. Importantly, we show that designing machine learning models to explicitly incorporate domain-specific knowledge both improves performance and provides additional insight by inferring the covariance of the retrieved atmospheric parameters. We apply texttt{plan-net} to the Hubble Space Telescope Wide Field Camera 3 transmission spectrum for WASP-12b and retrieve an isothermal temperature and water abundance consistent with the literature. We highlight that our method is flexible and can be expanded to higher-resolution spectra and a larger number of atmospheric parameters.
In the quiet regions on the solar surface, turbulent convective motions of granulation play an important role in creating small-scale magnetic structures, as well as in energy injection into the upper atmosphere. The turbulent nature of granulation can be studied using spectral line profiles, especially line broadening, which contains information on the flow field smaller than the spatial resolution of an instrument. Moreover, the Doppler velocity gradient along a line-of-sight (LOS) causes line broadening as well. However, the quantitative relationship between velocity gradient and line broadening has not been understood well. In this study, we perform bisector analyses using the spectral profiles obtained using the Spectro-Polarimeter of the Hinode/Solar Optical Telescope to investigate the relationship of line broadening and bisector velocities with the granulation flows. The results indicate that line broadening has a positive correlation with the Doppler velocity gradients along the LOS. We found excessive line broadening in fading granules, that cannot be explained only by the LOS velocity gradient, although the velocity gradient is enhanced in the process of fading. If this excessive line broadening is attributed to small-scale turbulent motions, the averaged turbulent velocity is obtained as 0.9 km/s.
In this Letter, we make use of sophisticated 3D numerical simulations to assess the extent of atmospheric ion and photochemical losses from Mars over time. We demonstrate that the atmospheric ion escape rates were significantly higher (by more than two orders of magnitude) in the past at $sim 4$ Ga compared to the present-day value owing to the stronger solar wind and higher ultraviolet fluxes from the young Sun. We found that the photochemical loss of atomic hot oxygen dominates over the total ion loss at the current epoch whilst the atmospheric ion loss is likely much more important at ancient times. We briefly discuss the ensuing implications of high atmospheric ion escape rates in the context of ancient Mars, and exoplanets with similar atmospheric compositions around young solar-type stars and M-dwarfs.
Line-intensity mapping observations will find fluctuations of integrated line emission are attenuated by varying degrees at small scales due to the width of the line emission profiles. This attenuation may significantly impact estimates of astrophysical or cosmological quantities derived from measurements. We consider a theoretical treatment of the effect of line broadening on both the clustering and shot-noise components of the power spectrum of a generic line-intensity power spectrum using a halo model. We then consider possible simplifications to allow easier application in analysis, particularly in the context of inferences that require numerous, repeated, fast computations of model line-intensity signals across a large parameter space. For the CO Mapping Array Project (COMAP) and the CO(1-0) line-intensity field at $zsim3$ serving as our primary case study, we expect a $sim10%$ attenuation of the spherically averaged power spectrum on average at relevant scales of $kapprox0.2$-$0.3$ Mpc$^{-1}$, compared to $sim25%$ for the interferometric Millimetre-wave Intensity Mapping Experiment (mmIME) targeting shot noise from CO lines at $zsim1$-$5$ at scales of $kgtrsim1$ Mpc$^{-1}$. We also consider the nature and amplitude of errors introduced by simplified treatments of line broadening, and find that while an approximation using a single effective velocity scale is sufficient for spherically-averaged power spectra, a more careful treatment is necessary when considering other statistics such as higher multipoles of the anisotropic power spectrum or the voxel intensity distribution.
Context. HD13724 is a nearby solar-type star at 43.48 $pm$ 0.06 pc hosting a long-period low-mass brown dwarf detected with the CORALIE echelle spectrograph as part of the historical CORALIE radial-velocity search for extra-solar planets. The companion has a minimum mass of $26.77^{+4.4}_{-2.2} M_{mathrm{Jup}}$ and an expected semi-major axis of $sim$ 240 mas making it a suitable target for further characterisation with high-contrast imaging, in particular to measure its inclination, mass, and spectrum and thus establish its substellar nature. Aims. Using high-contrast imaging with the SPHERE instrument on the Very Large Telescope (VLT), we are able to directly image a brown dwarf companion to HD13724 and obtain a low-resolution spectrum. Methods. We combine the radial-velocity measurements of CORALIE and HARPS taken over two decades and high contrast imaging from SPHERE to obtain a dynamical mass estimate. From the SPHERE data we obtain a low resolution spectrum of the companion from Y to J band, as well as photometric measurements from IRDIS in the J, H and K bands. Results. Using high-contrast imaging with the SPHERE instrument at the VLT, we report the first images of a brown dwarf companion to the host star HD13724. It has an angular separation of 175.6 $pm$ 4.5 mas and H-band contrast of $10.61pm0.16$ mag and, using the age estimate of the star to be $sim$1 Gyr, gives an isochronal mass estimate of $sim$44 $M_{mathrm{Jup}}$. By combining radial-velocity and imaging data we also obtain a dynamical mass of $50.5^{+3.3}_{-3.5} M_{mathrm{Jup}}$. Through fitting an atmospheric model, we estimate a surface gravity of $log g = 5.5$ and an effective temperature of 1000K. A comparison of its spectrum with observed T dwarfs estimates a spectral type of T4 or T4.5, with a T4 object providing the best fit.
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