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Register a new userAn Open-source Bayesian Atmospheric Radiative Transfer (BART) Code: II. The {transit} Radiative-Transfer Module and Retrieval of HAT-P-11b
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This and companion papers by Harrington et al. and Blecic et al. present the Bayesian Atmospheric Radiative Transfer ({BART}) code, an open-source, open-development package to characterize extrasolar-planet atmospheres. {BART} combines a thermochemical equilibrium abundances ({TEA}), a radiative-transfer ({transit}), and a Bayesian statistical (MC3) module to constrain atmospheric temperatures and molecular abundances for given spectroscopic observations. Here, we describe the {transit} radiative-transfer package, an efficient line-by-line radiative-transfer C code for one-dimensional atmospheres, developed by P. Rojo and further modified by the UCF exoplanet group. This code produces transmission and hemisphere-integrated emission spectra. {transit} handles line-by-line opacities from HITRAN, Partridge & Schwenke ({water}), Schwenke (TiO), and Plez (VO); and collision-induced absorption from Borysow, HITRAN, and ExoMol. {transit} emission-spectra models agree with models from C. Morley (priv. comm.) within a few percent. We applied {BART} to the {Spitzer} and {Hubble} transit observations of the Neptune-sized planet HAT-P-11b. Our results generally agree with those from previous studies, constraining the {water} abundance and finding an atmosphere enhanced in heavy elements. Different conclusions start to emerge when we make different assumptions from other studies. The {BART} source code and documentation are available at https://github.com/exosports/BART.
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We present the open-source Bayesian Atmospheric Radiative Transfer (BART) retrieval package, which produces estimates and uncertainties for an atmospheres thermal profile and chemical abundances from observations. Several BART components are also stand-alone packages, including the parallel Multi-Core Markov chain Monte Carlo (MC3), which implements several Bayesian samplers; a line-by-line radiative-transfer model, transit; a code that calculates Thermochemical Equilibrium Abundances, TEA; and a test suite for verifying radiative-transfer and retrieval codes, BARTTest. The codes are in Python and C. BART and TEA are under a Reproducible Research (RR) license, which requires reviewed-paper authors to publish a compendium of all inputs, codes, and outputs supporting the papers scientific claims. BART and TEA produce the compendiums content. Otherwise, these codes are under permissive open-source terms, as are MC3 and BARTTest, for any purpose. This paper presents an overview of the code, BARTTest, and an application to eclipse data for exoplanet HD 189733 b. Appendices address RR methodology for accelerating science, a reporting checklist for retrieval papers, the spectral resolution required for synthetic tests, and a derivation of the effective sample size required to estimate any Bayesian posterior distribution to a given precision, which determines how many iterations to run. Paper II, by Cubillos et al., presents the underlying radiative-transfer scheme and an application to transit data for exoplanet HAT-P-11b. Paper III, by Blecic et al., discusses the initialization and post-processing routines, with an application to eclipse data for exoplanet WASP-43b. We invite the community to use and improve BART and its components at http://GitHub.com/ExOSPORTS/BART/.
This and companion papers by Harrington et al. 2021, submitted and Cubillos et al. 2021, submitted describe an open-source retrieval framework, Bayesian Atmospheric Radiative Transfer (BART), available to the community under the reproducible-research license via https://github.com/exosports/BART . BART is a radiative-transfer code (transit, https://github.com/exosports/transit , Rojo 2009, 2009ASPC..420..321R), initialized by the Thermochemical Equilibrium Abundances (TEA, https://github.com/dzesmin/TEA , Blecic et al. 2016, arXiv:1505.06392) code, and driven through the parameter phase space by a differential-evolution Markov-chain Monte Carlo (MC3, https://github.com/pcubillos/mc3 , Cubillos et al. 2017, arXiv:1610.01336) sampler. In this paper we give a brief description of the framework, and its modules that can be used separately for other scientific purposes; outline the retrieval analysis flow; present the initialization routines, describing in detail the atmospheric profile generator and the temperature and species parameterizations; and specify the post-processing routines and outputs, concentrating on the spectrum band integrator, the best-fit model selection, and the contribution functions. We also present an atmospheric analysis of WASP-43b secondary eclipse data obtained from space- and ground-based observations. We compare our results with the results from the literature, and investigate how the inclusion of additional opacity sources influence the best-fit model.
HYPERION is a new three-dimensional dust continuum Monte-Carlo radiative transfer code that is designed to be as generic as possible, allowing radiative transfer to be computed through a variety of three-dimensional grids. The main part of the code is problem-independent, and only requires an arbitrary three-dimensional density structure, dust properties, the position and properties of the illuminating sources, and parameters controlling the running and output of the code. HYPERION is parallelized, and is shown to scale well to thousands of processes. Two common benchmark models for protoplanetary disks were computed, and the results are found to be in excellent agreement with those from other codes. Finally, to demonstrate the capabilities of the code, dust temperatures, SEDs, and synthetic multi-wavelength images were computed for a dynamical simulation of a low-mass star formation region. HYPERION is being actively developed to include new features, and is publicly available (http://www.hyperion-rt.org).
EMMA is a cosmological simulation code aimed at investigating the reionization epoch. It handles simultaneously collisionless and gas dynamics, as well as radiative transfer physics using a moment-based description with the M1 approximation. Field quantities are stored and computed on an adaptive 3D mesh and the spatial resolution can be dynamically modified based on physically-motivated criteria. Physical processes can be coupled at all spatial and temporal scales. We also introduce a new and optional approximation to handle radiation : the light is transported at the resolution of the non-refined grid and only once the dynamics have been fully updated, whereas thermo-chemical processes are still tracked on the refined elements. Such an approximation reduces the overheads induced by the treatment of radiation physics. A suite of standard tests are presented and passed by EMMA, providing a validation for its future use in studies of the reionization epoch. The code is parallel and is able to use graphics processing units (GPUs) to accelerate hydrodynamics and radiative transfer calculations. Depending on the optimizations and the compilers used to generate the CPU reference, global GPU acceleration factors between x3.9 and x16.9 can be obtained. Vectorization and transfer operations currently prevent better GPU performances and we expect that future optimizations and hardware evolution will lead to greater accelerations.
Molecular line-transition lists are an essential ingredient for radiative-transfer calculations. With recent databases now surpassing the billion-lines mark, handling them has become computationally prohibitive, due to both the required processing power and memory. Here I present a temperature-dependent algorithm to separate strong from weak line transitions, reformatting the large majority of the weaker lines into a cross-section data file, and retaining the detailed line-by-line information of the fewer strong lines. For any given molecule over the 0.3--30 {micron} range, this algorithm reduces the number of lines to a few million, enabling faster radiative-transfer computations without a significant loss of information. The final compression rate depends on how densely populated is the spectrum. I validate this algorithm by comparing Exomols HCN extinction-coefficient spectra between the complete (65 million line transitions) and compressed (7.7 million) line lists. Over the 0.6--33 {micron} range, the average difference between extinction-coefficient values is less than 1%. A Python/C implementation of this algorithm is open-source and available at https://github.com/pcubillos/repack . So far, this code handles the Exomol and HITRAN line-transition format.
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