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Copy file name to clipboardExpand all lines: joss/paper.bib
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@ARTICLE{DeCeuster2022,
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author = {{De Ceuster}, Frederik and {Ceulemans}, Thomas and {Srivastava}, Atulit and {Homan}, Ward and {Bolte}, Jan and {Yates}, Jeremy and {Decin}, Leen and {Boyle}, Peter and {Hetherington}, James},
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title = "{3D Line Radiative Transfer \& Synthetic Observations with Magritte}",
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title = {3D Line Radiative Transfer \& Synthetic Observations with {Magritte}},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@ARTICLE{Matsumoto2023,
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author = {{Matsumoto}, Kosei and {Camps}, Peter and {Baes}, Maarten and {De Ceuster}, Frederik and {Wada}, Keiichi and {Nakagawa}, Takao and {Nagamine}, Kentaro},
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title = "{Self-consistent dust and non-LTE line radiative transfer with SKIRT}",
author = {{Coenegrachts}, A. and {Danilovich}, T. and {De Ceuster}, F. and {Decin}, L.},
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title = "{The unusual 3D distribution of NaCl around the asymptotic giant branch star IK Tau}",
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journal = {\aap},
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journal = {Astronomy & Astrophysics},
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keywords = {stars: individual: IK Tau, stars: AGB and post-AGB, circumstellar matter, submillimeter: stars, Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies},
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year = 2023,
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month = oct,
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@inproceedings{Paszke2019,
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title = {{PyTorch}: {An} {Imperative} {Style}, {High}-{Performance} {Deep} {Learning} {Library}},
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title = {{PyTorch}: An ImperativeStyle, High-PerformanceDeepLearningLibrary},
Copy file name to clipboardExpand all lines: joss/paper.md
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# Summary
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A typical problem in astronomy is that, for most of our observations, we are restricted to the plane of the sky.
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As a result, these observations are always mere projections containing only partial information about the observed object.
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Luckily, some frequency bands of the electromagnetic spectrum are optically thin, such that we receive radiation from the entire medium along the line of sight.
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This means that, at least in principle, from the observed radiation, we can extract information about the physical and chemical conditions along the entire line of sight.
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This is especially the case for spectral line radiation caused by transitions between the quantized energy levels of atoms and molecules.
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Rotational transition lines are particularly interesting, since they are excited in many astrophysical environments and can easily be resolved individually.
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Using spectral line observations, we can infer information about physical and chemical parameters, such as abundance of certain molecules, velocity, and temperature distributions.
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To facilitate this, we built a Python package, called [pomme]{.sc}, that helps users reconstruct 1D spherically symmetric or generic 3D models, based on astronomical spectral line observations.
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To facilitate this, we built a Python package, called pomme, that helps users reconstruct 1D spherically symmetric or generic 3D models, based on astronomical spectral line observations.
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A detailed description and validation of the methods can be found in [@DeCeuster2024].
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# Statement of need
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Spectral line observations are indispensible in astronomy.
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Spectral line observations are indispensable in astronomy.
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As a result, many line radiation transport solvers exist to solve the (forward) problem of determining what spectral line observations of a certain model would look like [@DeCeuster2022; @Matsumoto2023].
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However, far fewer tools exist to efficiently solve the more pressing inverse problem of determining what model could correspond to certain observations, commonly referred to as fitting our models to observtions.
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Although one can use existing forward solvers to iteratively solve the inverse problem, the resulting process is often slow, cumbersome, and leaves, much room for improvement [@Coenegrachts2023; @Danilovich2024].
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Therefore, in [pomme]{.sc}, we have implemented a line radiative transfer solver (the forward problem) in the [PyTorch]{.sc} framework [@Paszke2019] to leverage the [autograd]{.sc} functionality [@Paszke2017] to efficiently fit our models to the observations (the inverse problem) in a streamlined way [@DeCeuster2024].
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However, far fewer tools exist to efficiently solve the more pressing inverse problem of determining what model could correspond to certain observations, commonly referred to as fitting our models to observations.
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Although one can use existing forward solvers to iteratively solve the inverse problem, the resulting process is often slow, cumbersome, and leaves much room for improvement [@Coenegrachts2023; @Danilovich2024].
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Therefore, in pomme, we have implemented a line radiative transfer solver (the forward problem) in the PyTorch framework [@Paszke2019] to leverage the autograd functionality [@Paszke2017] to efficiently fit our models to the observations (the inverse problem) in a streamlined way [@DeCeuster2024].
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# Example
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\autoref{fig:example} shows an application of [pomme]{.sc}, where it was used to reconstruct the abundance distribution of NaCl (table salt) around the evolved star IK Tauri.
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The reconstruction is based on observations of the NaCl ($J=26-25$) rotational line, taken with the Atacama Large (sub)Millimetre Array (ALMA), shown in \autoref{fig:example_obs}.
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The original analysis was done by @Coenegrachts2023, and we improved their methods using [pomme]{.sc} as described in @DeCeuster2024.
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\autoref{fig:example} shows an application of pomme, where it was used to reconstruct the abundance distribution of NaCl (table salt) around the evolved star IK Tauri.
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The reconstruction is based on observations of the NaCl ($J=26-25$) rotational line, taken with the Atacama Large Millimeter/submillimeter Array (ALMA), shown in \autoref{fig:example_obs}.
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The original analysis was done by @Coenegrachts2023, and we improved their methods using pomme as described in @DeCeuster2024.
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![Reconstruction of the NaCl abundance distribution around the evolved star IK Tauri, created with [pomme]{.sc}. An interactive version of the figure is available in the [documentation](https://pomme.readthedocs.io/en/latest/_static/NaCl_reconstruction.html). \label{fig:example}](IKTau_NaCl.png)
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. \label{fig:example}](IKTau_NaCl.png)
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![NaCl ($J=26-25$) rotational line observations, taken with the Atacama Large (sub)Millimetre Array (ALMA), which is used as input in [pomme]{.sc} to create a reconstruction. \label{fig:example_obs}](IKTau_NaCl_obs.png)
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# Acknowledgements
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TD is supported in part by the Australian Research Council through a Discovery Early Career Researcher Award, number DE230100183, and by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013.
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