diff --git a/joss.07321/10.21105.joss.07321.crossref.xml b/joss.07321/10.21105.joss.07321.crossref.xml new file mode 100644 index 000000000..694c696a8 --- /dev/null +++ b/joss.07321/10.21105.joss.07321.crossref.xml @@ -0,0 +1,193 @@ + + + + 20241210090034-df3f272d935dc761fc27dbc6137c4ed92d4c13ea + 20241210090034 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 12 + 2024 + + + 9 + + 104 + + + + Bayesian model reconstruction based on spectral line observations with pomme + + + + Frederik + De Ceuster + + Institute of Astronomy, Department of Physics & Astronomy, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium + + https://orcid.org/0000-0001-5887-8498 + + + Thomas + Ceulemans + + Institute of Astronomy, Department of Physics & Astronomy, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium + + https://orcid.org/0000-0002-7808-9039 + + + Leen + Decin + + Institute of Astronomy, Department of Physics & Astronomy, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium + + https://orcid.org/0000-0002-5342-8612 + + + Taissa + Danilovich + + School of Physics & Astronomy, Monash University, Clayton, Victoria, Australia + ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Clayton, Victoria, Australia + Institute of Astronomy, Department of Physics & Astronomy, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, Belgium + + https://orcid.org/0000-0002-1283-6038 + + + Jeremy + Yates + + Department of Computer Science, University College London, WC1E 6EA, London, United Kingdom + + https://orcid.org/0000-0003-1954-8749 + + + + 12 + 10 + 2024 + + + 7321 + + + 10.21105/joss.07321 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.14217136 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/7321 + + + + 10.21105/joss.07321 + https://joss.theoj.org/papers/10.21105/joss.07321 + + + https://joss.theoj.org/papers/10.21105/joss.07321.pdf + + + + + + 3D line radiative transfer & synthetic observations with Magritte + De Ceuster + The Journal of Open Source Software + 71 + 7 + 10.21105/joss.03905 + 2022 + De Ceuster, F., Ceulemans, T., Srivastava, A., Homan, W., Bolte, J., Yates, J., Decin, L., Boyle, P., & Hetherington, J. (2022). 3D line radiative transfer & synthetic observations with Magritte. The Journal of Open Source Software, 7(71), 3905. https://doi.org/10.21105/joss.03905 + + + Bayesian model reconstruction based on spectral line observations + De Ceuster + The Astrophysical Journal Supplement Series + 2 + 275 + 10.3847/1538-4365/ad89a2 + 2024 + De Ceuster, F., Ceulemans, T., Decin, L., Danilovich, T., & Yates, J. (2024). Bayesian model reconstruction based on spectral line observations. The Astrophysical Journal Supplement Series, 275(2), 44. https://doi.org/10.3847/1538-4365/ad89a2 + + + Self-consistent dust and non-LTE line radiative transfer with SKIRT + Matsumoto + Astronomy & Astrophysics + 678 + 10.1051/0004-6361/202347376 + 2023 + Matsumoto, K., Camps, P., Baes, M., De Ceuster, F., Wada, K., Nakagawa, T., & Nagamine, K. (2023). Self-consistent dust and non-LTE line radiative transfer with SKIRT. Astronomy & Astrophysics, 678, A175. https://doi.org/10.1051/0004-6361/202347376 + + + The unusual 3D distribution of NaCl around the asymptotic giant branch star IK Tau + Coenegrachts + Astronomy & Astrophysics + 678 + 10.1051/0004-6361/202346116 + 2023 + Coenegrachts, A., Danilovich, T., De Ceuster, F., & Decin, L. (2023). The unusual 3D distribution of NaCl around the asymptotic giant branch star IK Tau. Astronomy & Astrophysics, 678, A85. https://doi.org/10.1051/0004-6361/202346116 + + + Chemical tracers of a highly eccentric AGB-main-sequence star binary + Danilovich + Nature Astronomy + 8 + 10.1038/s41550-023-02154-y + 2024 + Danilovich, T., Malfait, J., Van de Sande, M., Montargès, M., Kervella, P., De Ceuster, F., Coenegrachts, A., Millar, T. J., Richards, A. M. S., Decin, L., Gottlieb, C. A., Pinte, C., De Beck, E., Price, D. J., Wong, K. T., Bolte, J., Menten, K. M., Baudry, A., de Koter, A., … Zijlstra, A. (2024). Chemical tracers of a highly eccentric AGB-main-sequence star binary. Nature Astronomy, 8, 308–327. https://doi.org/10.1038/s41550-023-02154-y + + + Automatic differentiation in PyTorch + Paszke + NIPS 2017 Autodiff Workshop + 2017 + Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., & Lerer, A. (2017). Automatic differentiation in PyTorch. NIPS 2017 Autodiff Workshop. https://openreview.net/forum?id=BJJsrmfCZ + + + PyTorch: An imperative style, high-performance deep learning library + Paszke + Advances in Neural Information Processing Systems 32 (NeurIPS 2019) + 32 + 10.48550/arXiv.1912.01703 + 2019 + Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E., DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner, B., Fang, L., … Chintala, S. (2019). PyTorch: An imperative style, high-performance deep learning library. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 32. https://doi.org/10.48550/arXiv.1912.01703 + + + + + + diff --git a/joss.07321/10.21105.joss.07321.pdf b/joss.07321/10.21105.joss.07321.pdf new file mode 100644 index 000000000..18d3fb9f1 Binary files /dev/null and b/joss.07321/10.21105.joss.07321.pdf differ diff --git a/joss.07321/paper.jats/10.21105.joss.07321.jats b/joss.07321/paper.jats/10.21105.joss.07321.jats new file mode 100644 index 000000000..fa02084fa --- /dev/null +++ b/joss.07321/paper.jats/10.21105.joss.07321.jats @@ -0,0 +1,419 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +7321 +10.21105/joss.07321 + +Bayesian model reconstruction based on spectral line +observations with pomme + + + +https://orcid.org/0000-0001-5887-8498 + +De Ceuster +Frederik + + + + +https://orcid.org/0000-0002-7808-9039 + +Ceulemans +Thomas + + + + +https://orcid.org/0000-0002-5342-8612 + +Decin +Leen + + + + +https://orcid.org/0000-0002-1283-6038 + +Danilovich +Taissa + + + + + + +https://orcid.org/0000-0003-1954-8749 + +Yates +Jeremy + + + + + +Institute of Astronomy, Department of Physics & +Astronomy, KU Leuven, Celestijnenlaan 200D, 3001 Leuven, +Belgium + + + + +School of Physics & Astronomy, Monash University, +Clayton, Victoria, Australia + + + + +ARC Centre of Excellence for All Sky Astrophysics in 3 +Dimensions (ASTRO 3D), Clayton, Victoria, Australia + + + + +Department of Computer Science, University College London, +WC1E 6EA, London, United Kingdom + + + + +1 +3 +2024 + +9 +104 +7321 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2024 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +astronomy +radiative transfer + + + + + + Summary +

A typical problem in astronomy is that, for most of our + observations, we are restricted to the plane of the sky. As a result, + these observations are always mere projections containing only partial + information about the observed object. 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. 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. This is especially the case for spectral + line radiation caused by transitions between the quantized energy + levels of atoms and molecules. Rotational transition lines are + particularly interesting, since they are excited in many astrophysical + environments and can easily be resolved individually. Using spectral + line observations, we can infer information about physical and + chemical parameters, such as abundance of certain molecules, velocity, + and temperature distributions. 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. A detailed description and validation of the methods can + be found in De Ceuster et al. + (2024).

+ + + Statement of need +

Spectral line observations are indispensable in astronomy. 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 + (De + Ceuster et al., 2022; + Matsumoto + et al., 2023). 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. 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 + (Coenegrachts + et al., 2023; + Danilovich + et al., 2024). Therefore, in pomme, we have implemented a line + radiative transfer solver (the forward problem) in the PyTorch + framework + (Paszke + et al., 2019) to leverage the autograd functionality + (Paszke + et al., 2017) to efficiently fit our models to the observations + (the inverse problem) in a streamlined way + (De + Ceuster et al., 2024).

+ + + Example +

[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. 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 + [fig:example_obs]. + The original analysis was done by Coenegrachts et al. + (2023), + and we improved their methods using pomme as described in De Ceuster + et al. + (2024).

+ +

Reconstruction of the NaCl abundance distribution around + the evolved star IK Tauri, created with pomme. An interactive + version of the figure is available in the + documentation. +

+ + + +

NaCl ( + + J=26−25) + rotational line observations, taken with the Atacama Large + Millimeter/submillimeter Array (ALMA), which is used as input in + pomme to create a reconstruction. +

+ + + + + Acknowledgements +

FDC is a Postdoctoral Research Fellow of the Research Foundation - + Flanders (FWO), grant number 1253223N, and was previously supported + for this research by a KU Leuven Postdoctoral Mandate (PDM), grant + number PDMT2/21/066. TC is a PhD Fellow of the Research Foundation - + Flanders (FWO), grant number 1166722N. LD acknowledges support from KU + Leuven C1 MAESTRO grant C16/17/007, KU Leuven C1 BRAVE grant + C16/23/009, KU Leuven Methusalem grant METH24/012, and FWO Research + grant G099720N. 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.

+ + + + + + + + + De CeusterFrederik + CeulemansThomas + SrivastavaAtulit + HomanWard + BolteJan + YatesJeremy + DecinLeen + BoylePeter + HetheringtonJames + + 3D line radiative transfer & synthetic observations with Magritte + The Journal of Open Source Software + 202203 + 7 + 71 + 10.21105/joss.03905 + 3905 + + + + + + + De CeusterFrederik + CeulemansThomas + DecinLeen + DanilovichTaı̈ssa + YatesJeremy + + Bayesian model reconstruction based on spectral line observations + The Astrophysical Journal Supplement Series + 202412 + 275 + 2 + https://arxiv.org/abs/2402.18525 + 10.3847/1538-4365/ad89a2 + 44 + + + + + + + MatsumotoKosei + CampsPeter + BaesMaarten + De CeusterFrederik + WadaKeiichi + NakagawaTakao + NagamineKentaro + + Self-consistent dust and non-LTE line radiative transfer with SKIRT + Astronomy & Astrophysics + 202310 + 678 + https://arxiv.org/abs/2309.02628 + 10.1051/0004-6361/202347376 + A175 + + + + + + + CoenegrachtsA. + DanilovichT. + De CeusterF. + DecinL. + + The unusual 3D distribution of NaCl around the asymptotic giant branch star IK Tau + Astronomy & Astrophysics + 202310 + 678 + https://arxiv.org/abs/2302.06221 + 10.1051/0004-6361/202346116 + A85 + + + + + + + DanilovichT. + MalfaitJ. + Van de SandeM. + MontargèsM. + KervellaP. + De CeusterF. + CoenegrachtsA. + MillarT. J. + RichardsA. M. S. + DecinL. + GottliebC. A. + PinteC. + De BeckE. + PriceD. J. + WongK. T. + BolteJ. + MentenK. M. + BaudryA. + de KoterA. + EtokaS. + GobrechtD. + GrayM. + HerpinF. + JesteM. + LagadecE. + MaesS. + McDonaldI. + MarinhoL. + MüllerH. S. P. + PimpanuwatB. + PlaneJ. M. C. + SahaiR. + WallströmS. H. J. + YatesJ. + ZijlstraA. + + Chemical tracers of a highly eccentric AGB-main-sequence star binary + Nature Astronomy + 202403 + 8 + https://arxiv.org/abs/2407.16979 + 10.1038/s41550-023-02154-y + 308 + 327 + + + + + + PaszkeAdam + GrossSam + ChintalaSoumith + ChananGregory + YangEdward + DeVitoZachary + LinZeming + DesmaisonAlban + AntigaLuca + LererAdam + + Automatic differentiation in PyTorch + NIPS 2017 Autodiff Workshop + 201710 + 20230406 + https://openreview.net/forum?id=BJJsrmfCZ + + + + + + PaszkeAdam + GrossSam + MassaFrancisco + LererAdam + BradburyJames + ChananGregory + KilleenTrevor + LinZeming + GimelsheinNatalia + AntigaLuca + DesmaisonAlban + KopfAndreas + YangEdward + DeVitoZachary + RaisonMartin + TejaniAlykhan + ChilamkurthySasank + SteinerBenoit + FangLu + BaiJunjie + ChintalaSoumith + + PyTorch: An imperative style, high-performance deep learning library + Advances in Neural Information Processing Systems 32 (NeurIPS 2019) + Curran Associates, Inc. + 2019 + 20230406 + 32 + https://papers.nips.cc/paper_files/paper/2019/hash/bdbca288fee7f92f2bfa9f7012727740-Abstract.html + 10.48550/arXiv.1912.01703 + + + + +
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