Towards a JOSS paper

paper/paper.bib

@@ -0,0 +1,71 @@
+
+
+@InProceedings{krämer2021probabilistic,
+  title =        {Probabilistic {ODE} Solutions in Millions of Dimensions},
+  author =       {Kr{\"a}mer, Nicholas and Bosch, Nathanael and Schmidt,
+                  Jonathan and Hennig, Philipp},
+  booktitle =    {Proceedings of the 39th International Conference on Machine
+                  Learning},
+  pages =        {11634--11649},
+  year =         2022,
+  editor =       {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and
+                  Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
+  volume =       162,
+  series =       {Proceedings of Machine Learning Research},
+  month =        {17--23 Jul},
+  publisher =    {PMLR},
+  pdf =          {https://proceedings.mlr.press/v162/kramer22b/kramer22b.pdf},
+  url =          {https://proceedings.mlr.press/v162/kramer22b.html},
+}
+
+@InProceedings{tronarp2022fenrir,
+  title =        {Fenrir: Physics-Enhanced Regression for Initial Value
+                  Problems},
+  author =       {Tronarp, Filip and Bosch, Nathanael and Hennig, Philipp},
+  AUTHOR+an =    {2=highlight},
+  booktitle =    {Proceedings of the 39th International Conference on Machine
+                  Learning},
+  pages =        {21776--21794},
+  year =         2022,
+  editor =       {Chaudhuri, Kamalika and Jegelka, Stefanie and Song, Le and
+                  Szepesvari, Csaba and Niu, Gang and Sabato, Sivan},
+  volume =       162,
+  series =       {Proceedings of Machine Learning Research},
+  month =        {17--23 Jul},
+  publisher =    {PMLR},
+  pdf =          {https://proceedings.mlr.press/v162/tronarp22a/tronarp22a.pdf},
+  url =          {https://proceedings.mlr.press/v162/tronarp22a.html},
+}
+
+@inproceedings{bosch2023probabilistic,
+  title =        {Probabilistic Exponential Integrators},
+  author =       {Nathanael Bosch and Philipp Hennig and Filip Tronarp},
+  booktitle =    {Thirty-seventh Conference on Neural Information Processing
+                  Systems},
+  year =         2023,
+  url =          {https://openreview.net/forum?id=2dx5MNs2Ip}
+}
+
+@inproceedings{beck2024diffusion,
+  title =        {Diffusion Tempering Improves Parameter Estimation with
+                  Probabilistic Integrators for Ordinary Differential Equations},
+  author =       {Jonas Beck and Nathanael Bosch and Michael Deistler and Kyra
+                  L. Kadhim and Jakob H. Macke and Philipp Hennig and Philipp
+                  Berens},
+  booktitle =    {Forty-first International Conference on Machine Learning},
+  year =         2024,
+  url =          {https://openreview.net/forum?id=43HZG9zwaj}
+}
+
+
+@misc{wenger2021probnum,
+  title =        {ProbNum: Probabilistic Numerics in Python},
+  author =       {Jonathan Wenger and Nicholas Krämer and Marvin Pförtner and
+                  Jonathan Schmidt and Nathanael Bosch and Nina Effenberger and
+                  Johannes Zenn and Alexandra Gessner and Toni Karvonen and
+                  François-Xavier Briol and Maren Mahsereci and Philipp Hennig},
+  year =         2021,
+  eprint =       {2112.02100},
+  archivePrefix ={arXiv},
+  primaryClass = {cs.MS}
+}

paper/paper.md

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+---
+title: 'ProbNumDiffEq.jl: Probabilistic Numerical Solvers for Ordinary Differential Equations in Julia'
+tags:
+  - Julia
+  - probabilistic numerics
+  - differential equations
+  - Bayesian filtering and smoothing
+  - simulation
+authors:
+  - name: Nathanael Bosch
+    orcid: 0000-0003-0139-4622
+    affiliation: 1
+    corresponding: true
+affiliations:
+ - name: Tübingen AI Center, University of Tübingen, Germany
+   index: 1
+date: 17 July 2024
+bibliography: paper.bib
+---
+
+# Summary
+
+The forces on stars, galaxies, and dark matter under external gravitational
+fields lead to the dynamical evolution of structures in the universe. The orbits
+of these bodies are therefore key to understanding the formation, history, and
+future state of galaxies. The field of "galactic dynamics," which aims to model
+the gravitating components of galaxies to study their structure and evolution,
+is now well-established, commonly taught, and frequently used in astronomy.
+Aside from toy problems and demonstrations, the majority of problems require
+efficient numerical tools, many of which require the same base code (e.g., for
+performing numerical orbit integration).
+
+# Statement of need
+
+`Gala` is an Astropy-affiliated Python package for galactic dynamics. Python
+enables wrapping low-level languages (e.g., C) for speed without losing
+flexibility or ease-of-use in the user-interface. The API for `Gala` was
+designed to provide a class-based and user-friendly interface to fast (C or
+Cython-optimized) implementations of common operations such as gravitational
+potential and force evaluation, orbit integration, dynamical transformations,
+and chaos indicators for nonlinear dynamics. `Gala` also relies heavily on and
+interfaces well with the implementations of physical units and astronomical
+coordinate systems in the `Astropy` package [@astropy] (`astropy.units` and
+`astropy.coordinates`).
+
+`Gala` was designed to be used by both astronomical researchers and by
+students in courses on gravitational dynamics or astronomy. It has already been
+used in a number of scientific publications [@Pearson:2017] and has also been
+used in graduate courses on Galactic dynamics to, e.g., provide interactive
+visualizations of textbook material [@Binney:2008]. The combination of speed,
+design, and support for Astropy functionality in `Gala` will enable exciting
+scientific explorations of forthcoming data releases from the *Gaia* mission
+[@gaia] by students and experts alike.
+
+# Mathematics
+
+Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$
+
+Double dollars make self-standing equations:
+
+$$\Theta(x) = \left\{\begin{array}{l}
+0\textrm{ if } x < 0\cr
+1\textrm{ else}
+\end{array}\right.$$
+
+You can also use plain \LaTeX for equations
+\begin{equation}\label{eq:fourier}
+\hat f(\omega) = \int_{-\infty}^{\infty} f(x) e^{i\omega x} dx
+\end{equation}
+and refer to \autoref{eq:fourier} from text.
+
+# Citations
+
+Citations to entries in paper.bib should be in
+[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html)
+format.
+
+If you want to cite a software repository URL (e.g. something on GitHub without a preferred
+citation) then you can do it with the example BibTeX entry below for @fidgit.
+
+For a quick reference, the following citation commands can be used:
+- `@author:2001`  ->  "Author et al. (2001)"
+- `[@author:2001]` -> "(Author et al., 2001)"
+- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)"
+
+- `@bosch20_calib_adapt_probab_ode_solver`: developed + implemented
+- `@bosch21_pick_and_mix_infor_operat`: developed + implemented
+- `@krämer2021probabilistic`: implemented
+- `@tronarp2022fenrir`: developed + implemented
+- `@bosch2023probabilistic`: developed + implemented
+- `@beck2024diffusion`: developed
+- `@wenger2021probnum`: related software package
+- DALTON: did they compare against my code?
+- BlackBox PN? Probabilistic richardson extrapolation paper?
+- probdiffeq: related code
+
+# Figures
+
+Figures can be included like this:
+![Caption for example figure.\label{fig:example}](figure.png)
+and referenced from text using \autoref{fig:example}.
+
+Figure sizes can be customized by adding an optional second parameter:
+![Caption for example figure.](figure.png){ width=20% }
+
+# Acknowledgements
+
+The authors gratefully acknowledge co-funding by the European Union (ERC, ANUBIS, 101123955. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them). 
+The authors thank the International Max Planck Research School for Intelligent Systems (IMPRS-IS) for supporting Nathanael Bosch.
+
+The authors are grateful to Nicholas Krämer for many valuable discussion and to Jonathan Schmidt for feedback on the manuscript.
+
+We acknowledge contributions from 
+Pietro Monticone (@pitmonticone),
+Vedant Puri (@vpuri3),
+Tim Holy (@timholy),
+Daniel González Arribas (@DaniGlez),
+David Widmann (@devmotion),
+Christopher Rackauckas (@ChrisRackauckas),
+Qingyu Qu (@ErikQQY),
+Cornelius Roemer (@corneliusroemer),
+and Jose Storopoli (@storopoli).
+
+
+# References