Joss paper (#203)

* Initial paper commit

* Updated author list

* suggestions/additions for JOSS paper (#169)

* Fix references

* Update paper.md (#195)

Adding some funding acknowledgements.

* Address JOSS reviewer comments (#198)

Addresses reviewer comments of first pre-review by fixing references
and explaining relation to prior work.

* Fix one word (paper -> package).

* Added a word

* Address reviewer comments

* Split the "Statement of need" section
* Add GROMACS citation

* Address reviewer comment by renaming "Prior work" to "Relation to prior work" for added clarity

* Implement editorial suggestions

Co-authored-by: Michael Shirts <mrshirts@gmail.com>

joss/paper.bib

@@ -0,0 +1,38 @@
+@article{Merz:2018,
+    doi = {10.1371/journal.pone.0202764},
+    author = {{Merz}, Pascal T. and {Shirts}, Michael R.},
+    journal = {PLOS ONE},
+    publisher = {Public Library of Science},
+    title = {Testing for physical validity in molecular simulations},
+    year = {2018},
+    month = {09},
+    volume = {13},
+    url = {https://doi.org/10.1371/journal.pone.0202764},
+    pages = {1-22},
+    number = {9},
+}
+@article{Shirts:2013,
+    doi = {10.1021/ct300688p},
+    author = {{Shirts}, Michael R.},
+    journal = {Journal of Chemical Theory and Computation},
+    title = {Simple Quantitative Tests to Validate Sampling from Thermodynamic Ensembles},
+    year = {2013},
+    volume = {9},
+    url = {https://doi.org/10.1021/ct300688p},
+    pages = {909-926},
+    number = {2},
+}
+@article{Abraham:2015,
+title = {GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers},
+journal = {SoftwareX},
+volume = {1-2},
+pages = {19-25},
+year = {2015},
+issn = {2352-7110},
+doi = {https://doi.org/10.1016/j.softx.2015.06.001},
+url = {https://www.sciencedirect.com/science/article/pii/S2352711015000059},
+author = {Mark James Abraham and Teemu Murtola and Roland Schulz and Szilárd Páll and Jeremy C. Smith and Berk Hess and Erik Lindahl},
+keywords = {Molecular dynamics, GPU, SIMD, Free energy},
+abstract = {GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis tools. Several advanced techniques for free-energy calculations are supported. In version 5, it reaches new performance heights, through several new and enhanced parallelization algorithms. These work on every level; SIMD registers inside cores, multithreading, heterogeneous CPU–GPU acceleration, state-of-the-art 3D domain decomposition, and ensemble-level parallelization through built-in replica exchange and the separate Copernicus framework. The latest best-in-class compressed trajectory storage format is supported.}
+}
+

joss/paper.md

@@ -0,0 +1,141 @@
+---
+title: 'physical_validation: A Python package to assess the physical validity of molecular simulation results'
+tags:
+  - Python
+  - molecular simulation
+  - molecular dynamics
+  - molecular mechanics
+  - statistical mechanics
+  - physical validation
+authors:
+  - name: Pascal T. Merz
+    orcid: 0000-0002-7045-8725
+    affiliation: 1
+  - name: Wei-Tse Hsu
+    affiliation: 1
+  - name: Matt W. Thompson
+    affiliation: 1
+  - name: Simon Boothroyd
+    affiliation: 2
+  - name: Chris C. Walker
+    affiliation: 1
+  - name: Michael R. Shirts
+    orcid: 0000-0003-3249-1097
+    affiliation: 1
+affiliations:
+ - name: Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO 80309, United States of America
+   index: 1
+ - name: Boothroyd Scientific Consulting Ltd., 71-75 Shelton Street, London, United Kingdom
+   index: 2
+date: 7 Jun 2021
+bibliography: paper.bib
+---
+
+# Summary
+
+Molecular simulations such as molecular dynamics (MD) and Monte Carlo (MC)
+simulations are powerful tools allowing the prediction of experimental
+observables in the study of systems such as proteins, membranes, and polymeric
+materials.
+The quality of predictions based on molecular simulations depend on the
+validity of the underlying physical assumptions.
+`physical_validation` allows users of molecular simulation programs to perform
+simple yet powerful tests of physical validity on their systems and setups.
+It can also be used by molecular simulation package developers to run
+representative test systems during development, increasing code correctness.
+The theoretical foundation of the physical validation tests were established
+in [@Merz:2018], in which the `physical_validation` package was first
+mentioned.
+
+# Statement of need
+
+For most of the history of molecular simulation-based research in chemistry, biophysics, 
+physics and engineering, most users of molecular simulation packages were experts that 
+contributed to the code bases themselves or were very familiar with the methodology used.
+Increased popularity of molecular simulation methods has led to a significantly
+increased user base and to an explosion of available methods.
+The simulation packages are faster and more powerful than ever, and even more than before require
+expertise to avoid using combinations of methods and parameters that could violate
+physical assumptions or affect reproducibility.
+Unphysical artifacts have frequently been reported to significantly affect physical observables
+such as the folding of proteins or DNA, the properties of lipid bilayers, the
+dynamics of peptides and polymers, or properties of simple liquids (see [@Merz:2018]
+for further references).
+
+# Functionality
+
+`physical_validation` tackles the problem of robustness in molecular
+simulations at two levels.
+The first level is the end-user level.
+`physical_validation` allows users to test their simulation results for a number
+of deviations from physical assumptions such as the distribution of the kinetic
+energy, the equipartition of kinetic energy throughout the system, the sampling
+of the correct ensemble in the configurational quantities, and the precision of
+the integrator.
+The combination of these tests allow to cover a wide range of potential
+unphysical simulation conditions [@Merz:2018].
+This increases the confidence that users can have in their simulation results
+independently of and in addition to any code correctness tests provided by the developers of their
+simulation package.
+These validation tools explain their assumptions and conclusions using
+comprehensive output and figures, making their use suitable also for users
+new to the field of molecular simulations.
+Since `physical_validation` also returns its conclusions in machine-readable
+form, it can be included in pipelines allowing results to be tested for
+physical validity without user interaction.
+The second level of usage is by code developers. Unphysical behavior might not only result
+from poor or incompatible parameters and models, it might also stem from
+coding errors in the simulation programs.
+`physical_validation` can therefore be used to regularly run representative simulations
+as end-to-end tests in a continuous integration setup, ensuring that code
+changes do not introduce bugs that lead to unphysical results.
+GROMACS [@Abraham:2015], one of the leading MD packages, has been using `physical_validation`
+since 2019 to test every release version with a comprehensive set of
+simulations covering all major code paths.
+
+# Relation to prior work
+
+[@Shirts:2013] and [@Merz:2018] laid the theoretical foundation for
+the `physical_validation` package. [@Shirts:2013] introduced the
+ensemble validation tests, and implemented them in a simple python
+script which was made available accompanied by some examples on
+github.com/shirtsgroup/checkensemble. This script was used as a base
+for the ensemble validation tests in `physical_validation`.
+[@Merz:2018] built upon the previous work by showing that combining
+the ensemble tests with kinetic energy distribution and equipartition
+checks as well as integrator convergence tests could detect many types
+of unphysical simulation conditions. [@Merz:2018] first mentions
+`physical_validation` and its use in the validation of GROMACS
+releases.
+
+In the three years since the publication, the software has matured
+into a stable release. The ensemble tests now also support $\mu VT$
+ensembles, covering the full set of ensembles described in
+[@Shirts:2013]. The user interface, the screen output and the plotting
+functionality were polished based on user feedback. The API was
+improved and is now considered stable, and the package can be
+installed using `conda`, both of which were much requested features
+from users looking to use the package in pipelines automating
+simulation protocols. While the version published in 2018 had no test
+coverage, the stable release is extensively covered by both unit and
+regression tests, reaching a test coverage of above 90%. Finally, the
+documentation was significantly improved based on user feedback.
+
+# Acknowledgements
+
+* Research reported in this publication was supported in part by the
+  National Institute of General Medical Science of the National
+  Institutes of Health under award number R01GM115790 (funding PTM)
+  and R01RGM132386 (funding MTT), and also in part by the National
+  Science Foundation under grant OAC-1835720 (funding WTH) and the
+  U.S. Department of Energy, Office of Science, Office of Basic Energy
+  Sciences, Materials Sciences and Engineering (MSE) Division, under
+  Award Number DE-SC0018651 (funding CCW).
+* The Molecular Sciences Software Institute (MolSSI) for a MolSSI
+  Software Fellowship to Pascal Merz
+* Can Pervane for helpful discussions in the early stages of the
+  project
+* Nate Abraham for careful reading of the documentation
+* Lenny Fobe for help in the setup of the CI
+
+# References