Update the date on the paper.

JOSS/paper.md

@@ -65,10 +65,10 @@ affiliations:
    index: 5
  - name: University of Texas at Austin, 2515 Speedway, Austin, TX 78712, USA
    index: 6
-
 
 
-date: 13 August 2017
+
+date: 13 January 2025
 bibliography: paper.bib
 
 aas-doi:
@@ -77,41 +77,41 @@ aas-journal:
 
 # Summary
 
-SSAPy is a fast and flexible orbit modeling and analysis tool for orbits spanning from 
-low-Earth into the cislunar regime. Orbits can be flexibly specified from common 
-input formats such as Keplerian elements or two-line 
-element data files. SSAPy allows users to model satellites and specify parameters such 
-as satellite area, mass, and drag coefficients. SSAPy includes a customizable force propagation 
-with a range of Earth, Lunar, radiation, atmospheric, and maneuvering models. SSAPy makes 
+SSAPy is a fast and flexible orbit modeling and analysis tool for orbits spanning from
+low-Earth into the cislunar regime. Orbits can be flexibly specified from common
+input formats such as Keplerian elements or two-line
+element data files. SSAPy allows users to model satellites and specify parameters such
+as satellite area, mass, and drag coefficients. SSAPy includes a customizable force propagation
+with a range of Earth, Lunar, radiation, atmospheric, and maneuvering models. SSAPy makes
 use of various community integration methods and can calculate
 time-evolved orbital quantities, including satellite magnitudes and state vectors.
 Users can specify various space- and ground-based observation models with support for
 multiple coordinate and reference frames. SSAPy also supports orbit analysis and
-propagation methods such as multiple hypothesis tracking and has built-in uncertainty quantification. 
-The majority of SSAPy's methods are vectorized and parallelizable, allowing effective use of 
-high performance computer (HPC) systems. Finally, SSAPy has plotting functionality, allowing users to 
-visualize orbits and trajectories, an example of which is shown in Figures 1 and 2. 
+propagation methods such as multiple hypothesis tracking and has built-in uncertainty quantification.
+The majority of SSAPy's methods are vectorized and parallelizable, allowing effective use of
+high performance computer (HPC) systems. Finally, SSAPy has plotting functionality, allowing users to
+visualize orbits and trajectories, an example of which is shown in Figures 1 and 2.
 
-SSAPy has been used for the 
-classification of cislunar [@Higgins2024], and closely-spaced [@Pruett2024], orbits as 
+SSAPy has been used for the
+classification of cislunar [@Higgins2024], and closely-spaced [@Pruett2024], orbits as
 well as for studying the long-term stability of orbits in cislunar space [@Yeager2023]. SSAPy
 has also been used to build a case study for rare events analysis in the context of satellites
-passing close to each other in space [@Miller2022;@Bernstein2021]. 
+passing close to each other in space [@Miller2022;@Bernstein2021].
 
 # Statement of need
 
 Cislunar space is a region between earth out to beyond the Moon's orbit that includes the
 Lagrange points. This region of space is of growing importance to scientific and other space exploration endeavors [e.g., @Duggan2019].
-Understanding, mapping, and modeling orbits through cislunar space is 
-critical to all of these endeavors. The challenge for cislunar orbits is that n-body dynamics (e.g., gravitational forces 
-from the Sun, Earth, Moon and other planets) are significant, leading to unpredictable and chaotic orbital motion. 
-In this chaotic regime, orbits cannot be reduced to simple parametric descriptions making scalable orbit 
+Understanding, mapping, and modeling orbits through cislunar space is
+critical to all of these endeavors. The challenge for cislunar orbits is that n-body dynamics (e.g., gravitational forces
+from the Sun, Earth, Moon and other planets) are significant, leading to unpredictable and chaotic orbital motion.
+In this chaotic regime, orbits cannot be reduced to simple parametric descriptions making scalable orbit
 simulation and modeling a critical analysis tool [@Yeager2023]. Current orbit modeling software tools
 are predominantly used via graphical user interfaces (e.g., The General Mission Analysis Tool; @Hughes2014 or the Systems Tool Kit)
 and are not optimized for large scale simulation on HPC systems. Orbital modeling codes that
 can be run on HPC systems (e.g., REBOUND; @Rein2012) lack full observable generation and modeling capabilities
 with uncertainty quantification. SSAPy, with its full-featured modeling framework and scalable, parallelizable
-functionality, fills the gap in the orbital software landscape. 
+functionality, fills the gap in the orbital software landscape.
 
 
 ![Example SSAPy visualization plot of an orbit ground track over the surface of the Earth. The 48 hour orbit has a semi-major axis of 0.75 GEO (27,000km), an eccentricity 0.2 and an inclination of 45 degrees.](ground_track.png)
@@ -120,13 +120,13 @@ functionality, fills the gap in the orbital software landscape.
 
 # Acknowledgements
 
-`SSAPy` depends on NumPy [@Harris2020], SciPy [@Virtanen2020], matplotlib [@Hunter2007], emcee [@ForemanMackey2013], 
+`SSAPy` depends on NumPy [@Harris2020], SciPy [@Virtanen2020], matplotlib [@Hunter2007], emcee [@ForemanMackey2013],
 astropy [@astropy2022], pyerfa [@Kerkwijk2023], lmfit [@newville2024], and sqp4 [@Vallado2006].
 We would like to thank Robert Armstrong and Iméne Goumiri for valuable contributions to this project.
  This work was performed under the auspices of the U.S.
 Department of Energy by Lawrence Livermore National
 Laboratory (LLNL) under Contract DE-AC52-07NA27344.
-The document number is LLNL-JRNL-871602-DRAFT and the code number is LLNL-CODE-862420. SSAPy was developed with support 
+The document number is LLNL-JRNL-871602-DRAFT and the code number is LLNL-CODE-862420. SSAPy was developed with support
 from LLNL's Laboratory Directed Research and Development Program under projects 19-SI-004 and 22-ERD-054.
 
 # References