[Paper Review] The 2023 release of Cloudy

Marios Chatzikos, S. Bianchi+9 more|arXiv (Cornell University)|Aug 11, 2023

Machine Learning in Materials ScienceMaterials Science3 citations

TL;DR

The 2023 release of Cloudy (C23) introduces major upgrades to atomic and molecular data, including migration to Git version control enabling annual releases, enhanced Chianti (v10), improved H- and He-like collisional rates, updated LAMDA molecular data, and recent UDfA/KiDA reaction rates. It also advances X-ray capabilities for XRISM and Athena missions, with new features like $F_\lambda$ unit support, customizable line blends, and improved SED grid handling, significantly boosting accuracy and usability for astrophysical spectral modeling.

ABSTRACT

We describe the 2023 release of the spectral synthesis code Cloudy. Since the previous major release, migrations of our online services motivated us to adopt git as our version control system. This change alone led us to adopt an annual release scheme, accompanied by a short release paper, the present being the inaugural. Significant changes to our atomic and molecular data have improved the accuracy of Cloudy predictions: we have upgraded our instance of the Chianti database from version 7 to 10; our H- and He-like collisional rates to improved theoretical values; our molecular data to the most recent LAMDA database, and several chemical reaction rates to their most recent UDfA and KiDA values. Finally, we describe our progress on upgrading Cloudy's capabilities to meet the requirements of the X-ray microcalorimeters aboard the upcoming XRISM and Athena missions, and outline future development that will make Cloudy of use to the X-ray community.

Motivation & Objective

• Address the need for more frequent, transparent, and reproducible updates to the Cloudy spectral synthesis code by adopting an annual release cycle.
• Improve the accuracy of spectral predictions by integrating the latest atomic and molecular databases, including Chianti v10, updated collisional rates, and LAMDA molecular data.
• Enhance Cloudy's capabilities to model X-ray emission from astrophysical plasmas, particularly for upcoming missions like XRISM and Athena.
• Modernize the codebase and user interface by migrating to Git, introducing new commands (e.g., set blend), and improving data handling for SED grids and abundances.
• Support high-precision astrophysical spectroscopy by advancing atomic data quality, including laboratory-grade wavelengths and accurate transition probabilities.

Proposed method

• Adopted Git as the version control system to enable frequent, stable, and traceable code updates, facilitating an annual release schedule.
• Upgraded internal atomic data to Chianti v10, incorporating the latest theoretical and observational results for ionized species.
• Integrated improved collisional excitation rates for H- and He-like ions using updated theoretical models.
• Updated molecular data to the most recent LAMDA database and reaction rates to the latest UDfA and KiDA values.
• Enhanced X-ray modeling by extending treatment of fine-structure transitions and preparing for microcalorimeter data from XRISM and Athena.
• Introduced new user commands such as 'set blend' to define custom line blends, and enabled $F_\lambda$ units in output, with backward compatibility for $F_\nu$ and $\nu F_\nu$.

Experimental results

Research questions

• RQ1 How can the Cloudy spectral synthesis code be modernized to support more frequent, transparent, and reproducible releases?
• RQ2 What improvements in atomic and molecular data are necessary to enhance the accuracy of spectral predictions for astrophysical plasmas?
• RQ3 How can Cloudy be adapted to meet the high-resolution X-ray requirements of upcoming missions like XRISM and Athena?
• RQ4 What software and infrastructure changes are needed to improve user flexibility and performance in SED grid handling and line emission modeling?
• RQ5 What future developments are required to support time-dependent simulations and advanced radiative transfer in Cloudy?

Key findings

• The 2023 release (C23) marks the first in an annual release cycle, enabled by migration to Git, improving code maintainability and user transparency.
• Chianti database was upgraded from version 7 to 10, significantly improving ionization and emission line predictions for astrophysical plasmas.
• H- and He-like collisional excitation rates were updated to more accurate theoretical values, enhancing modeling of collisionally excited lines.
• Molecular data were updated to the latest LAMDA database, improving accuracy in modeling molecular emission in cool and dense environments.
• Reaction rates for key chemical processes were updated to the most recent UDfA and KiDA values, improving predictions in photodissociation regions and interstellar medium.
• New features include support for $F_\lambda$ units in output, customizable line blends via the 'set blend' command, and improved SED grid handling with optional binary indexing for performance.