The <scp>HyLight</scp> model for hydrogen emission lines in simulated nebulae

Abstract Hydrogen recombination lines provide key diagnostics of ionized gas in galaxies, yet most hydrodynamical simulations estimate hydrogen level populations using interpolated emissivity tables rather than computing them directly from local physical conditions. We present HyLight, a Python-based atomic model that calculates hydrogen level populations and line emissivities from the gas density, temperature, and ionization state, enabling accurate predictions in both equilibrium and non-equilibrium environments. Benchmark comparisons show that HyLight reproduces Cloudy predictions for Balmer, Paschen, and Brackett emissivities to within 1percnt under typical photoionized nebular conditions, while discrepancies of several tens of per cent arise relative to other published calculations. As an illustrative application, we use HyLight to compute photoionization-to-line intensity ratios in an H ii nebula and generate synthetic hydrogen emission maps from a radiation-hydrodynamical simulation that includes non-equilibrium thermochemistry. Combining physical consistency with flexibility, HyLight provides a robust framework for connecting hydrodynamical simulations with observational diagnostics of photoionized regions, and enhances our ability to interpret hydrogen emission in complex, non-equilibrium astrophysical environments.

Authors

Institutions

Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2026-03-05
DOI
https://doi.org/10.1093/mnras/stag429
Primary Topic
Astrophysics and Star Formation Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The HyLight model for hydrogen emission lines in simulated nebulae

Alexander J. Richings, T K Chan, Tom Theuns, Yuankang Liu et al.
Monthly Notices of the Royal Astronomical Society
Astrophysics and Star Formation Studies
article

The HyLight model for hydrogen emission lines in simulated nebulae

Alexander J. Richings, T K Chan, Tom Theuns, Yuankang Liu, Anna Faye McLeod
article en

Abstract

Abstract Hydrogen recombination lines provide key diagnostics of ionized gas in galaxies, yet most hydrodynamical simulations estimate hydrogen level populations using interpolated emissivity tables rather than computing them directly from local physical conditions. We present HyLight, a Python-based atomic model that calculates hydrogen level populations and line emissivities from the gas density, temperature, and ionization state, enabling accurate predictions in both equilibrium and non-equilibrium environments. Benchmark comparisons show that HyLight reproduces Cloudy predictions for Balmer, Paschen, and Brackett emissivities to within 1percnt under typical photoionized nebular conditions, while discrepancies of several tens of per cent arise relative to other published calculations. As an illustrative application, we use HyLight to compute photoionization-to-line intensity ratios in an H ii nebula and generate synthetic hydrogen emission maps from a radiation-hydrodynamical simulation that includes non-equilibrium thermochemistry. Combining physical consistency with flexibility, HyLight provides a robust framework for connecting hydrodynamical simulations with observational diagnostics of photoionized regions, and enhances our ability to interpret hydrogen emission in complex, non-equilibrium astrophysical environments.

Monthly Notices of the Royal Astronomical Society
Chinese University of Hong Kong (HK), Durham University (GB), University of Hull (GB), University of Chicago (US)
UK Research and Innovation, European Commission, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 34%
Astrophysics and Star Formation Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.