In order to compare simulations and observations we traditionally perform inverse modelling, or SED fitting, and compare in some physical property space. An alternative approach is to forward model numerical simulations directly to the observational space. This avoids many of the uncertainties and biases inherent to inverse modelling, and provides a new space to compare and understand our models. I have written codes and performed analysis of forward modelled simulations in a wide range of projects. Most of my time now is spent developing and working with Synthesizer.
Figure showing the various points at which models and observations can be compared, and inverse (green) and forward (blue) modelling approaches.
Synthesizer is a python package for generating synthetic astrophysical observables. It is designed to be modular, extensible, flexible and fast. The code is hosted on Gihub, and comprehensive documentation is provided here.
Flowchart showing some of the main modules and functionality in Synthesizer.
Some papers that have used Synthesizer include (Lovell et al., 2024) and (Newman et al., 2025). Synthesizer is based on codes developed for a number of previous papers, including (missing reference) and (Vijayan et al., 2021). It is also meant to complement full dust radiative transfer approaches, in codes such as Powderday (Narayanan et al., 2021).
References
2025
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Cloudy-Maraston: Integrating nebular continuum and line emission with the Maraston stellar population synthesis models
Sophie L. Newman, Christopher C. Lovell, Claudia Maraston, and 5 more authors
Jan 2025
arXiv:2501.03133 [astro-ph]
The James Webb Space Telescope has ushered in an era of abundant high-redshift observations of young stellar populations characterized by strong emission lines, motivating us to integrate nebular emission into the new Maraston stellar population model which incorporates the latest Geneva stellar evolutionary tracks for massive stars with rotation. We use the photoionization code Cloudy to obtain the emergent nebular continuum and line emission for a range of modelling parameters, then compare our results to observations on various emission line diagnostic diagrams. We carry out a detailed comparison with several other models in the literature assuming different input physics, including modified prescriptions for stellar evolution and the inclusion of binary stars, and find close agreement in the H{}rm }beta H{}rm }alpha [N II]{}lambda 6583 and [S II]{}lambda 6731 luminosities between the models. However, we find significant differences in lines with high ionization energies, such as He II{}lambda\1640 and [O III]{}lambda 5007 due to large variations in the hard ionizing photon production rates. The models differ by a maximum of {}hat{Q}_{}rm [O III]}lambda 5007} = }rm 6 }times 10^9 }; s^{-1} }, M_{}odot}^{-1} where these differences are mostly caused by the assumed stellar rotation and effective temperatures for the Wolf Rayet phase. Interestingly, rotation and uncorrected effective temperatures in our single star population models alone generate [O III] ionizing photon production rates higher than models including binary stars with ages between 1 to 8 Myr. These differences highlight the dependence of derived properties from SED fitting on the assumed model, as well as the sensitivity of predictions from cosmological simulations.
2024
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Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours
Christopher C. Lovell, Tjitske Starkenburg, Matthew Ho, and 9 more authors
Nov 2024
arXiv:2411.13960
We perform the first direct cosmological and astrophysical parameter inference from the combination of galaxy luminosity functions and colours using a simulation based inference approach. Using the Synthesizer code we simulate the dust attenuated ultraviolet–near infrared stellar emission from galaxies in thousands of cosmological hydrodynamic simulations from the CAMELS suite, including the Swift-EAGLE, Illustris-TNG, Simba & Astrid galaxy formation models. For each galaxy we calculate the rest-frame luminosity in a number of photometric bands, including the SDSS {}textit{ugriz} and GALEX FUV & NUV filters; this dataset represents the largest catalogue of synthetic photometry based on hydrodynamic galaxy formation simulations produced to date, totalling \textgreater200 million sources. From these we compile luminosity functions and colour distributions, and find clear dependencies on both cosmology and feedback. We then perform simulation based (likelihood-free) inference using these distributions, and obtain constraints on both cosmological and astrophysical parameters. Both colour distributions and luminosity functions provide complementary information on certain parameters when performing inference. Most interestingly we achieve constraints on {}sigma_8 describing the clustering of matter. This is attributable to the fact that the photometry encodes the star formation–metal enrichment history of each galaxy; galaxies in a universe with a higher {}sigma_8 tend to form earlier and have higher metallicities, which leads to redder colours. We find that a model trained on one galaxy formation simulation generalises poorly when applied to another, and attribute this to differences in the subgrid prescriptions, and lack of flexibility in our emission modelling. The photometric catalogues are publicly available at: https://camels.readthedocs.io/ .
2021
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First Light And Reionization Epoch Simulations (FLARES) – II: The photometric properties of high-redshift galaxies
Aswin P Vijayan, Christopher C Lovell, Stephen M Wilkins, and 5 more authors
MNRAS, Mar 2021
We present the photometric properties of galaxies in the First Light And Reionization Epoch Simulations (FLARES). The simulations trace the evolution of galaxies in a range of overdensities through the epoch of reionization. With a novel weighting scheme, we combine these overdensities, extending significantly the dynamic range of observed composite distribution functions compared to periodic simulation boxes. FLARES predicts a significantly larger number of intrinsically bright galaxies, which can be explained through a simple model linking dust attenuation to the metal content of the interstellar medium, using a line-of-sight extinction model. With this model, we present the photometric properties of the FLARES galaxies for z ∈ [5, 10]. We show that the ultraviolet (UV) luminosity function (LF) matches the observations at all redshifts. The function is fitted by Schechter and double power-law forms, with the latter being favoured at these redshifts by the FLARES composite UV LF. We also present predictions for the UV-continuum slope as well as the attenuation in the UV. The impact of environment on the UV LF is also explored, with the brightest galaxies forming in the densest environments. We then present the line luminosity and equivalent widths of some prominent nebular emission lines arising from the galaxies, finding rough agreement with available observations. We also look at the relative contribution of obscured and unobscured star formation, finding comparable contributions at these redshifts.
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powderday: Dust Radiative Transfer for Galaxy Simulations
Desika Narayanan, Matthew J. Turk, Thomas Robitaille, and 18 more authors
ApJS, Jan 2021
Publisher: American Astronomical Society
We present powderday (available at https://github.com/dnarayanan/powderday), a flexible, fast, open-source dust radiative transfer package designed to interface with both idealized and cosmological galaxy formation simulations. powderday builds on fsps stellar population synthesis models, and hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, allowing significant flexibility in the assumed stellar physics and nebular line emission. The dust content follows either simple observationally motivated prescriptions (i.e., constant dust-to-metals ratios, or dust-to-gas ratios that vary with metallicity), direct modeling from galaxy formation simulations that include dust physics, as well as a novel approach that includes the dust content via learning-based algorithms from the simba cosmological galaxy formation simulation. Active galactic nuclei (AGNs) can additionally be included via a range of prescriptions. The output of these models are broadband (912 Å–1 mm) spectral energy distributions (SEDs), as well as filter-convolved monochromatic images. powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models and seamlessly interfaces with gizmo, arepo, gasoline, changa, and enzo. We demonstrate the capabilities of the code via three applications: a model for the star formation rate–infrared luminosity relation in galaxies (including the impact of AGNs), the impact of circumstellar dust around AGB stars on the mid-infrared emission from galaxy SEDs, and the impact of galaxy inclination angle on dust attenuation laws.
