9 citations · 12 across the 7 of their papers we have counts for
8 papers
How bright can a galaxy be? Extreme value predictions for high-redshift survey observables
Christopher C. Lovell, Theodore Martin, Sandro Tacchella +2
Assessing the significance of extreme galaxy candidates has typically relied on redshifts and stellar / halo masses inferred through inverse modelling, which carries substantial sy…
Stellar photoionisation modelling in SYNTHESIZER
Aswin P. Vijayan, Stephen M. Wilkins, Sophie L. Newman +5
Emission from photoionised gas surrounding young stellar populations ( regions) provides critical diagnostics of the physical conditions in star forming galaxies. This…
A Pixel-by-Pixel Path to Population III Discovery with JWST
Patricia Iglesias-Navarro, Thomas Harvey, Marc Huertas-Company +11
The identification of the first generation of metal-free stars, known as Population III (Pop~III), remains a primary goal of modern observational astronomy. While JWST has discover…
Introducing sapphire: Towards Hybrid Physics-Informed, Data-Driven Modeling of Galaxy Formation
Viraj Pandya, Greg L. Bryan, T. Lucas Makinen +18
Semi-analytic models (SAMs) have been treating galaxy populations as dynamical systems for years, but their evolution equations remain poorly constrained. We introduce…
Flexible Simulation Based Inference for Galaxy Photometric Fitting with Synthesizer
Thomas Harvey, Christopher C. Lovell, Sophie Newman +13
We introduce Synference, a new, flexible Python framework for galaxy SED fitting using simulation-based inference (SBI). Synference leverages the Synthesizer package for flexible f…
Galactification: painting galaxies onto dark matter only simulations using a transformer-based model
Shivam Pandey, Christopher C. Lovell, Chirag Modi +1
Connecting the formation and evolution of galaxies to the large-scale structure is crucial for interpreting cosmological observations. While hydrodynamical simulations accurately m…
Synthesizer: a Software Package for Synthetic Astronomical Observables
Christopher C. Lovell, William J. Roper, Aswin P. Vijayan +3
We present Synthesizer, a fast, flexible, modular and extensible platform for modelling synthetic astrophysical observables. Synthesizer can be used for a number of applications, b…
Synthesizer: Synthetic Observables For Modern Astronomy
Will J. Roper, Christopher Lovell, Aswin Vijayan +12
Synthesizer is a fast, flexible, modular, and extensible Python package that empowers astronomers to turn theoretical galaxy models into realistic synthetic observations - includin…