SPECULATOR: Emulating stellar population synthesis for fast and accurate galaxy spectra and photometry

Understand

We present SPECULATOR - a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry.

• For emulating spectra, we use principal component analysis to construct a set of basis functions, and neural networks to learn the basis coefficients as a function of the SPS model parameters.
• For photometry, we parameterize the magnitudes (for the filters of interest) as a function of SPS parameters by a neural network.
• The resulting emulators are able to predict spectra and photometry under both simple and complicated SPS model parameterizations to percent-level accuracy, giving a factor of $10^3$-$10^4$ speed up over direct SPS computation.