SENGI: a small, fast, interactive viewer for spectral outputs from stellar population synthesis models

Research output: Contribution to journalArticlepeer-review

Abstract

We present Sengi, (https://christopherlovell.github.io/sengi), an online tool for viewing the spectral outputs of stellar population synthesis (SPS) codes. Typical SPS codes require significant disk space or computing resources to produce spectra for simple stellar populations with arbitrary parameters. This makes it difficult to present their results in an interactive, web-friendly format. Sengi uses Non-negative Matrix Factorisation (NMF) and bilinear interpolation to estimate output spectra for arbitrary values of stellar age and metallicity. The reduced disk requirements and computational expense allows the result to be served as a client-based Javascript application. In this paper we present the method for generating grids of spectra, fitting those grids with NMF, bilinear interpolation across the fitted coefficients, and finally provide estimates of the prediction and interpolation errors.
Original languageEnglish
Article number100444
Number of pages7
JournalAstronomy and Computing
Volume34
DOIs
Publication statusPublished - 8 Jan 2021

Fingerprint

Dive into the research topics of 'SENGI: a small, fast, interactive viewer for spectral outputs from stellar population synthesis models'. Together they form a unique fingerprint.

Cite this