@article{lovell_sengi_2021,
	title = {Sengi: {A} small, fast, interactive viewer for spectral outputs from stellar population synthesis models},
	volume = {34},
	issn = {2213-1337},
	shorttitle = {Sengi},
	url = {http://www.sciencedirect.com/science/article/pii/S2213133720300986},
	doi = {10.1016/j.ascom.2020.100444},
	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.},
	language = {en},
	urldate = {2021-01-14},
	journal = {Astronomy and Computing},
	author = {Lovell, C. C.},
	month = jan,
	year = {2021},
	keywords = {Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
	pages = {100444},
}

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