## Detalles de publicación

PP 010046

## Spectroscopy from Photometry Using Sparsity. The SDSS Case Study

Instituto de Astrofísica de Canarias

We explore whether medium-resolution stellar spectra can be reconstructed

from photometric observations, taking advantage of the highly compressible nature of the

spectra. We formulate the spectral reconstruction as

a least-squares problem with a sparsity constraint. In our test case using data from the

Sloan Digital Sky Survey, only three broad-band filters are used as input.

We demonstrate that reconstruction using three

principal components is feasible with these filters, leading to differences with respect

to the original spectrum smaller than 5%. We analyze the effect of uncertainties in the observed magnitudes and find

that the available high photometric precision induces very small errors in the reconstruction.

This process may facilitate the extraction of purely spectroscopic

quantities, such as the overall metallicity, for hundreds of millions of stars for which

only photometric information is available, using standard techniques applied

to the reconstructed spectra.

from photometric observations, taking advantage of the highly compressible nature of the

spectra. We formulate the spectral reconstruction as

a least-squares problem with a sparsity constraint. In our test case using data from the

Sloan Digital Sky Survey, only three broad-band filters are used as input.

We demonstrate that reconstruction using three

principal components is feasible with these filters, leading to differences with respect

to the original spectrum smaller than 5%. We analyze the effect of uncertainties in the observed magnitudes and find

that the available high photometric precision induces very small errors in the reconstruction.

This process may facilitate the extraction of purely spectroscopic

quantities, such as the overall metallicity, for hundreds of millions of stars for which

only photometric information is available, using standard techniques applied

to the reconstructed spectra.