  The amount of sparse asteroid photometry being gathered by both space- and
ground-based surveys is growing exponentially. This large volume of data poses
a computational challenge owing to both the large amount of information to be
processed and the new methods needed to combine data from different sources
(e.g. obtained by different techniques, in different bands, and having
different random and systematic errors). The main goal of this work is to
develop an algorithm capable of merging sparse and dense data sets, both
relative and differential, in preparation for asteroid observations originating
from, for example, Gaia, TESS, ATLAS, LSST, K2, VISTA, and many other sources.
We present a novel method to obtain asteroid phase curves by combining sparse
photometry and differential ground-based photometry. In the traditional
approach, the latter cannot be used for phase curves. Merging those two data
types allows for the extraction of phase-curve information for a growing number
of objects. Our method is validated for 26 sample asteroids observed by the
Gaia mission.
