  Blue Horizontal Branch (BHB) stars, excellent distant tracers for probing the
Milky Way's halo density profile, are distinguished in the $(g-r)_0$ vs
$(i-z)_0$ color space from another class of stars, blue straggler stars (BSs).
We develop a Bayesian mixture model to classify BHB stars using high-precision
photometry data from the Dark Energy Survey Data Release 2 (DES DR2). We select
$\sim2100$ highly-probable BHBs based on their $griz$ photometry and the
associated uncertainties, and use these stars to map the stellar halo over the
Galactocentric radial range $20 \lesssim R \lesssim 70$ kpc. After excluding
known stellar overdensities, we find that the number density $n_\star$ of BHBs
can be represented by a power law density profile $n_\star \propto R^{-\alpha}$
with an index of $\alpha=4.28_{-0.12}^{+0.13}$, consistent with existing
literature values. In addition, we examine the impact of systematic errors and
the spatial inhomogeneity on the fitted density profile. Our work demonstrates
the effectiveness of high-precision $griz$ photometry in selecting BHB stars.
The upcoming photometric survey from the Rubin Observatory, expected to reach
depths 2-3 magnitudes greater than DES during its 10-year mission, will enable
us to investigate the density profile of the Milky Way's halo out to the virial
radius, unravelling the complex processes of formation and evolution in our
Galaxy.
