  Based on 4,\,098 very metal-poor (VMP) stars with 6D phase-space and chemical
information from \textit{Gaia} DR3 and LAMOST DR9 as tracers, we apply an
unsupervised machine learning algorithm, Shared Nearest Neighbor (SNN), to
identify stellar groups in the action-energy (\textbf{\textit{J}}-$E$) space.
We detect seven previously known mergers in local samples, including Helmi
Stream, Gaia-Sausage-Enceladus (GSE), Metal-weak Thick Disk (MWTD), Pontus,
Wukong, Thamnos, and I'itoi+Sequoia+Arjuna. According to energy, we further
divide GSE and Wukong into smaller parts to explore the orbital characteristics
of individual fragments. Similarly, the division of Thamnos is based on action.
It can be found that the apocentric distances of GSE parts of high and medium
energy levels are located at $29.5\pm3.6\,{\rm kpc}$ and $13.0\pm2.7\,{\rm
kpc}$, respectively, which suggests that GSE could account for breaks in the
density profile of the Galactic halo at both $\approx30$\,kpc and
$15\text{-}18$\,kpc. The VMP stars of MWTD move along prograde orbits with
larger eccentricities than those of its more metal-rich stars, which indicates
that the VMP part of MWTD may be formed by accreting with dwarf galaxies.
Finally, we summarize all substructures discovered in our local VMP samples.
Our results provide a reference for the formation and evolution of the inner
halo of the Milky Way (MW).

Astrophysics of Galaxies