  ipie is a Python-based auxiliary-field quantum Monte Carlo (AFQMC) package
that has undergone substantial improvements since its initial release [J. Chem.
Theory Comput., 2022, 19(1): 109-121]. This paper outlines the improved
modularity and new capabilities implemented in ipie. We highlight the ease of
incorporating different trial and walker types and the seamless integration of
ipie with external libraries. We enable distributed Hamiltonian simulations,
allowing for multi-GPU simulations of large systems. This development enabled
us to compute the interaction energy of a benzene dimer with 84 electrons and
1512 orbitals, which otherwise would not have fit on a single GPU. We also
support GPU-accelerated multi-slater determinant trial wavefunctions
[arXiv:2406.08314] to enable efficient and highly accurate simulations of
large-scale systems. This allows for near-exact ground state energies of
multi-reference clusters, [Cu$_2$O$_2$]$^{2+}$ and
[Fe$_2$S$_2$(SCH$_3$)]$^{2-}$. We also describe implementations of free
projection AFQMC, finite temperature AFQMC, AFQMC for electron-phonon systems,
and automatic differentiation in AFQMC for calculating physical properties.
These advancements position ipie as a leading platform for AFQMC research in
quantum chemistry, facilitating more complex and ambitious computational method
development and their applications.
