Efficient implementation of the parquet equations: Role of the reducible vertex function and its kernel approximation

We present an efficient implementation of the parquet formalism that respects the asymptotic structure of the vertex functions at both single- and two-particle levels in momentum and frequency space. We identify the two-particle reducible vertex as the core function that is essential for the construction of the other vertex functions. This observation stimulates us to consider a two-level parameter reduction for this function to simplify the solution of the parquet equations. The resulting functions, which depend on fewer arguments, are coined "kernel functions." With the use of the kernel functions, the open boundary of various vertex functions in Matsubara-frequency space can be faithfully satisfied. We justify our implementation by accurately reproducing the dynamical mean-field theory results from momentum-independent parquet calculations. The high-frequency asymptotics of the single-particle self-energy and the two-particle vertex are correctly reproduced, which turns out to be essential for the self-consistent determination of the parquet solutions. The current implementation is also feasible for the dynamical vertex approximation.