The total number of orbitals and the number of orbitals in the OES for N-and O-core with the CC-PCVTZ basis set for different amino acid molecules are depicted in Fig. . A significant truncation of the orbital space occurs with DMET-EOM-CC, which reduces the Hilbert space size and, thus, the computational requirements. Additionally, the truncation of orbital space with two different basis sets is illustrated in Fig. . For N-and O-core, there is an average truncation of 57.4 and 54.5%, respectively, with the DZ basis set, which increases to 67.2 and 65.7%, respectively, with the TZ basis set. This is consistent with the behavior of DMET in other applications: as discussed above, DMET tends to generate proportionally fewer bath orbitals as the size of the AO basis increases. In this application, however, this proportional reduction in bath size is not accompanied by a reduction in accuracy. Because EOM-CCSD and EOM-CCSD* have high polynomial operation-cost scaling, reducing the number of orbitals by a factor of one half to two thirds corresponds to an order of magnitude speedup in end-to-end calculation time. For example, Table shows wall time required for N-or O-core ionization energy calculations on six amino acids using both the canonical and the DMET-based methods while maintaining identical computational resources. We employed a single node with 16 processors and 200 GB of memory.