  Correlated electron materials, such as superconductors and magnetic
materials, are regarded as fascinating targets in quantum computing. However,
the quantitative resources, specifically the number of quantum gates and
qubits, required to perform a quantum algorithm to simulate correlated electron
materials remain unclear. In this study, we estimate the resources required for
the Hamiltonian simulation algorithm for correlated electron materials,
specifically for organic superconductors, iron-based superconductors, binary
transition metal oxides, and perovskite oxides, using the fermionic swap
network. The effective Hamiltonian derived using the $ab~initio$ downfolding
method is adopted for the Hamiltonian simulation, and a procedure for the
resource estimation by using the fermionic swap network for the effective
Hamiltonians including the exchange interactions is proposed. For example, in
the system for the $10^2$ unit cells, the estimated number of gates per Trotter
step and qubits are approximately $10^7$ and $10^3$, respectively, on average
for the correlated electron materials. Furthermore, our results show that the
number of interaction terms in the effective Hamiltonian, especially for the
Coulomb interaction terms, is dominant in the gate resources when the number of
unit cells constituting the whole system is up to $10^2$, whereas the number of
fermionic swap operations is dominant when the number of unit cells is more
than $10^3$.
