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Correlated electron materials, such as superconductors and magneticmaterials, are regarded as fascinating targets in quantum computing. However,the quantitative resources, specifically the number of quantum gates andqubits, required to perform a quantum algorithm to simulate correlated electronmaterials remain unclear. In this study, we estimate the resources required forthe Hamiltonian simulation algorithm for correlated electron materials,specifically for organic superconductors, iron-based superconductors, binarytransition metal oxides, and perovskite oxides, using the fermionic swapnetwork. The effective Hamiltonian derived using the $ab~initio$ downfoldingmethod is adopted for the Hamiltonian simulation, and a procedure for theresource estimation by using the fermionic swap network for the effectiveHamiltonians including the exchange interactions is proposed. For example, inthe system for the $10^2$ unit cells, the estimated number of gates per Trotterstep and qubits are approximately $10^7$ and $10^3$, respectively, on averagefor the correlated electron materials. Furthermore, our results show that thenumber of interaction terms in the effective Hamiltonian, especially for theCoulomb interaction terms, is dominant in the gate resources when the number ofunit cells constituting the whole system is up to $10^2$, whereas the number offermionic swap operations is dominant when the number of unit cells is morethan $10^3$.

Resource estimations for the Hamiltonian simulation in correlated electron materials