  Using quantum systems with more than two levels, or qudits, can scale the
computation space of quantum processors more efficiently than using qubits,
which may offer an easier physical implementation for larger Hilbert spaces.
However, individual qudits may exhibit larger noise, and algorithms designed
for qubits require to be recompiled to qudit algorithms for execution. In this
work, we implemented a two-qubit emulator using a 4-level superconducting
transmon qudit for variational quantum algorithm applications and analyzed its
noise model. The major source of error for the variational algorithm was
readout misclassification error and amplitude damping. To improve the accuracy
of the results, we applied error-mitigation techniques to reduce the effects of
the misclassification and qudit decay event. The final predicted energy value
is within the range of chemical accuracy. Our work demonstrates that qudits are
a practical alternative to qubits for variational algorithms.
