  Solving optimization problems on near term quantum devices requires
developing error mitigation techniques to cope with hardware decoherence and
dephasing processes. We propose a mitigation technique based on the LHZ
architecture. This architecture uses a redundant encoding of logical variables
to solve optimization problems on fully programmable planar quantum chips. We
discuss how this redundancy can be exploited to mitigate errors in quantum
optimization algorithms. In the specific context of the quantum approximate
optimization algorithm (QAOA), we show that errors can be significantly
mitigated by appropriately modifying the objective cost function.
