  Quantum computing has the potential to solve many complex algorithms in the
domains of optimization, arithmetics, structural search, financial risk
analysis, machine learning, image processing, and others. Quantum circuits
built to implement these algorithms usually require multi-controlled gates as
fundamental building blocks, where the multi-controlled Toffoli stands out as
the primary example. For implementation in quantum hardware, these gates should
be decomposed into many elementary gates, which results in a large depth of the
final quantum circuit. However, even moderately deep quantum circuits have low
fidelity due to decoherence effects and, thus, may return an almost perfectly
uniform distribution of the output results. This paper proposes a different
approach for efficient cost multi-controlled gates implementation using the
quantum Fourier transform. We show how the depth of the circuit can be
significantly reduced using only a few ancilla qubits, making our approach
viable for application to noisy intermediate-scale quantum computers. This
quantum arithmetic-based approach can be efficiently used to implement many
complex quantum gates.
