Determining the Efficiency of Quantum Search Algorithms with the Renormalization Group
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Quantum walks provide a powerful demonstration of the effectiveness of the renormalization group (RG), here applied to find a lower bound on the computational complexity of Grover's quantum search algorithms in low-dimensional networks. For these, the RG reveals a competition between Grover's abstract algorithm, i.e., a rotation in Hilbert space, and quantum transport in an actual geometry. It can be characterized in terms of the quantum walk dimension d^Q_w and the spatial (fractal) dimension d_f, even when translational invariance is broken. The analysis simultaneously determines the optimal time for a quantum measurement and the probability for successfully pin-pointing the sought-after element in the network. The RG further encompasses an optimization scheme, devised by Tulsi, that allows to tune that probability to certainty. Our RG considers entire families of problems to be studied, thereby establishing a large universality class for quantum search, here verified with extensive simulations.
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