Towards analyzing large graphs with quantum annealing and quantum gate computers
This addresses hard graph problems relevant to big data analysis, but it appears incremental as it builds on existing quantum methods and algorithms.
The paper tackled graph community detection and regularity checking using quantum computing, demonstrating capabilities on D-Wave's quantum annealer and simulations, with a new algorithm based on Szemeredi's Regularity Lemma and speed-ups via Grover's algorithm and quantum phase estimation.
The use of quantum computing in graph community detection and regularity checking related to Szemeredi's Regularity Lemma (SRL) are demonstrated with D-Wave Systems' quantum annealer and simulations. We demonstrate the capability of quantum computing in solving hard problems relevant to big data. A new community detection algorithm based on SRL is also introduced and tested. In worst case scenario of regularity check we use Grover's algorithm and quantum phase estimation algorithm, in order to speed-up computations using a quantum gate computers.