Paparo, G.D.Müller, MarkusComellas, F.Martin-Delgado Alcántara, Miguel Ángel2023-06-192023-06-192014-07-222190-544410.1140/epjp/i2014-14150-yhttps://hdl.handle.net/20.500.14352/35593© Società Italiana di Fisica / Springer-Verlag 2014. This work has been supported by the Spanish MINECO grants, the European Regional Development Fund under projects FIS2012- 33152, MTM2011-28800-C02-01, CAM research consortium QUITEMAD S2009-ESP-1594, European Commission PICC: FP7 2007-2013, Grant No. 249958 and UCM-BS grant GICC-910758 and the U.S. Army Research Office through grant W911NF-14-1-0103.We review the main findings on the ranking capabilities of the recently proposed Quantum PageRank algorithm [1, 2] applied to large complex networks. The algorithm has been shown to identify unambiguously the underlying topology of the network and to be capable of clearly highlighting the structure of secondary hubs of networks. Furthermore, it can resolve the degeneracy in importance of the low lying part of the list of rankings. Examples of applications include real world instances from the WWW, which typically display a scale-free network structure and models of hierarchical networks. The quantum algorithm has been shown to display an increased stability with respect to a variation of the damping parameter, present in the Google algorithm, and a more clearly pronounced power-law behaviour in the distribution of importance among the nodes, as compared to the classical algorithm.engjournal articlehttp://dx.doi.org/10.1140/epjp/i2014-14150-yhttps://link.springer.comhttps://arxiv.org/pdf/1409.3793.pdfopen access53Scale-freeMetabollic networksKey-distributionOrganizationComputationRepeatersDynamicsGraphsWebInformation.Física-Modelos matemáticos