New approaches to the random generation of combinatorial objects

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This project intends to create new methods to generate networks. Networks are useful theoretical combinatorial objects, which also occur in natural contexts such as social networks or the world wide web. Some studies require network simulations and often the best option for this is to generate the networks uniformly at random. Then each one of a given size occurs with the same probability. This project plans to introduce new approaches to performing this task, enabling it to be done efficiently for a much broader range of networks, graphs and other combinatorial objects than before. This would permit better simulations and efficient and truthful sampling, giving better prediction of network properties and better analysis of algorithms applied to networks.