Uniform Generation of Random Regular Graphs

We develop a new approach for uniform generation of combinatorial objects, and apply it to derive a uniform sampler REG for d-regular graphs. REG can be implemented such that each graph is generated in expected time O(nd3), provided that d = o(√n). Our result significantly improves the previously best uniform sampler, which works efficiently only when d = O(n1/3), with essentially the same running time for the same d. We also give a linear-time approximate sampler REG*, which generates a random d-regular graph whose distribution differs from the uniform by o(1) in total variation distance, when d = o(√n).