Abstract
In the framework of analytic combinatorics, Boltzmann models give rise to efficient algorithms for the random generation of combinatorial objects. This paper proposes an efficient Boltzmann sampler for ordered structures defined by first-order differential specifications. Under an abstract real-arithmetic computation model, our algorithm is of linear complexity for free generation; in addition, for many classical structures, the complexity is also linear when a small tolerance is allowed on the size of the generated object. The resulting implementation makes it possible to generate very large random objects, such as increasing trees, in a few seconds on a standard machine.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
