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dc.contributor.authorAkitaya, Hugo A.
dc.contributor.authorDemaine, Erik D
dc.contributor.authorDemaine, Martin L
dc.contributor.authorHesterberg, Adam Classen
dc.contributor.authorHurtado, Ferran
dc.contributor.authorKu, Jason S
dc.contributor.authorLynch, Jayson R.
dc.date.accessioned2020-11-10T16:20:43Z
dc.date.available2020-11-10T16:20:43Z
dc.date.issued2017-07
dc.date.submitted2015-03
dc.identifier.issn0925-7721
dc.identifier.urihttps://hdl.handle.net/1721.1/128438
dc.description.abstractInspired by the Japanese game Pachinko, we study simple (perfectly “inelastic” collisions) dynamics of a unit ball falling amidst point obstacles (pins) in the plane. A classic example is that a checkerboard grid of pins produces the binomial distribution, but what probability distributions result from different pin placements? In the 50–50 model, where the pins form a subset of this grid, not all probability distributions are possible, but surprisingly the uniform distribution is possible for {1,2,4,8,16} possible drop locations. Furthermore, every probability distribution can be approximated arbitrarily closely, and every dyadic probability distribution can be divided by a suitable power of 2 and then constructed exactly (along with extra “junk” outputs). In a more general model, if a ball hits a pin off center, it falls left or right accordingly. Then we prove a universality result: any distribution of n dyadic probabilities, each specified by k bits, can be constructed using O(nk2) pins, which is close to the information-theoretic lower bound of Ω(nk).en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.comgeo.2017.06.011en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcearXiven_US
dc.titlePachinkoen_US
dc.typeArticleen_US
dc.identifier.citationAkitaya, Hugo A. et al. "Pachinko." Computational Geometry 68 (March 2018): 226-242 © 2017 Elsevier B.V.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalComputational Geometryen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-06-10T11:52:36Z
dspace.date.submission2019-06-10T11:52:37Z
mit.journal.volume68en_US
mit.metadata.statusComplete


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