The question of how many shuffles are required to randomize an initially ordered deck of cards is a problem that has fascinated mathematicians, scientists, and the general public. The two principal theoretical approaches to the problem, which differed in how each defined randomness, has led to statistically different threshold numbers of shuffles. This paper reports a comprehensive experimental analysis of the card randomization problem for the purposes of determining 1) which of the two theoretical approaches made the more accurate prediction, 2) whether different statistical tests yield different threshold numbers of randomizing shuffles, and 3) whether manual or mechanical shuffling randomizes a deck more effectively for a given number of shuffles. Permutations of 52-card decks, each subjected to sets of 19 successive riffle shuffles executed manually and by an auto-shuffling device were recorded sequentially and analyzed in respect to 1) the theory of runs, 2) rank ordering, 3) serial correlation, 4) theory of rising sequences, and 5) entropy and information theory. Among the outcomes, it was found that: 1) different statistical tests were sensitive to different patterns indicative of residual order; 2) as a consequence, the threshold number of randomizing shuffles could vary widely among tests; 3) in general, manual shuffling randomized a deck better than mechanical shuffling for a given number of shuffles; and 4) the mean number of rising sequences as a function of number of manual shuffles matched very closely the theoretical predictions based on the Gilbert-Shannon-Reed (GSR) model of riffle shuffles, whereas mechanical shuffling resulted in significantly fewer rising sequences than predicted.
KeywordsRandomization of CardsNumber of Riffle ShufflesRising SequencesGSR ModelEntropy and Information
Bayer, D. and Diaconis, P. (1992) Trailing the Dovetail Shuffle to Its Lair. The Annals of Applied Probability, 2 294-313. https://doi.org/10.1214/aoap/1177005705
Trefethen, L.N. and Trefethen, L.M. (2000) How Many Shuffles to Randomize a Deck of Cards? Proceedings of the Royal Society of London. Series A, 456, 2561-2568. https://doi.org/10.1098/rspa.2000.0625
Ogievetsky, O. and Petrova, V. (2018) Cyclotomic Shuffles. Physics of Particles and Nuclei, 49, 867-872. https://doi.org/10.1134/S1063779618050325
Aldous, D. and Diaconis, P. (1986) Shuffling Cards and Stopping Times. The American Mathematical Monthly, 93, 333-348. https://doi.org/10.1080/00029890.1986.11971821
Sanz, A., Sanz-Sanz, C., Gonzalez-Lezana, T., Roncero, O. and Miret-Artes, S. (2012) Quantum Zeno Effect: Quantum Shuffling and Markovianity. Annals of Physics, 327, 1277-1289. https://doi.org/10.1016/j.aop.2011.12.012
Knuth, D.E. (1998) Seminumerical Algorithms. In: The Art of Computer Programming, Vol. 2, 3rd Edition, Addison-Wesley, Boston, 12-15, 145-146.
Wikipedia (2019) Fisher-Yates Shuffle. http://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle#cite_note-knuth3-4
Kolata, G. (1990) In Shuffling Cards, 7 Is a Winning Number. New York Times, 9 January 1990, 1.
Peterson, I. (2000) Disorder in the Deck. Science News Online, 21 October 2000. http://sciencenews.org/articles/20001021/mathtrek.asp
McGinty, J.C. (2018) The Trick behind Properly Shuffling Cards: Casual Players Don’t Typically Randomize the Deck, but a Perfect “Riffle” Also Doesn’t Work. Wall Street Journal, 11 May 2018. http://www.wsj.com/articles/the-trick-behind-properly-shuffling-cards-1526043600
Rehmeyer, J. (2008) Shuffling the Cards: Math Does the Trick. Science News Online, 7 November 2008. http://www.sciencenews.org/article/shuffling-cards-math-does-trick
Silverman, M.P., Strange, W., Silverman, C.R. and Lipscombe, T.C. (1999) Tests of Alpha-, Beta-, and Electron Capture Decays for Randomness. Physics Letters A, 262, 265-273. https://doi.org/10.1016/S0375-9601(99)00668-4
Silverman, M.P., Strange, W., Silverman, C. and Lipscombe, T.C. (2000) Tests for Randomness of Spontaneous Quantum Decay. Physical Review A, 61, Article ID: 042106. https://doi.org/10.1103/PhysRevA.61.042106
Silverman, M.P. and Strange, W. (2000) Experimental Tests for Randomness of Quantum Decay Examined as a Markov Process. Physics Letters A, 272, 1-9. https://doi.org/10.1016/S0375-9601(00)00374-1
Silverman, M.P. (2014) A Certain Uncertainty: Nature’s Random Ways. Cambridge University Press, Cambridge. https://doi.org/10.1017/CBO9781139507370
Weaver, W. (1963) Lady Luck: The Theory of Probability. Doubleday & Company, Garden City, 324-348.
Bernstein, P.L. (1998) Against the Gods: The Remarkable Story of Risk. Wiley, New York, 12-14.
McLeod, J. (2006) Playing-Card Games. International Playing Card Society. https://i-p-c-s.org/faq/games.php
Parlett, D. (1991) A History of Card Games. Oxford University Press, Oxford.
Diaconis, P., Graham, R.L. and Kanton, W.M. (1983) The Mathematics of Perfect Shuffles. Advances in Applied Mathematics, 4, 175-196. https://doi.org/10.1016/0196-8858(83)90009-X
Diaconis, P., McGrath, M. and Pitman, J.W. (1995) Riffle Shuffles, Cycles and Descents. Combinatorica, 15, 11-29. https://doi.org/10.1007/BF01294457
Shannon, C.E. and Weaver, W. (1964) The Mathematical Theory of Communication. University of Illinois Press, Urbana.
Kullback, S. (1968) Information Theory and Statistics. Dover Publications, Mineola.
Stark, D., Ganesh, A. and O’Connell, N. (2002) Information Loss in Riffle Shuffling. Combinatorics, Probability and Computing, 11, 79-95. https://doi.org/10.1017/S0963548301004990
Brillioun, L. (1962) Science and Information Theory. 2nd Edition, Academic Press, New York, 11-22. https://doi.org/10.1063/1.3057866
Gilbert, E.W. (1955) Theory of Shuffling. Bell Laboratories Technical Memorandum, Murray Hill.
Reeds, J. (1981) Unpublished Manuscript. https://en.wikipedia.org/wiki/Gilbert%E2%80%93Shannon%E2%80%93Reeds_model
Diaconis, P., Fulman, J. and Holmes, S. (2013) Analysis of Casino Shelf Shuffling Machines. The Annals of Applied Probability, 4, 1692-1720. https://doi.org/10.1214/12-AAP884
Hald, A. (1952) Statistical Theory with Engineering Applications. Wiley, New York, 342-359.
Wald, A. and Wolfowitz, J. (1940) On a Test Whether Two Samples Are from the Same Population. The Annals of Mathematical Statistics, 11, 147-162. https://doi.org/10.1214/aoms/1177731909
Mood, A.M. (1940) The Distribution Theory of Runs. The Annals of Mathematical Statistics, 11, 367-392. https://doi.org/10.1214/aoms/1177731825
Silverman, M.P., Strange, W., Silverman, C.R. and Lipscombe, T.C. (1999) On the Run: Unexpected Outcomes of Random Events. The Physics Teacher, 37, 218-225. https://doi.org/10.1119/1.880232
Kendall, M.G. and Stuart, A. (1961) The Advanced Theory of Statistics. Vol. 2, Inference and Relationship. Hafner, New York, 474-483. https://doi.org/10.2307/3538355
Altman, D.G. (1991) Practical Statistics for Medical Research. Chapman & Hall/CRC, New York, 296-298.
Walpole, R.E. and Myers, R.H. (1978) Probability and Statistics for Engineers and Scientists. 2nd Edition, Macmillan, New York, 492-495. https://doi.org/10.2307/2530629
Wald, A. and Wolfowitz, J. (1943) An Exact Test for Randomness in the Non-Parametric Case Based on Serial Correlation. The Annals of Mathematical Statistics, 14, 378-388. https://doi.org/10.1214/aoms/1177731358
Hoel, P.G. (1947) Introduction to Mathematical Statistics. Wiley & Sons, New York, 182-183.
Brown, K. (no date) Eulerian Numbers. http://www.mathpages.com/home/kmath012/kmath012.htm
Mann, B. (1994) How Many Times Should You Shuffle a Deck of Cards? UMAP Journal, 15, 303-331. http://www.dartmouth.edu/~chance/teaching_aids/Mann.pdf
Knuth, D.E. (1993) Johann Faulhaber and Sums of Powers. Mathematics of Computation, 61, 277-294. https://doi.org/10.1090/S0025-5718-1993-1197512-7
Arfken, G.B. and Weber, H.J. (2005) Mathematical Methods for Physicists. Academic Press, New York, 376-379, 473-474.
Jaynes, E.T. (1957) Information Theory and Statistical Mechanics. The Physical Review, 106, 620-630. https://doi.org/10.1103/PhysRev.106.620
Rozanov, Y.A. (1969) Introductory Probability Theory. Prentice-Hall, Englewood Cliffs, 115-120.
Ball, P. (2000) Shuffling: What’s the Deal? Nature. https://doi.org/10.1038/news001005-8 http://www.nature.com/news/1998/001005/full/news001005-8.html