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Numerous but Rare: An Exploration of Magic Squares

How rare are magic squares? So far, the exact number of magic squares of order n is only known for n ≤ 5. For larger squares, we need statistical approaches for estimating the number. For this purpose, we formulated the problem as a combinatorial optimization problem and applied the Multicanonical M...

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Detalles Bibliográficos
Autores principales: Kitajima, Akimasa, Kikuchi, Macoto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431883/
https://www.ncbi.nlm.nih.gov/pubmed/25973764
http://dx.doi.org/10.1371/journal.pone.0125062
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author Kitajima, Akimasa
Kikuchi, Macoto
author_facet Kitajima, Akimasa
Kikuchi, Macoto
author_sort Kitajima, Akimasa
collection PubMed
description How rare are magic squares? So far, the exact number of magic squares of order n is only known for n ≤ 5. For larger squares, we need statistical approaches for estimating the number. For this purpose, we formulated the problem as a combinatorial optimization problem and applied the Multicanonical Monte Carlo method (MMC), which has been developed in the field of computational statistical physics. Among all the possible arrangements of the numbers 1; 2, …, n (2) in an n × n square, the probability of finding a magic square decreases faster than the exponential of n. We estimated the number of magic squares for n ≤ 30. The number of magic squares for n = 30 was estimated to be 6.56(29) × 10(2056) and the corresponding probability is as small as 10−(212). Thus the MMC is effective for counting very rare configurations.
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spelling pubmed-44318832015-05-27 Numerous but Rare: An Exploration of Magic Squares Kitajima, Akimasa Kikuchi, Macoto PLoS One Research Article How rare are magic squares? So far, the exact number of magic squares of order n is only known for n ≤ 5. For larger squares, we need statistical approaches for estimating the number. For this purpose, we formulated the problem as a combinatorial optimization problem and applied the Multicanonical Monte Carlo method (MMC), which has been developed in the field of computational statistical physics. Among all the possible arrangements of the numbers 1; 2, …, n (2) in an n × n square, the probability of finding a magic square decreases faster than the exponential of n. We estimated the number of magic squares for n ≤ 30. The number of magic squares for n = 30 was estimated to be 6.56(29) × 10(2056) and the corresponding probability is as small as 10−(212). Thus the MMC is effective for counting very rare configurations. Public Library of Science 2015-05-14 /pmc/articles/PMC4431883/ /pubmed/25973764 http://dx.doi.org/10.1371/journal.pone.0125062 Text en © 2015 Kitajima, Kikuchi http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kitajima, Akimasa
Kikuchi, Macoto
Numerous but Rare: An Exploration of Magic Squares
title Numerous but Rare: An Exploration of Magic Squares
title_full Numerous but Rare: An Exploration of Magic Squares
title_fullStr Numerous but Rare: An Exploration of Magic Squares
title_full_unstemmed Numerous but Rare: An Exploration of Magic Squares
title_short Numerous but Rare: An Exploration of Magic Squares
title_sort numerous but rare: an exploration of magic squares
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431883/
https://www.ncbi.nlm.nih.gov/pubmed/25973764
http://dx.doi.org/10.1371/journal.pone.0125062
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