Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Counting in Cycles

Version 1 : Received: 21 September 2022 / Approved: 23 September 2022 / Online: 23 September 2022 (14:19:16 CEST)
Version 2 : Received: 12 November 2022 / Approved: 14 November 2022 / Online: 14 November 2022 (10:55:36 CET)

A peer-reviewed article of this Preprint also exists.

Javorszky, K. Counting in Cycles. Information Theories and Applications 2022, 29, 36–99, doi:10.54521/ijita29-01-p02. Javorszky, K. Counting in Cycles. Information Theories and Applications 2022, 29, 36–99, doi:10.54521/ijita29-01-p02.


Counting in terms of cycles allows modeling many processes of Nature. We make use of a slight numerical incongruence within the numbering system to find a translational mechanism which connects sequential ↔ commutative properties of assemblies. The algorithms allow picturing the logical syntax Nature uses when reading the DNA. Ordering a collection on two different properties of its members will impose two differing sequences on the members. The coordinates of a point on a plane of which the axes are the sorting orders sidestep the logical contradiction arising from the different linear assignments. During a reorder, elements aggregate into cycles. Using an etalon collection of simple logical symbols (which are pairs of natural numbers), which we reorder, we see typical movement patterns along the path of the string of elements that are members of the same cycle. We split the {value, position} descriptions of a natural number and observe the places the unit occupies at specific instances of time among its peers, while being a member of a cycle, under different orders prevailing. One cannot lose a bet on the idea that sorting and ordering a collection of elementary logical elements will turn up typical patterns and that these archetypes of patterns will be of interest to Theoretical Physics, Chemistry, Biology, Information Theory, and some other fields, too.


information theory; number theory; theoretical physics; artificial intelligence


Computer Science and Mathematics, Logic

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