normal numbers and automatic complexity
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Normal numbers and automatic complexity alexander.shen@lirmm.fr, www.lirmm.fr/~ashen LIRMM CNRS & University of Montpellier September 2017, FCT alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity Individual


  1. Normal numbers and automatic complexity alexander.shen@lirmm.fr, www.lirmm.fr/~ashen LIRMM CNRS & University of Montpellier September 2017, FCT alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  2. Individual random sequence alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  3. Individual random sequence If a coin tossing gives 00000 . . . or 01010101 . . . , we become suspicious alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  4. Individual random sequence If a coin tossing gives 00000 . . . or 01010101 . . . , we become suspicious individual sequence of 0 and 1: can it be “random”/“nonrandom”? alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  5. Individual random sequence If a coin tossing gives 00000 . . . or 01010101 . . . , we become suspicious individual sequence of 0 and 1: can it be “random”/“nonrandom”? von Mises (1919): Kollektiv: a basic notion of probability theory; frequency stability alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  6. Individual random sequence If a coin tossing gives 00000 . . . or 01010101 . . . , we become suspicious individual sequence of 0 and 1: can it be “random”/“nonrandom”? von Mises (1919): Kollektiv: a basic notion of probability theory; frequency stability Borel: normal numbers alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  7. Normal numbers alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  8. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  9. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  10. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 # 00 ( n ) = number of occurences of 00 in the first n positions alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  11. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 # 00 ( n ) = number of occurences of 00 in the first n positions # 00 ( n ) + # 01 ( n ) + # 10 ( n ) + # 11 ( n ) = n alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  12. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 # 00 ( n ) = number of occurences of 00 in the first n positions # 00 ( n ) + # 01 ( n ) + # 10 ( n ) + # 11 ( n ) = n normal: # 00 ( n ) / n → 1 / 4 and the same for all other blocks (any length) alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  13. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 # 00 ( n ) = number of occurences of 00 in the first n positions # 00 ( n ) + # 01 ( n ) + # 10 ( n ) + # 11 ( n ) = n normal: # 00 ( n ) / n → 1 / 4 and the same for all other blocks (any length) Another approach: cut the sequence into k -bit blocks and count the number of blocks of each type (aligned occurrences); these two definitions are equivalent alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  14. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 # 00 ( n ) = number of occurences of 00 in the first n positions # 00 ( n ) + # 01 ( n ) + # 10 ( n ) + # 11 ( n ) = n normal: # 00 ( n ) / n → 1 / 4 and the same for all other blocks (any length) Another approach: cut the sequence into k -bit blocks and count the number of blocks of each type (aligned occurrences); these two definitions are equivalent almost all numbers are normal alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  15. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 # 00 ( n ) = number of occurences of 00 in the first n positions # 00 ( n ) + # 01 ( n ) + # 10 ( n ) + # 11 ( n ) = n normal: # 00 ( n ) / n → 1 / 4 and the same for all other blocks (any length) Another approach: cut the sequence into k -bit blocks and count the number of blocks of each type (aligned occurrences); these two definitions are equivalent almost all numbers are normal √ e , π, 2??? Champernowne: 0 1 10 11 100 101 110 . . . alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  16. Normal numbers 00100111010111 . . . # 0 ( n ) = number of 0 among the first n bits simply normal: # 0 ( n ) / n → 1 / 2, # 1 ( n ) → 1 / 2 # 00 ( n ) = number of occurences of 00 in the first n positions # 00 ( n ) + # 01 ( n ) + # 10 ( n ) + # 11 ( n ) = n normal: # 00 ( n ) / n → 1 / 4 and the same for all other blocks (any length) Another approach: cut the sequence into k -bit blocks and count the number of blocks of each type (aligned occurrences); these two definitions are equivalent almost all numbers are normal √ e , π, 2??? Champernowne: 0 1 10 11 100 101 110 . . . Wall: α is normal, n integer ⇒ n α , α/ n normal alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  17. Randomness as incompressibility alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  18. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  19. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment Normality is necessary but hardly sufficient alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  20. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment Normality is necessary but hardly sufficient Martin-L¨ of: random ⇔ obeys all “effective laws” of probability theory alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  21. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment Normality is necessary but hardly sufficient Martin-L¨ of: random ⇔ obeys all “effective laws” of probability theory Kolmogorov, Levin, Chaitin,. . . : randomness = incompressibility of prefixes alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  22. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment Normality is necessary but hardly sufficient Martin-L¨ of: random ⇔ obeys all “effective laws” of probability theory Kolmogorov, Levin, Chaitin,. . . : randomness = incompressibility of prefixes 000 . . . 000 not random: short description: “million zeros” alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  23. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment Normality is necessary but hardly sufficient Martin-L¨ of: random ⇔ obeys all “effective laws” of probability theory Kolmogorov, Levin, Chaitin,. . . : randomness = incompressibility of prefixes 000 . . . 000 not random: short description: “million zeros” What is “description”? Different answers possible alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  24. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment Normality is necessary but hardly sufficient Martin-L¨ of: random ⇔ obeys all “effective laws” of probability theory Kolmogorov, Levin, Chaitin,. . . : randomness = incompressibility of prefixes 000 . . . 000 not random: short description: “million zeros” What is “description”? Different answers possible Normality = weak randomness alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

  25. Randomness as incompressibility Individual random sequences: plausible as outcomes of coin tossing experiment Normality is necessary but hardly sufficient Martin-L¨ of: random ⇔ obeys all “effective laws” of probability theory Kolmogorov, Levin, Chaitin,. . . : randomness = incompressibility of prefixes 000 . . . 000 not random: short description: “million zeros” What is “description”? Different answers possible Normality = weak randomness Limited class of descriptions: finite memory alexander.shen@lirmm.fr, www.lirmm.fr/~ashen Normal numbers and automatic complexity

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