In mathematics, the Champernowne constant C10 is a certain real number, named after mathematician D. G. Champernowne. It is a simple number to construct, which has some important properties.
Normality
Say we have some real number x. We call x normal in base b if the probability of finding some digit string among the digits of x is the same as if we were to search amongst some random sequence of digits. See normal number for a more detailed explanation.
If we denote a digit string as [a0,a1,…], then, in base ten, we would expect strings [0],[1],[2],…,[9] to occur 1/10 of the time, strings [0,0],[0,1],…,[9,8],[9,9] to occur 1/100 of the time, and so on, in a normal number.
Given this definition, is it possible to construct a normal number? Naturally, one would consider concatenating strings [0],[1],[2],…,[9], which would satisfy the first condition, then strings [0,0],[0,1],…,[9,8],[9,9], which would satisfy the second condition, and so on.
This is precisely how the Champernowne constant is defined.
In base 10, we have:
- <math>C_{10} = 0.12345678910111213141516\dots</math>
This is clearly normal in base ten. We can create Champernowne constants that are normal in other bases, similarly, for example:
- <math>C_2 = 0.1\,10\,11\,100\,101\,110\,111\dots {}_2</math>
- <math>C_3 = 0.1\,2\,10\,11\,12\,20\,21\,22\dots {}_3</math>
and so on. The sequence of binary digits in <math>C_2</math> is known as the Champernowne sequence. [1]
Another way of understanding the normality of Champernowne’s constant is to realize that the act of counting itself will ultimately explore every combination of base b digits. That’s what counting is all about.
Computations
Computing Champernowne’s constant can be done by concatenation of bit strings on a computer, but this may not necessarily be the fastest way of computation. Often computing the constant is much faster if one does so purely numerically.[2]
One method of computation includes the calculation of the continued fraction form of a number. Computing this form can help us analyse the number also.
Normally in considering a fraction, we take some real number y and split it into the quotient of two integers a and b so y = a/b, the continued fraction takes a real number y and splits in the following way
- <math> y = a_0+ {1 \over a_1 + {1 \over a_2 + {1 \over a_3 + {1 \over a4 + \ddots } } } }</math>
which we can write more compactly as [a0; a1, a2, …].
For example, consider the exponential constant:
- <math>e=2.718281828\cdots = 2 + {1 \over 1 + {1 \over 2 + {1 \over 1 + {1 \over 1 + \ddots } } } } = [2; 1, 2, 1, 1, 4, 1, 1, 6, 1, 1, \cdots]</math>
The terms in the continued fraction stop after some point if the number is rational, and continue indefinitely if the number is irrational. Clearly Champernowne’s constant is irrational, since rational numbers have a repeating or terminating expansion into digits to the right of the “decimal” (radix) point. So the continued fraction of Champernowne’s constant does not terminate.
If we were to stop the continued fraction after a certain point in an irrational number, we get an approximation to that number by means of a simple fraction. The more terms we take, the more accurate the approximation. For example,
- [2; 1, 2, 1, 1] = 2.714285714, e – [2; 1, 2, 1, 1] = 0.003996114
- [2; 1, 2, 1, 1, 4, 1, 1, 6, 1, 1] = 2.718281718, e – [2; 1, 2, 1, 1, 4, 1, 1, 6, 1, 1] ~ 1.10 ×10–7
If we are to examine the continued fraction of Champernowne’s constant, we get some erratic behaviour. In base 10,
- C10 = [0; 8, 9, 1, 149083, 1, 1, 1, 4, 1, 1, 1, 3, 4, 1, 1, 1, 15,
-
- 4 57540 11139 10310 76483 64662 82429 56118 59960 39397 10457 55500 06620 04393 09026 26592 56314 93795 32077 47128 65631 38641 20937 55035 52094 60718 30899 84575 80146 98631 48833 59214 17830 10987,
- 6, 1, 1, 21, 1, 9, 1, 1, 2, 3, 1, 7, 2, 1, 83, 1, 156, 4, 58, 8, 54, …]
The large number at position 19 has 166 digits.
We get other extremely large numbers as part of the continued fraction if we continue. The next term of the continued fraction is huge, having 2504 digits. This can pose problems in computing the terms of the continued fraction, and may stress weak algorithms for computing the continued fraction. However, the fact that there are such large numbers as part of the continued fraction expansion means that if we take terms up to and onward from these large numbers, we get an exceedingly good approximation in comparison to the terms that did not include the large number. Calling this large number above at position 19 in the continued fraction K, then, for example,
- C10 – [0; 8, 9, 1, 149083, 1, 1, 1, 4, 1, 1, 1, 3, 4, 1, 1, 1, 15] ~ –9 ×10–190
- C10 – [0; 8, 9, 1, 149083, 1, 1, 1, 4, 1, 1, 1, 3, 4, 1, 1, 1, 15, K] ~ 3 ×10–356
which is an improvement in accuracy by 166 orders of magnitude.
A direct computation of Champernowne’s constant for a base b is given by
- <math> C_b = \sum_{n=1}^\infty\frac{\sum_{k=b^{n-1}}^{b^n-1}kb^{-n(k-(b^{n-1}-1))}}{b^{\sum_{k=0}^{n-1}k(b-1)b^{k-1}}} </math>,
(Parkin).
Transcendence
In 1937, Kurt Mahler proved that Champernowne’s constant is transcendental; that is, it is not the root of any polynomial with integer coefficients.
References
- D. G. Champernowne, The construction of decimals normal in the scale of ten, Journal of the London Mathematical Society, vol. 8 (1933), p. 254-260
- K. Mahler, Arithmetische Eigenschaften einer Klasse von Dezimalbrüchen, Proc. Konin. Neder. Akad. Wet. Ser. A. 40 (1937), p. 421-428.
- Rytin, M. Champernowne Constant and Its Continued Fraction Expansion, (1999), http://library.wolfram.com/infocenter/MathSource/2876/
- Parkin, Spencer T., “An Identity for Champernowne’s Constant”, (Not published)
External links
- Champernowne constant at Mathworld