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Fabius function

From Wikipedia, the free encyclopedia
Nowhere analytic, infinitely differentiable function
Graph of the Fabius function on the interval [0,1].

In mathematics, the Fabius function is an example of an infinitely differentiable function that is nowhere analytic, found by Jaap Fabius (1966).

This function satisfies the initial condition f ( 0 ) = 0 {\displaystyle f(0)=0} {\displaystyle f(0)=0}, the symmetry condition f ( 1 x ) = 1 f ( x ) {\displaystyle f(1-x)=1-f(x)} {\displaystyle f(1-x)=1-f(x)} for 0 x 1 , {\displaystyle 0\leq x\leq 1,} {\displaystyle 0\leq x\leq 1,} and the functional differential equation

f ( x ) = 2 f ( 2 x ) {\displaystyle f'(x)=2f(2x)} {\displaystyle f'(x)=2f(2x)}

for 0 x 1 / 2. {\displaystyle 0\leq x\leq 1/2.} {\displaystyle 0\leq x\leq 1/2.} It follows that f ( x ) {\displaystyle f(x)} {\displaystyle f(x)} is monotone increasing for 0 x 1 , {\displaystyle 0\leq x\leq 1,} {\displaystyle 0\leq x\leq 1,} with f ( 1 / 2 ) = 1 / 2 {\displaystyle f(1/2)=1/2} {\displaystyle f(1/2)=1/2} and f ( 1 ) = 1 {\displaystyle f(1)=1} {\displaystyle f(1)=1} and f ( 1 x ) = f ( x ) {\displaystyle f'(1-x)=f'(x)} {\displaystyle f'(1-x)=f'(x)} and f ( x ) + f ( 1 2 x ) = 2. {\displaystyle f'(x)+f'({\tfrac {1}{2}}-x)=2.} {\displaystyle f'(x)+f'({\tfrac {1}{2}}-x)=2.}

It was also written down as the Fourier transform of

f ^ ( z ) = m = 1 ( cos π z 2 m ) m {\displaystyle {\hat {f}}(z)=\prod _{m=1}^{\infty }\left(\cos {\frac {\pi z}{2^{m}}}\right)^{m}} {\displaystyle {\hat {f}}(z)=\prod _{m=1}^{\infty }\left(\cos {\frac {\pi z}{2^{m}}}\right)^{m}}

by Børge Jessen and Aurel Wintner (1935).

The Fabius function is defined on the unit interval, and is given by the cumulative distribution function of

n = 1 2 n ξ n , {\displaystyle \sum _{n=1}^{\infty }2^{-n}\xi _{n},} {\displaystyle \sum _{n=1}^{\infty }2^{-n}\xi _{n},}

where the ξn are independent uniformly distributed random variables on the unit interval. That distribution has an expectation of 1 2 {\displaystyle {\tfrac {1}{2}}} {\displaystyle {\tfrac {1}{2}}} and a variance of 1 36 {\displaystyle {\tfrac {1}{36}}} {\displaystyle {\tfrac {1}{36}}}.

Extension of the function to the nonnegative real numbers.

There is a unique extension of f to the real numbers that satisfies the same differential equation for all x. This extension can be defined by f (x) = 0 for x ≤ 0, f (x + 1) = 1 − f (x) for 0 ≤ x ≤ 1, and f (x + 2r) = −f (x) for 0 ≤ x ≤ 2r with r a positive integer. The sequence of intervals within which this function is positive or negative follows the same pattern as the Thue–Morse sequence.

The Rvachëv up function[1] is closely related: u ( t ) = { F ( t + 1 ) , | t | < 1 0 , | t | 1 {\displaystyle u(t)={\begin{cases}F(t+1),\quad |t|<1\0,円\quad |t|\geq 1\end{cases}}} {\displaystyle u(t)={\begin{cases}F(t+1),\quad |t|<1\0,円\quad |t|\geq 1\end{cases}}} which fulfills the Delay differential equation [2] d d t u ( t ) = 2 u ( 2 t + 1 ) 2 u ( 2 t 1 ) . {\displaystyle {\frac {d}{dt}}u(t)=2u(2t+1)-2u(2t-1).} {\displaystyle {\frac {d}{dt}}u(t)=2u(2t+1)-2u(2t-1).} (see Another example).

Values

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The Fabius function is constant zero for all non-positive arguments, and assumes rational values at positive dyadic rational arguments. For example:[3] [4]

  • f ( 1 ) = 1 {\displaystyle f(1)=1} {\displaystyle f(1)=1}
  • f ( 1 2 ) = 1 2 {\displaystyle f({\tfrac {1}{2}})={\tfrac {1}{2}}} {\displaystyle f({\tfrac {1}{2}})={\tfrac {1}{2}}}
  • f ( 1 4 ) = 5 72 {\displaystyle f({\tfrac {1}{4}})={\tfrac {5}{72}}} {\displaystyle f({\tfrac {1}{4}})={\tfrac {5}{72}}}
  • f ( 1 8 ) = 1 288 {\displaystyle f({\tfrac {1}{8}})={\tfrac {1}{288}}} {\displaystyle f({\tfrac {1}{8}})={\tfrac {1}{288}}}
  • f ( 1 16 ) = 143 2073600 {\displaystyle f({\tfrac {1}{16}})={\tfrac {143}{2073600}}} {\displaystyle f({\tfrac {1}{16}})={\tfrac {143}{2073600}}}
  • f ( 1 32 ) = 19 33177600 {\displaystyle f({\tfrac {1}{32}})={\tfrac {19}{33177600}}} {\displaystyle f({\tfrac {1}{32}})={\tfrac {19}{33177600}}}
  • f ( 1 64 ) = 1153 561842749440 {\displaystyle f({\tfrac {1}{64}})={\tfrac {1153}{561842749440}}} {\displaystyle f({\tfrac {1}{64}})={\tfrac {1153}{561842749440}}}
  • f ( 1 128 ) = 583 179789679820800 {\displaystyle f({\tfrac {1}{128}})={\tfrac {583}{179789679820800}}} {\displaystyle f({\tfrac {1}{128}})={\tfrac {583}{179789679820800}}}

with the numerators listed in OEISA272755 and denominators in OEISA272757 .

Asymptotic

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log f ( x ) = log 2 x 2 log 2 + log x log ( log x ) log 2 ( 1 2 + 1 + log log 2 log 2 ) log x log 2 ( log x ) 2 log 2 + log log 2 log ( log x ) log 2 + ( 6 γ 2 + 12 γ 1 π 2 6 log 2 log 2 12 log 2 7 log 2 12 log π 2 ) + log 2 ( log x ) 2 log 2 log x log log 2 log ( log x ) log 2 log x + O ( 1 log x ) {\displaystyle {\begin{aligned}\log f(x)&=-{\frac {\log ^{2}x}{2\log 2}}+{\frac {\log x\cdot \log(-\log x)}{\log 2}}-\left({\frac {1}{2}}+{\frac {1+\log \log 2}{\log 2}}\right)\log x-{\frac {\log ^{2}(-\log x)}{2\log 2}}+{\frac {\log \log 2\cdot \log(-\log x)}{\log 2}}\\&+\left({\frac {6\gamma ^{2}+12\gamma _{1}-\pi ^{2}-6\log ^{2}\log 2}{12\log 2}}-{\frac {7\log 2}{12}}-{\frac {\log \pi }{2}}\right)+{\frac {\log ^{2}(-\log x)}{2\log 2\cdot \log x}}-{\frac {\log \log 2\cdot \log(-\log x)}{\log 2\cdot \log x}}+O\!\left({\frac {1}{\log x}}\right)\end{aligned}}} {\displaystyle {\begin{aligned}\log f(x)&=-{\frac {\log ^{2}x}{2\log 2}}+{\frac {\log x\cdot \log(-\log x)}{\log 2}}-\left({\frac {1}{2}}+{\frac {1+\log \log 2}{\log 2}}\right)\log x-{\frac {\log ^{2}(-\log x)}{2\log 2}}+{\frac {\log \log 2\cdot \log(-\log x)}{\log 2}}\\&+\left({\frac {6\gamma ^{2}+12\gamma _{1}-\pi ^{2}-6\log ^{2}\log 2}{12\log 2}}-{\frac {7\log 2}{12}}-{\frac {\log \pi }{2}}\right)+{\frac {\log ^{2}(-\log x)}{2\log 2\cdot \log x}}-{\frac {\log \log 2\cdot \log(-\log x)}{\log 2\cdot \log x}}+O\!\left({\frac {1}{\log x}}\right)\end{aligned}}}

for x 0 + , {\displaystyle x\to 0^{+},} {\displaystyle x\to 0^{+},} where γ {\displaystyle \gamma } {\displaystyle \gamma } is Euler's constant, and γ 1 {\displaystyle \gamma _{1}} {\displaystyle \gamma _{1}} is the Stieltjes constant. Equivalently,

log f ( 2 n ) = n 2 log 2 2 n log n + ( 1 + log 2 2 ) n log 2 n 2 log 2 + ( 6 γ 2 + 12 γ 1 π 2 12 log 2 7 log 2 12 log π 2 ) log 2 n 2 n log 2 2 + O ( 1 n ) {\displaystyle \log f\!\left(2^{-n}\right)=-{\frac {n^{2}\log 2}{2}}-n\log n+\left(1+{\frac {\log 2}{2}}\right)n-{\frac {\log ^{2}n}{2\log 2}}+\left({\frac {6\gamma ^{2}+12\gamma _{1}-\pi ^{2}}{12\log 2}}-{\frac {7\log 2}{12}}-{\frac {\log \pi }{2}}\right)-{\frac {\log ^{2}n}{2n\log ^{2}2}}+O\!\left({\frac {1}{n}}\right)} {\displaystyle \log f\!\left(2^{-n}\right)=-{\frac {n^{2}\log 2}{2}}-n\log n+\left(1+{\frac {\log 2}{2}}\right)n-{\frac {\log ^{2}n}{2\log 2}}+\left({\frac {6\gamma ^{2}+12\gamma _{1}-\pi ^{2}}{12\log 2}}-{\frac {7\log 2}{12}}-{\frac {\log \pi }{2}}\right)-{\frac {\log ^{2}n}{2n\log ^{2}2}}+O\!\left({\frac {1}{n}}\right)}

for n . {\displaystyle n\to \infty .} {\displaystyle n\to \infty .}

References

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