Half-exponential function

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In mathematics, a half-exponential function is a functional square root of an exponential function>. That is, a function such that composed with itself results in an exponential function: [1] [2]

Contents

for some constants and .

Impossibility of a closed-form formula

If a function is defined using the standard arithmetic operations, exponentials, logarithms, and real-valued constants, then is either subexponential or superexponential. [3] Thus, a Hardy L-function cannot be half-exponential.

Construction

There are infinitely many functions whose self-composition is the same exponential function as each other. In particular, for every in the open interval and for every continuous strictly increasing function from onto , there is an extension of this function to a continuous strictly increasing function on the real numbers such that . [4] The function is the unique solution to the functional equation

Example of a half-exponential function Half-exponential function.png
Example of a half-exponential function

A simple example, which leads to having a continuous first derivative everywhere, is to take and , giving

Application

Half-exponential functions are used in computational complexity theory for growth rates "intermediate" between polynomial and exponential. [2] A function grows at least as quickly as some half-exponential function (its composition with itself grows exponentially) if it is non-decreasing and , for every . [5]

See also

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References

  1. Kneser, H. (1950). "Reelle analytische Lösungen der Gleichung φ(φ(x) = ex und verwandter Funktionalgleichungen". Journal für die reine und angewandte Mathematik . 187: 56–67. MR   0035385.
  2. 1 2 Miltersen, Peter Bro; Vinodchandran, N. V.; Watanabe, Osamu (1999). "Super-polynomial versus half-exponential circuit size in the exponential hierarchy". In Asano, Takao; Imai, Hiroshi; Lee, D. T.; Nakano, Shin{-}Ichi; Tokuyama, Takeshi (eds.). Computing and Combinatorics, 5th Annual International Conference, COCOON '99, Tokyo, Japan, July 26–28, 1999, Proceedings. Lecture Notes in Computer Science. Vol. 1627. Springer. pp. 210–220. doi:10.1007/3-540-48686-0_21. MR   1730337.
  3. van der Hoeven, J. (2006). Transseries and real differential algebra. Lecture Notes in Mathematics. Vol. 1888. Springer-Verlag, Berlin. doi:10.1007/3-540-35590-1. ISBN   978-3-540-35590-8. MR   2262194.. See exercise 4.10, p. 91, according to which every such function has a comparable growth rate to an exponential or logarithmic function iterated an integer number of times, rather than the half-integer that would be required for a half-exponential function.
  4. Crone, Lawrence J.; Neuendorffer, Arthur C. (1988). "Functional powers near a fixed point". Journal of Mathematical Analysis and Applications. 132 (2): 520–529. doi: 10.1016/0022-247X(88)90080-7 . MR   0943525.
  5. Razborov, Alexander A.; Rudich, Steven (1997). "Natural proofs". Journal of Computer and System Sciences . 55 (1): 24–35. doi: 10.1006/jcss.1997.1494 . MR   1473047.