Super-logarithm

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In mathematics, the super-logarithm is one of the two inverse functions of tetration. Just as exponentiation has two inverse functions: roots and logarithms, likewise tetration has two inverse functions: super-roots and super-logarithms. There are several ways of interpreting super-logarithms:

One of the reasons why the super-logarithm has been slow to become standard is that there are several competing definitions. Each of these definitions complement each other in some way, and are all "correct" in some sense. So determining which definition is more "correct" has led to some confusion and debate amongst the mathematical community investigating the super-logarithm.

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[edit] Definitions

The super-logarithm, written \,\mathrm{slog}_b(z), is defined implicitly by

\,\mathrm{slog}_b(b^z) = \mathrm{slog}_b(z) + 1 and
\,\mathrm{slog}_b(1) = 0.

Notice that this definition can only have integer outputs, and will only accept values that will produce integer outputs. The only numbers that this definition will accept are of the form b, b^b, b^{b^b} and so on. In order to extend the domain of the super-logarithm from this sparse set to the real numbers, several approaches have been pursued. These usually include a third requirement in addition to those listed above, which vary from author to author. These approaches are:

  • The linear approximation approach by Rubstov and Romerio,
  • The quadratic approximation approach by Andrew Robbins,
  • The regular Abel function approach by George Szekeres,
  • The iterative functional approach by Peter Walker, and
  • The natural matrix approach by Peter Walker, and later generalized by Andrew Robbins.

[edit] Approximations

Usually, the special functions are defined not only for the real values of argument(s), but to complex plane, and differential and/or integral representation, as well as expansions in convergent and asymptotic series. Yet, no such representaitons are available for the slog function. Nevertheless, the simple approximations below are suggested.

[edit] Linear approximation

The linear approximation to the super-logarithm is:

\mathrm{slog}_b(z) \approx \begin{cases}
\mathrm{slog}_b(b^z) - 1 & \text{if } z \le 0 \\
-1 + z & \text{if } 0 < z \le 1 \\
\mathrm{slog}_b(\log_b(z)) + 1 & \text{if } 1 < z \\
\end{cases}

which is a piecewise-defined function with a linear "critical piece". This function has the property that it is continuous for all real z (C0 continuous). The first authors to recognize this approximation were Rubstov and Romerio, although it is not in their paper, it can be found in their algorithm that is used in their software prototype. The linear approximation to tetration, on the other hand, had been known before, for example by Ioannis Galidakis. This is a natural inverse of the linear approximation to tetration.

Authors like Holmes recognize that the super-logarithm would be a great use to the next evolution of computer floating-point arithmetic, but for this purpose, the function need not be infinitely differentiable. Thus, for the purpose of representing large numbers, the linear approximation approach provides enough continuity (C0 continuity) to ensure that all real numbers can be represented on a super-logarithmic scale.

[edit] Quadratic approximation

The quadratic approximation to the super-logarithm is:

\mathrm{slog}_b(z) \approx \begin{cases}
\mathrm{slog}_b(b^z) - 1 & \text{if } z \le 0 \\
-1 + \frac{2\log(b)}{1+\log(b)}z + 
\frac{1-\log(b)}{1+\log(b)}z^2 & \text{if } 0 < z \le 1 \\
\mathrm{slog}_b(\log_b(z)) + 1 & \text{if } 1 < z
\end{cases}

which is a piecewise-defined function with a quadratic "critical piece". This function has the property that it is continuous and differentiable for all real z (C1 continuous). The first author to publish this approximation was Andrew Robbins in this paper.

This version of the super-logarithm allows for basic calculus operations to be performed on the super-logarithm, without requireing a large amount of solving before-hand. Using this method, basic investigation of the properties of the super-logarithm and tetration can be performed with a small amount of computational overhead.

[edit] Approaches to the Abel function

Main article: Abel function

The Abel function is any function that satisfies Abel's functional equation:

\,A_f(f(x)) = A_f(x) + 1

Given an Abel function Af(x) another solution can be obtained by adding any constant A'f(x) = Af(x) + c. Thus given that the super-logarithm is defined by slogb(1) = 0 and the third special property that differs between approaches, the Abel function of the exponential function could be uniquely determined.

[edit] Regular approach

Szekeres defines the regular Abel function as the logarithm of the regular Schroeder function. The regular Schroeder function is defined as

S_f(x) = \lim_{n\rightarrow\infty} \frac{f^n(x)}{(f'(x_0))^n}

(where fn(x) is functional iteration, and x0 = f(x0) is a fixed point of f(x)) so as to satisfy the functional equation (called Schroeder's functional equation)

\,S_f(f(x)) = (f'(x_0))S_f(x)

So using this, the regular Abel function is defined by

A_f(x) = \frac{\log(S_f(x))}{\log(f'(x_0))}

so as to satisfy the functional equation (called Abel's functional equation)

\,A_f(f(x)) = A_f(x) + 1

Using this approach, the super-logarithm is defined as \mathrm{slog}_b(z) = A_{(\exp_b)}(x), the regular Abel function of bx. This is one of the oldest approaches, and as such it is called the regular approach. So the super-logarithm based on this approach is called the regular super-logarithm. Since the regular approach depends upon a fixed point x0, this is also called the regular super-logarithm about x0, for clarity.

[edit] Other approaches

Other approaches to the super-logarithm do exist, as mentioned above. For example, Peter Walker's approaches, both his iterative approach and his matrix approach are apt at discovering more about the super-logarithm. Until more papers are published on these methods, many aspects of these techniques remain unknown. For more information about these methods, the reader is encouraged to see the references below.

[edit] Properties

Other equations that the super-logarithm satisfies are:

\,\mathrm{slog}_b(z) = \mathrm{slog}_b(\log_b(z)) + 1
\,\mathrm{slog}_b(z) > -2 for all real z

[edit] slog as inverse of tertration

f = sloge(z) in the compex z-plane.
f = sloge(z) in the compex z-plane.

While tetration (or super-exponential) ~{\rm sexp}_b(z)~ is suspected to be analytic finction [1], at least for some values of ~b~, the inverse function slogb=sexpb-1 may be also analytic. Behavior of ~{\rm slog}_b(z)~, defined in such a way, the complex ~z~ plane is scetched in Figure 1 for the case ~b=~e. Levels of integer values of real and integer values of imaginary parts of the slog functions are shown with thick lines. If the existence and uniqueness of the analytic extension of tetration is provided by the condition of its asymptoric approach to the eigenvalues  L \approx 0.318131505204764135312654 + 1.33723570143068940890116{\!~\rm i} and L^*\approx 0.318131505204764135312654 - 1.33723570143068940890116{\!~\rm i} of logarithm ( L = ln(L) ) in the upper and lower parts of the complex plane, then the inverse function should be also unique. such function is real at the real axis. It has two branch points at ~z= L~ and ~z=L^*. It approaches its limiting value − 2 in vicinity of the negative part of the real axis (all the strip between the cuts shown with pink lines in the figure), and slowly grows up along the positive direction of the real axis. As the derivative at the real axis is positive, the imaginary part of slog remains positive just above the real axis and negative just below the real axis. The existence, the unuqueness and the generalizations are under discussion [2].

[edit] See also

[edit] References

  1. ^ Peter Walker (1991). "Infinitely Differentiable Generalized Logarithmic and Exponential Functions". Mathematics of Computation, 57 (196): 723-733. 
  2. ^ Tetration forum, http://math.eretrandre.org/tetrationforum/index.php


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