Half iterate of 2^x

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what f satisfy the following equation: f(f(x)) = 2^x?
 

Hurkyl

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Is x any real number? Do you want f to be continuous, differentiable, or something else?
 
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x is real. ideally, f is differentiable. i think i may have something. let W(x) be the inverse function for x exp(x). i think
f(x)=exp(W( log(2) x^2 )) might be what i'm looking for... checking it now. oh wait, W is defined only for x>=-1, so let's say that the domain is [-1,oo).

my ultimate goal is to see if i can find a set B such that A<B<2^A for an infinite set A. supposing my f is right, i just have to figure out if exp(W( log(2) A^2 )) can somehow be translated into cardinal arithmetic/infinite sets.
 
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Hurkyl

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I did a quick check in Mathematica, unless I did something wrong that doesn't seem to work.
 
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right. for that f, f(f(0)) != 1 = 2^0...

what's kinda confusing me is that if i assume that f(x)=a^x, where a itself may be a function of x, and i tell mathematica to solve
f(f(x))=2^x, this is the solution it gives but it doesn't work.

what's wrong with the following solution?
we want to solve for a so that a^(a^x)=2^x. if we're assuming f(x)=a^x, then this means that f(f(x))=2^x. actually, we're more interested in finding a^x since this is what f(x) equals.

log both sides to get
(a^x)log(a) = xlog(2)

rewrite a^x as exp(log(a^x)) to get
( exp(log(a^x)) )log(a) = xlog(2)

multiply both sides by x and use xlog(a)=log(a^x) to get
( exp(log(a^x)) )log(a^x) = (x^2)log(2)

use W function to isolate log(a^x):
log(a^x)=W( (x^2)log(2) )

f(x)=a^x=exp(W( (x^2)log(2) )).
***
i think the basic problem is that since a is not a constant, f(f(x)) != a^(a^x). so, if f(x)=a(x)^x, then f(f(x)) would be
a(a(x)^x)^(a(x)^x), not a(x)^(a(x)^x).
 
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Hurkyl

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Yah, my gut tells me right off the bat that a^a^x cannot be a half-iterate of 2^x.


Let g(x) = 2^x

x = 2 is a fixed point of g(x), so it makes sense to define
f(2) := 2

To preserve the fixed point property.


Oh, how about differentiation? Maybe that will help us!

f(f(x)) = g(x)

f'(f(x)) f'(x) = g'(x) = 2^x ln 2

Hrm, it's nonobvious this gets us anywhere. Anyways, if we plug in 2 for x and use our fixed point, we get

f'(2)^2 = 2^2 ln 2
so f'(2) = 2 (ln 2)^(1/2)

I wonder if we can keep going? Let's differentiate again.

2^x (ln 2)^2 = g''(x) = f''(x) f'(f(x)) + f'(x))^2 f''(f(x))
and plugging in x = 2 gives us

4 (ln 2)^2 = f''(2) f'(2) + f'(2)^2 f''(2)

f''(2) = 4(ln 2)^2 / f'(2) / (1 + f'(2))


So we can generate Taylor polynomials for f(x)... I dunno if they will converge or how useful they will be, however.
 
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actually, 2 is not a fixed point of g(x)=2^x. the idea of using taylor series is something i'm trying to avoid if possible. another approach is to use neural networks to approximate f. in this case, a nn with two hidden layers with corresponding values locked to each other would basically produce f. i've also found that f is what is called a half exponential and some dude named Szekeres already talked about it. looking for Szekeres' articles.
 

Hurkyl

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By "2" I mean an actual fixed point of g(x). :smile:

It's complex, though, so the computations for the Taylor coefficients isn't as straightforward as I thought...
 
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Hurkyl

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All right; I think I know a procedure that can generate any strictly increasing continuous function f satisfying f(f(x)) = 2^x.


First, let's extend the domain to include -&infin;; so, of course, 2^(&infin;) = 0.

Choose any (finite) negative number b.

Assign any values you like to f(x) over the range [-&infin;, b] satisfying f(-&infin;) = b, f(b) = 0, and f continuous on [-&infin;, b].

Now, use f(f(x)) = 2^x as a recurrence relation to generate the rest of the values!

E.G.

For any &xi; in [-&infin;, b], set f(f(&xi;)) = 2^&xi;. This assigns values to f(x) in the range [b, 0].

For any &xi; in [b, 0], set f(f(&xi;)) = 2^&xi;. This assigns values to f(x) in the range [0, 2^b]

For any &xi; in [0, 2^b], set f(f(&xi;)) = 2^&xi;. This assigns values to f(x) in the range [2^b, 1].

et cetera

It's clear that this recursion defines f to be strictly increasing and continuous, and f(f(x)) = 2^x. It seems obvious that any such f can be defined in this way, but it's too late at night to give a proof. :smile:
 
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i'd like f to be as smooth as possible.

this is related to the following:
find function A such that A(2^x)=A(x)+1.
then f(x)=Ainv(A(x)+1/2). this is a special case of abel's equation.

by A(-oo), i mean, of course, lim_{x-> -oo} A(x).
let's pretend that A(-oo)=s.

A(2^(-oo))=A(-oo)+1 yields A(0)=s+1.

A(2^0)=A(0)+1 yields A(1)=s+2.

A(2^1)=A(1)+1 yields A(2)=s+3.

A(2^2)=A(2)+1 yields A(4)=s+4.

A(2^3)=A(3)+1 yields A(8)=s+5.

A(2^4)=A(4)+1 yields A(16)=s+6.

a picture of this data is located here:
http://www.alephnulldimension.net/phoenix/pics/pics7/abel.JPG
the hope is to find an A so that the line (x=s) above the x-axis is an asymptote as x-> -oo and that A passes through all the dots.

it looks like A(x)=s+log_2(x)+2 for x>0. let's stick to x>0 for the moment.

Ainv(x)=2^(x-s-2) and
Ainv(A(x)+1/2)=2^((A(x)+1/2)-s-2)=2^(log_2(x)+1/2).
thus, a candidate for f(x) is 2^(log_2(x)+1/2) = SQRT(2)x. of course, it couldn't be this easy: f(f(x))=2x, not 2^x.

if A(x) satisfies A(2^x)=A(x)+1, then so does the function A(x)+c for any constant c. so let's modify the above found A so that A(x)=log_2(x)+c (for x>0). one way to go is to see if we let
f(x)=Ainv(A(x)+1/2), to see if f(f(x))=2^x for any c.

to make a long story short, Ainv(A(x)+1/2)=SQRT(2)x again.

perhaps the problem lies in the fact that if A(x)=log_2(x)+c, A has a singularity at 0 and A(-oo) is not finite.

does a smooth function A exist, defined on R, such that A(-oo) exists and is finite, say equal to s, and A(x)=s+log_2(x)+2 for numbers x that are positive integral powers of 2? is there some kind of canonical solution? if not, how about finding such an A definied on the largest set containing (0,oo). i think what i'm going to to next is try to investigate A(x) for some rational values of x...

in general, A(2^(p/q))=A(p/q)+1, so A(p/q)=A(2^(p/q))-1. this gives some relation for rational inputs of A. if i could find a value of A(1/2) depending only on s and not any other values of A, i would be better off.

we also have that A(-x)=A(2^(-x))-1. if
A(x)=log_2(x)+s+2 for x>0, then for x<0, we have
A(x)=x+s+1. but this would mean that A(-oo)=-oo != s. hmm...

oh, i guess that there's no way A(x)=log_2(x)+s+2 has much hope of working since it doesn't satisfy A(2^x)=A(x)+1.

ok, so log_2(x)+s+2 is ruled out. anything else that's smooth satisfying all the above conditions?

another thought. above, we have relations on A(2^-x) where x>=0 so that A(2^-x)=A(-x)+1. if A is known on the domain D={1/2, 1/4, 1/8, ...} somehow and if it coincided with some holomorphic function on a region G containing 0 and D then A would equal that function on G by the identity theorem (if A is holomorphic). it might help prove that A can't be holomorphic at least on all of G.
 
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NateTG

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For cardinal arithmetic, finding a set B so that
A < B < 2^A
with strict <'s (no equality) and arbitrary A is stronger than disproving the continuum hypothesis and hence proven impossible. (Sorry, no reference links.)

Consider that 2^N=R so you would have
N < B < R

(Disproving the continuum hypothesis.)

So, unless you add some unusual axioms, that's a dead end.

P.S.

Let g(x) = 2^x

x = 2 is a fixed point of g(x), so it makes sense to define
g(2)=2^2=4 so 2 is not a fixed point. I don't think that 2^x has a fixed point in the reals.
 
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one wonders whether this means that such an f doesn't exist, if f isn't applicable to sets, or if f is not strictly increasing on sets.
 

Hurkyl

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I think you made some mistakes, phoenixthoth.

Suppose we have A(-&infin;) = s.

Then
A(0) = A(2^-&infin;) = s + 1
A(1) = A(2^0) = A(0) + 1 = s + 2
A(2) = A(2^1) = A(1) + 1 = s + 3
A(4) = A(2^2) = A(2) + 1 = s + 4
A(8) = A(2^3) = A(3) + 1 = ?

We have no idea what A(3) is, so we can't know A(8). However, we have:

A(16) = A(2^4) = A(4) + 1 = s + 5
A(65536) = A(2^16) = A(16) + 1 = s + 6
A(2^65536) = s + 7
...

And no, A(x) = s + lg lg x + 3 doesn't work either. (lg := log base 2)


A and f sure seem to interact nicely... there's the general identity:

A(f(n)(x)) = A(x) + n/2

where f(n) means you apply f n times.


We can play the same kind of trick with A as we did with f:

Choose any values you want for A on the range [-&infin;, 0] with A(0) = A(-&infin) + 1

Define A on the range [0, 1] by the recursion A(x) = A(lg x) + 1
Define A on the range [1, 2] by the recursion
Define A on the range [2, 4] by the recursion
Define A on the range [4, 8] by the recursion
et cetera


In fact, we can do the following.

Choose your favorite interval of the form [s, 2s).
Define A(x) on the interval [s, 2s) to be anything you like.
Extend A(x) to the rest of the real numbers (and -&infin; if you like) via the recursions A(2^x) = A(x) + 1 and A(x) = A(lg x) + 1.


As for smoothness, I will be impressed if you can prove the existance of an analytic solution for A, but I think you can get A to be infinitely differentiable everywhere.
 
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A(2^(-oo))=A(-oo)+1 yields A(0)=s+1.

A(2^0)=A(0)+1 yields A(1)=s+2.

A(2^1)=A(1)+1 yields A(2)=s+3.

A(2^2)=A(2)+1 yields A(4)=s+4.

A(2^3)=A(3)+1 yields A(8)=s+5.

A(2^4)=A(4)+1 yields A(16)=s+6.
oops! yeah, the second to the last line is incorrect. as you said, it should be A(16)=A(2^4)=A(4)+1=s+5. then the last line should be, as you said, A(65536)=A(2^16)=A(16)+1=s+7.

if g(x)=2^x and g^n(x) is the n-th iterate of g, since A(g(x))=A(x)+1, it looks like we have A(g^(n+1)(x))=A(g^n(x))+1 upon replacement of x by g^n(x). then for n>=0, we have A(g^n(x))=n+A(x) (thus the above lines generalize to A(g^n(0))=n+s+1). then if n=m/2, we have what you said, that A(f^m(x))=m/2+A(x). this is a more general version of something i said earlier, that f(x) would be Ainv(1/2+A(x)).

it doesn't appear to me that looking at abel's equation makes things any easier. it's also conceivable that it's possible to find f even if A(2^x)=1+A(x) has no solution (although it does appear to have *a* solution).

so let's return to f(f(x))=2^x for the moment. for x=-oo, we get f(f(-oo))=0. at this point, it's conceivable that |f(-oo)|=oo. let's take the derivative (now assuming f is differentiable) to get
f'(f(x))f'(x)=(2^x)log(2). letting x=-oo (so to speak) again, we get f'(f(-oo))f'(-oo)=0 which means that f'(f(-oo))=0 or f'(-oo)=0. i don't have a proof for this, but i don't think it's possible to have all three of the following:
1. |f(-oo)|=oo
2. f'(f(-oo))=0
3. f'(-oo)=0.

matters would be easier (though of course that doesn't make it so) if f(-oo)=t for some finite t and f is strictly increasing. that being the case, f(x)>0 for all x and it cannot be the case that
f'(f(-oo))=f'(t)=0, so then f'(-oo)=0 which makes sense if y=t is an asymptote. now this doesn't prove f has an asymptote since this is a circular argument starting with the assumption that f has an asymptote. but let's see what happens with the assumption f(-oo)=t. (i think this leads into the analysis you gave earlier.)

let's stick to the notation g(x)=2^x and g^n is the n-th iterate of g. keep in mind that since f is increasing, t<0.

here's some data (one "for instance" is t=-1):
f(-oo):=t
f(t)=f(f(-oo))=g(-oo)=0
f(0)=f(f(t))=g(t)=2^t
f(g(t))=f(g(t))=f(f(0))=g(0)=1
f(g(0))=f(1)=f(g(0))=f(f(f(0)))=g(f(0))=g(2^t)=g^2(t)
f(g^2(t))=f(f(1))=g(1)=2=g^2(0)
f(g^2(0))=f(2)=f(f(f(1)))=g(f(1))=g(g^2(t))=g^3(t)
f(g^3(t))=f(f(2))=g(2)=4=g^3(0)
f(g^3(0))=f(f(g^3(t)))=g^4(t)

it looks like we have the following pattern:
f(g^n(0))=g^(n+1)(t)
f(g^n(t))=g^n(0).

we've got an infinite amount of data about f now and perhaps some curve-fit search is in order. perhaps i'll start with t=-1 and see what happens. perhaps each t<0 gives rise to another solution f or perhaps there is only one t for which there is an f or perhaps there is no f for any t. i'm wondering if f retains its arbitaryness you speak of if the condition that f is differentiable is kept.
 
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here's a relevant article by kevin iga:

it's also true that f is a function that commutes with g. are there any nice/helpful characterizations of functions that commute with g(x)=2^x?
 
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"progress"

a series for [tex]g\left( x\right) =2^{x}[/tex] centered at zero is [tex]g_{n}\left( x\right) =\sum_{k=0}^{n}\frac{\left( \log 2\right) ^{k}}{k!}x^{k}[/tex].

if i let [tex]f_{3}(x)=\sum_{k=0}^{3}a_{k}x^{k}=\sum_{k=0}^{3}\frac{b_{k}}{k!}x^{k}[/tex], compute [tex]f_{3}\left( f_{3}\left( x \right) \right) [/tex], ignore terms of order higher than 3, and equate to [tex]g_{3}[/tex], i get the following approximations:

[tex]\begin{tabular}{ccc}
$k$ & $a_{k}$ & $b_{k}$ \\
0 & 0.544772 & 0.544772 \\
1 & 0.748014 & 0.748014 \\
2 & 0.154587 & 0.309174 \\
3 & 0.0114634 & 0.0687804
\end{tabular}[/tex]

btw, [tex]a_{0}\approx \frac{1}{1+\sqrt{\log 2}}[/tex]. the relative difference between [tex]f_{3}\circ f_{3}[/tex] and [tex]g[/tex] in [tex]\left[ -2.5,6.6\right] [/tex] is under about 5%. since [tex]f\left( f\left( -\infty \right) \right) =0[/tex], [tex]
f_{3}\left( -\infty \right) \approx f_{3}^{-1}\left( 0\right) \approx
-0.876858[/tex]. since this value is in [tex]\left[ -2.5,6.6\right] [/tex], it is probably close. this suggests the range of [tex]f[/tex] is something like [tex]\left( -0.876858,\infty \right) [/tex]. i also know that [tex]x<f\left( x\right) <g\left( x\right) [/tex] for all [tex]x[/tex]. [tex]g_{3}\left( x\right) \approx
1+0.693147x+0.240227x^{2}+0.0555041x^{3}[/tex] and [tex]f_{3}\left( f_{3}\left( x\right) \right) \approx 1+0.693147x+0.240227x^{2}+0.0555041x^{3}[/tex].

abel's equation. if [tex]A[/tex] is a function satisfying [tex]g\left( x\right) =A^{-1}\left( A\left( x\right) +1\right) [/tex] and [tex]f\left( x\right) =A^{-1}\left( A\left( x\right) +\frac{1}{2}\right) [/tex], then [tex]f\circ f=g[/tex]. if [tex]A[/tex] satisfies this version of abel's equation ([tex]g\left( x\right)
=A^{-1}\left( A\left( x\right) +1\right) [/tex]), then so does [tex]A+c[/tex] for any constant [tex]c[/tex]. therefore, without loss of generality, we can assume that [tex]A\left( 0\right) =0[/tex]. then if we assume [tex]A_{n}\left( x\right) =\sum_{k=0}^{n}a_{k}x^{k}=\sum_{k=0}^{n}\frac{b_{k}}{k!}x^{k}[/tex] and say [tex]A_{6}^{-1}\circ \left( A_{6}+1\right) =g_{6}[/tex], i get the following
approximations for the [tex]a_{k}[/tex] and [tex]b_{k}[/tex]:

[tex]\begin{tabular}{ccc}
$k$ & $a_{k}$ & $b_{k}$ \\
0 & 0 & 0 \\
1 & 0.783476 & 0.783476 \\
2 & 0.261744 & 0.523487 \\
3 & -0.0122861 & -0.0737167 \\
4 & -0.0491509 & -1.17962 \\
5 & 0.0175623 & 2.10748 \\
6 & 0.0313423 & 22.5665
\end{tabular}
[/tex]
[tex]A_{6}^{-1}\left( x\right) \approx
1.27636x-0.54425x^{2}+0.496751x^{3}-0.397809x^{4}+0.215844x^{5}-0.0468988x^{6} [/tex] and [tex]A_{6}^{-1}\left( A_{6}\left( x\right) +1\right) \approx 1+0.693147x+0.240227x^{2}+0.0555041x^{3}+0.00961812x^{4}+0.00133335x^{5}[/tex] while [tex]g_{5}\left( x\right) \approx 1+0.693147x+0.240227x^{2}+0.0555041x^{3}+0.00961813x^{4}+0.00133336x^{5}[/tex]. [tex]A_{6}^{-1}\left( A_{6}\left( x\right) +\frac{1}{2}\right) \approx 0.545362+0.755607x+0.148081x^{2}-0.0221803x^{3}-0.00908802x^{4}+0.0532461x^{5} [/tex]. note the comparison to [tex]f_{3}[/tex] above. seems as though that [tex]f_{3}[/tex] is a better approximation.

it's kinda weird how [tex]f_{3}[/tex] looks like an exponential but [tex]\log f_{3}[/tex] looks like a log.
 
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schröder's equation

a perhaps nicer related functional equation is schröder's equation. given [tex]g[/tex], the goal is to find a function [tex]s[/tex] such that for a nonzero constant [tex]\mu[/tex], [tex]s \circ g= \mu s[/tex]. if [tex]s[/tex] is invertible and the domains/ranges match up right, then [tex]g^{m} \left( x \right) =s^{-1} \left( \mu ^{m} s \left( x \right) \right)[/tex]. the solutions to schröder's equation form a vector space, a kind of eigenspace.

there is a relationship between the set of solutions to schröder's equation and the set of solutions to abel's equation given by the [tex]log[/tex] function. at least when domains are possibly complex, the solution set of one is empty if and only if the solution set of the other is empty.
 
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does anyone have access to springer articles?

can you send link.springer.de/link/service/journals/00010/bibs/1061001/10610001.htm[/URL] to [email]phoenix@alephnulldimension.net[/email]?
 
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Assign any values you like to f(x) over the range [-oo, b] satisfying f(-oo) = b, f(b) = 0, and f continuous on [-oo, b].
a similar thing was done with abel's equation. now i get how definining f or the solution to abel's/schroeder's equation on some interval will then lock in place all other values but i don't think this can be done in an arbitrary way. how is it ensured, for example, that the arbitrary assignment of values to f over the range [-oo,b] will lead to satisfaction of f(f(x))=2^x?

btw, from my estimates, b should be about -0.88 and f(0) should be about 0.545.
 
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