The Fractal Sequence applet defaults to filter method ``T.'' In fact,
any character other than will run this filter method. In our
example, this method replaces every substring ``12'' by the substring
``1,'' and uses the result to drive the chaos game. This means that
the resulting object has points in exactly those addresses that
contain no substring ``21'' (addresses are read in the opposite
direction from sequences).
I believe that the resulting object is a near-fractal. Clearly there
is a good deal of self-similarity: sub-squares ,
, and
are
exact half-scale replicas of the entire object, but this similarity
breaks down for sub-square
. Every attempt (of mine...) to
describe this object using a finite set of affine transformations
misses a small portion. Of course, the fact that I've been unable to
find a suitable finite set of affine transformations doesn't prove
that there are none. However, below (see Section 4) I prove
there there is no `` really nice'' set of affine transformations that
do the job, where by ``really nice'' I mean a finite set of affine
transformations that are each a contraction, whose ranges are not
overlapping, and whose ranges correspond to sub-squares of some finite
size.
If you render this object in the Fractal Sequence applet using
, you'll find that some
addresses appear denser than others. For example, addresses
,
, and
are ``hot spots'' (dense), whereas
,
,
,
and
are considerably sparser (of course
is empty). Does
this reflect the structure of the object, or simply the choice of
probabilities? I think the answer is the latter (the choice of
probabilities) but it may not be possible to choose an optimal set of
s.
Here's my reasoning. Suppose and
are two equal-length
substrings over the digits
. If I denote the
corresponding areas as
, and
(the areas of those
sub-squares with addresses
-reversed and
-reversed), I would
like
. For strings of length
this means that
However ``hot-spots'' remain at addresses ,
, and
. To
see why this occurs, notice that whenever a string
is truncated
by removing the one (or more) trailing
s, a new string
is
created, where
is one of
,
, or
-- the non-
character to the right of the block of
s. So the frequency of
strings
is increased, which corresponds to the number of
points in addresses
. Since these addresses have areas
equivalent to
and
, their relative density
increases.
Is it possible to ``tweak'' the probabilities so that all the
addresses of length
are rendered with equal density? I don't
think so, for the following reason. There are fifteen legal addresses
of length
(address
is generated by a sequence that contains
the forbidden substring). Among these fifteen, addresses
,
,
, and
have
the area of the others, since they each have
a sub-square (e.g.
) removed. Recalling that sequences are read
in the opposite order from addresses, this means that we'd like (after
filtering) to end up with addresses
so that:
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