In mathematics, a Markov odometer is a certain type of topological dynamical system. It plays a fundamental role in ergodic theory and especially in orbit theory of dynamical systems, since a theorem of H. Dye asserts that every ergodic nonsingular transformation is orbit-equivalent to a Markov odometer.[1]
The basic example of such system is the "nonsingular odometer", which is an additive topological group defined on the product space of discrete spaces, induced by addition defined as
x\mapstox+\underline{1}
\underline{1}:=(1,0,0,...)
The general form, which is called "Markov odometer", can be constructed through Bratteli–Vershik diagram to define Bratteli–Vershik compactum space together with a corresponding transformation.
Several kinds of non-singular odometers may be defined.[2] These are sometimes referred to as adding machines.[3] The simplest is illustrated with the Bernoulli process. This is the set of all infinite strings in two symbols, here denoted by
\Omega=\{0,1\}N
\Omega=\prodn\inN\left(Z/knZ\right)
(kn)
kn\ge2.
The odometer for
kn=2
n
The topological entropy of every adding machine is zero. Any continuous map of an interval with a topological entropy of zero is topologically conjugate to an adding machine, when restricted to its action on the topologically invariant transitive set, with periodic orbits removed.
The set of all infinite strings in strings in two symbols
\Omega=\{0,1\}N
l{B}
x\in\Omega
x=(x1,x2,x3, … ).
The Bernoulli process is conventionally endowed with a collection of measures, the Bernoulli measures, given by
\mup(xn=1)=p
\mup(xn=0)=1-p
0<p<1
n
p=1/2
\Omega
\Omega
The space
\Omega
(x+y)n=xn+yn+\varepsilonn\bmod2
\varepsilon0=0
\varepsilonn=\begin{cases} 0&xn-1+yn-1<2\\ 1&xn-1+yn-1=2 \end{cases}
inductively. Increment-by-one is then called the (dyadic) odometer. It is the transformation
T:\Omega\to\Omega
T(x)=x+\underline{1}
\underline{1}:=(1,0,0,...)
T
T\left(1,...,1,0,xk+1,xk+2,...\right)=\left(0,...,0,1,xk+1,xk+2,...\right)
T-1(0,0, … )=(1,1, … )
T
l{B}
T-1(\sigma)\inl{B}
\sigma\inl{B}.
The transformation
T
\mup
\tau:\Omega\to\Omega
\sigma\inl{B}
\mu(\tau-1\sigma)=0
\mu(\sigma)=0
d\mup\circT | |
d\mup |
=\left(
1-p | |
p\right) |
\varphi
\varphi(x)=min\left\{n\inN\midxn=0\right\}-2
T
\mup
The transformation
T
x\in\Omega
n
x
T0,T1, … ,T
2n-1 | |
\{0,1\}n
T
Note that for the special case of
p=1/2
\left(\Omega,l{B},\mu1/2,T\right)
The same construction enables to define such a system for every product of discrete spaces. In general, one writes
\Omega=\prodn\inNAn
An=Z/mnZ=\{0,1,...,mn-1\}
mn\ge2
l{B}
\Omega
l{B}
style\mu=\prodn\inN\mun,
\mun
An
T(x1,...,xk,xk+1,xk+2,...)=(0,...,0,xk+1,xk+1,xk+2,...)
k
xk ≠ mk-1
A special case of this is the Ornstein odometer, which is defined on the space
\Omega=\left(Z/2Z\right) x \left(Z/3Z\right) x \left(Z/4Z\right) x …
\mun(j)=\begin{cases} 1/2&ifj=0\\ 1/2(n+1)&ifj\ne0\\ \end{cases}
A concept closely related to the conservative odometer is that of the abelian sandpile model. This model replaces the directed linear sequence of finite groups constructed above by an undirected graph
(V,E)
v\inV
Z/nZ
n=deg(v)
v
Sandpile models differ from the above definition of a conservative odometer in three different ways. First, in general, there is no unique vertex singled out as the starting vertex, whereas in the above, the first vertex is the starting vertex; it is the one that is incremented by the transition function. Next, the sandpile models in general use undirected edges, so that the wrapping of the odometer redistributes in all directions. A third difference is that sandpile models are usually not taken on an infinite graph, and that rather, there is one special vertex singled out, the "sink", which absorbs all increments and never wraps. The sink is equivalent to cutting away the infinite parts of an infinite graph, and replacing them by the sink; alternately, as ignoring all changes past that termination point.
Let
B=(V,E)
style\coprodn\inNV(n)
V0
style\coprodn\inNE(n)
The diagram includes source surjection-mappings
(n) | |
s | |
n:E |
\toV(n-1)
(n) | |
r | |
n:E |
\toV(n)
e,e'\inE(n)
rn(e)=rn(e')
For such diagram we look at the product space
styleE:=\prodn\inNE(n)
XB:=\left\{x=(xn)n\inN\inE\midxn\inE(n)andr(xn)=s(xn+1)\right\}
Assume there exists only one infinite path
xmax=(xn)n
xn
xmin
TB:XB\toXB
T(xmax)=xmin
x=(xn)n\in ≠ xmax
TB(x1,...,xk,xk+1,...)=(y1,...,yk,xk+1,...)
k
xk
(y1,...,yk)
y1,...,yk-1
yk
xk
TB
XB
Let
P=\left(P(1),P(2),...\right)
P(n)
(n) | |
=\left(p | |
(v,e)\inVn-1 x E(n) |
\right)
(n) | |
p | |
v,e |
>0
v=sn(e)
XB
\muP([e1,...,en])=
(1) | |
p | |
s1(e1),e1 |
…
(n) | |
p | |
sn(en),en |
\left(XB,l{B},\muP,TB\right)
One can show that the nonsingular odometer is a Markov odometer where all the
V(n)