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An interval map $F:I\to I$ has a horseshoe when there are an open interval $J\subseteq I$ and disjoint open intervals $K_0,K_1\subseteq J$ such thatIterating inverse branches produces full two-symbol itinerary dynamics.

Yes. There is a computable isomorphism, obtained by an effective back-and-forth construction. Decidability of the two orders makes the usual existence argument into an algorithm.

Maintain a finite order-preserving partial isomorphism of structures $f_s$ from $(\mathbb{N},{<}_A)$ to $(\mathbb{N},{<}_B)$, starting with the empty map. At a forth step, take the least ordinary natural number $a$ outside its domain. Look at the finitely many mapped elements below and above $a$ in ${<}_A$. Their images impose an open interval in ${<}_B$: it lies above all the lower images and below all the upper images, with a missing bound interpreted as an unbounded side.

This interval contains a fresh element. If both bounds exist they are ordered correctly by the induction hypothesis; density supplies an element strictly between them. If there is just one bound, the absence of endpoints supplies an element beyond it; if there are no bounds, choose any element. Density and the absence of endpoints moreover give infinitely many points in every such open interval, so finitely many already used images can always be avoided.

Enumerate $b=0,1,2,\dots$ in the ordinary presentation order, test whether $b$ is unused and satisfies every required ${<}_B$ inequality, and choose the first successful candidate. All tests are decidable, and the existence argument proves termination. Extend $f_s$ by $a\mapsto b$.

At a back step, take the least natural number outside the range, interchange the roles of $A$ and $B$, and carry out exactly the same search for a fresh preimage. Alternate forth and back steps. Every stage is an effective terminating finite computation, and every stage remains an order-preserving partial isomorphism of structures.

Let $f={\bigcup }_s{f}_s$. The least-unused scheduling puts every element of $A$ into the domain and every element of $B$ into the range. For example, after $n+1$ forth steps, all ordinary presentation numbers at most $n$ have been included, since each step removes the least missing one. Thus $f$ is a bijection preserving and reflecting the orders. To compute $f(n)$, simulate the construction until $n$ appears in its domain; this terminates. The corresponding range search computes its inverse. HenceThe searches use the decidable presentations, rather than a possibly ineffective choice of points in an abstract dense linear order without endpoints.

No: the Lebesgue measure can decrease when separate components of the Minkowski sum merge. A one-dimensional example is enough to disprove the assertion in general. TakeThe Minkowski sum $A+tB$ consists of four open intervals, with left endpoints $0,10,2t,10+2t$ and common length $(1+t)/10$. At $t=4$ the four open intervals are disjoint, soAt $t=5$ the middle two open intervals coincide and the remaining three are disjoint, soFor a counterexample in any prescribed dimension $n>1$, take Cartesian products of these open sets with $(0,1)$ in the remaining coordinates. Compare $t_2=5$ with $t_1=5-\delta$, where $\delta ={\delta }_n>0$ is sufficiently small, and choose the interval width $\epsilon >0$ so small that $6\epsilon <2\delta$. The four intervals remain disjoint at $t_1$, givingChoosing $(1-\delta /6{)}^n>3/4$ makes the latter smaller. Here $A_n=((0,\epsilon )\cup (10,10+\epsilon ))\times (0,1{)}^{n-1}$ and $B_n=((0,\epsilon )\cup (2,2+\epsilon ))\times (0,1{)}^{n-1}$. The Brunn–Minkowski inequality gives a lower bound at each value of $t$; it does not give the claimed monotonicity for arbitrary open sets.

An interval map $F:I\to I$ has a horseshoe when there are an open interval $J\subseteq I$ and two disjoint open intervals $K_0,K_1\subseteq J$ such that

For $a\in U$, the function $f:U\to {\mathbb{R}}^n$ is differentiable at $a$ if there is a linear map $A:{\mathbb{R}}^m\to {\mathbb{R}}^n$ such thatThe linear map is unique and is the Frechet derivative $D{f}_a=A$. The function is continuously differentiable at $a$ if it is differentiable on a neighbourhood of $a$ and the map $x\mapsto D{f}_x$, with values in the space of linear maps equipped with the operator norm, is continuous at $a$.

If $T:{\mathbb{R}}^m\to {\mathbb{R}}^n$ is linear, thenConsequently $D{T}_a=T$ at every $a$. The derivative is a constant function of $a$, hence is continuous, so every linear map is continuously differentiable everywhere.

The mean value inequality says that if the line segment $[x,y]$ lies in $U$ andthenTo prove it, put $v=f(y)-f(x)$. The claim is immediate if $v=0$. Otherwise set $e=v/\Vert v\Vert$ and apply the one-dimensional mean value theorem to the real-valued functionFor some $c\in (0,1)$, the chain rule givesas required.

Now suppose that $U$ is open and connected and that $D{f}_a=0$ for every $a\in U$. Every point has an open ball contained in $U$. The mean value inequality with $M=0$ shows that $f$ is constant on each such ball, so $f$ is locally constant. Fix $a_0\in U$. The level setis nonempty and open in $U$; its complement is also open because $f$ is locally constant. Since $U$ is connected, $E=U$. This proves the zero derivative on a connected open set result: $f$ is constant.

The inverse function theorem states that if $f:U\to {\mathbb{R}}^m$ is continuously differentiable, $a\in U$, and $D{f}_a$ is an invertible linear map, then there are open neighbourhoods $V$ of $a$ and $W$ of $f(a)$ such that $f{|}_V:V\to W$ is a bijection whose inverse is continuously differentiable.

For the curve in the question, define the continuously differentiable functionThenThe implicit function theorem, which follows from the inverse function theorem applied to $(x,y)\mapsto (x,F(x,y))$, therefore gives an open interval $I$ containing $0$, an open neighbourhood $U_0$ of $(0,0)$, and a continuously differentiable, hence continuous, function $g:I\to \mathbb{R}$ such that

For $n\ge 0$, putEach $S_n$ is closed, the hypothesis gives $\mathbb{R}={\bigcup }_n{S}_n$, and $E_n\subset E_{n+1}$ because a function that vanishes on an open set has derivative zero there.

The open setis dense. Indeed, inside any nonempty open interval choose a nondegenerate closed subinterval $J$. The complete metric space $J$ is covered by the closed sets $J\cap S_n$, so the Baire's theorem makes one of them contain a relative open interval, which lies in some $E_n$.

On each connected component $I$ of $\Omega$, the function $F$ is one polynomial. To see this, any compact subinterval $K\subset I$ is covered by the increasing family $(E_n)$. A finite subcover therefore gives $K\subset E_N$ for some $N$, and $F^{(N)}=0$ on $K$. Hence $F$ is polynomial on $K$; overlapping compact intervals force these polynomials to agree throughout $I$.

Let $D=\mathbb{R}\setminus \Omega$. This closed set has no isolated points. Otherwise, on the two sides of an isolated point $x$, $F$ would equal polynomials. Smoothness makes all their one-sided derivatives agree at $x$, so the two polynomials are identical and extend across $x$. Some derivative would then vanish on a neighborhood of $x$, contrary to $x\in D$.

Suppose that $D$ is nonempty. It is complete andis a countable closed cover. A second application of Baire's theorem gives an index $k$ and an open interval $U_0$ such thatChoose $x_0\in D\cap U_0$ and a bounded open interval $U$ centred at $x_0$ whose closure lies in $U_0$.

Because $D$ has no isolated points, every $x\in D\cap U$ is approached by distinct points of $D\cap U$. Difference quotients first give $F^{(k+1)}(x)=0$, and induction gives

No component of $\Omega$ meeting $U$ can cross $x_0$, so it has an endpoint in $D\cap U$. If its polynomial had degree $d\ge k$, then its $d$th derivative would approach a nonzero constant at that endpoint, contradicting the preceding display. Its degree is therefore less than $k$, so $F^{(k)}$ also vanishes on the part of that component in $U$. We conclude that $F^{(k)}=0$ throughout $U$, which says $U\subset E_k\subset \Omega$ and contradicts $D\cap U\ne \varnothing$.