\documentclass[reqno]{amsart}
\usepackage{hyperref}

\AtBeginDocument{{\noindent\small
{\em Electronic Journal of Differential Equations},
Vol. 2006(2006), No. 90, pp. 1--21.\newline
ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu
\newline ftp ejde.math.txstate.edu  (login: ftp)}
\thanks{\copyright 2006 Texas State University - San Marcos.}
\vspace{9mm}}

\begin{document}
\title[\hfilneg EJDE-2006/90\hfil Boundary-value problems]
{Boundary-value problems for Hamiltonian systems and absolute
minimizers \\ in calculus of variations}

\author[V. N. Kolokol'tsov, A. E. Tyukov\hfil EJDE-2006/90\hfilneg]
{Vassili N. Kolokol'tsov, Alexey E. Tyukov}  % in alphabetical order

\address{Vassili N. Kolokol'tsov \newline
 Dept of Statistics, University of Warwick, Coventry CV4 7AL, United Kingdom}
\email{v.kolokoltsov@warwick.ac.uk}

\address{Alexey E. Tyukov \newline
Cardiff School of Mathematics,
Cardiff University, Senghennydd Road, Cardiff, CF24 4AG, United Kingdom}
\email{tyukovA@cardiff.ac.uk, tyukov@yahoo.co.uk}

\date{}
\thanks{Submitted November 14, 2005. Published August 15, 2006.}
\subjclass[2000]{49J99, 34B15}
\keywords{Hamiltonian systems; absolute minimizers;
 global field of extremals; \hfill\break\indent WKB method}


\begin{abstract}
 We apply the method of  Hamilton shooting to obtain the
 well-posedness of boundary value problems  for certain Hamiltonian
 systems and some estimates for their solutions. The examples of
 Hamiltonian functions covered by the method include elliptic
 polynomials and exponentially growing functions. As a consequence we
 prove global existence, smoothness and almost everywhere uniqueness
 of absolute minimizers in the corresponding problem of calculus of
 variations and hence construct the global field of extremals.
\end{abstract}

\maketitle
\numberwithin{equation}{section}
\newtheorem{theorem}{Theorem}[section]
\newtheorem{lemma}[theorem]{Lemma}
\newtheorem{proposition}[theorem]{Proposition}
\newtheorem{corollary}[theorem]{Corollary}
\newtheorem{remark}[theorem]{Remark}

\newcommand{\wt}{\widetilde}
\newcommand{\pa}{\partial}

\section{Introduction}

The classical problem of calculus of variations
consists in finding a  curve $\widetilde{y} (\tau)$
connecting $x_0$ and $x$ in time $t$  such that
\begin{equation} \label{27}
I_{\widetilde{y}}  (t, x, x_0) = \min_{y(0)=x_0,  y(t)=x}
I_y (t, x, x_0),
\end{equation}
where
\begin{equation}   \label{25}
I_y (t, x, x_0) = \int_0^t L(y  (\tau) , \dot{y} (\tau)) \, d\tau .
\end{equation}
Here the function $L : \mathbb{R}^{2d} \to \mathbb{R}$
is called the Lagrangian of  problem \eqref{27}. The value of
minimum \eqref{27} is called the \emph{two-point function}
corresponding to the Lagrangian $L$ and will be denoted $S(t, x,
x_0)$. It is usually assumed to be convex with respect to the
second variable. The function
\begin{equation}\label{151}
H(x, p) = \sup_{v \in \mathbb{R}^d} (pv -L (x, v))
\end{equation}
is called the Hamiltonian of problem \eqref{27}. The  celebrated
Tonelli theorem is known to give the existence of $\widetilde{y}
(\tau)$ under mild assumptions on $L$. The proof is based on the
use of the so called direct methods of calculus  of variations.
However the minimizer $\widetilde{y} (\tau) $ given by Tonelli's
theorem may be  singular  (see \cite{B} for an example and
discussion). The aim of our paper is to single out some general
enough class of Lagrangians (or Hamiltonians) having always
non-singular minimizers and moreover, to prove the existence of
the global field of smooth extremals for these classes. For a
review on  existence of non-singular minimizers see e.g.
\cite{GH}, \cite{T}.

In this paper we apply the method of Hamilton shooting
to obtain existence,   uniqueness of smooth
solutions of the boundary value problems
for  systems
\begin{equation}\label{4}
 \begin{gathered}
\dot{x} = H_p (x, p) \\
\dot{p}  = -H_x (x, p)
\end{gathered}
\end{equation}
with a rather general class of Hamiltonians. This  class of
Hamiltonians includes the elliptic polynomials  and functions of
uniform exponential growth. In turn the well-posedness of boundary
value problems  and  uniform estimates for the domain of
uniqueness for boundary value problems imply the global existence,
uniqueness and smoothness of absolute minimizers for problem
\eqref{27} and hence the existence of a global field of extremals.
It is proved that the smooth solutions always exist and are unique
almost everywhere i.e. for any $x_0 \in \mathbb{R}^d, t >0$ the
set of those $x \in \mathbb{R}^d$ for which a trajectory
delivering the absolute minimum to functional \eqref{25} is not
unique is a closed set of Lebesgue measure zero. Our method also
yields estimates for the ``two-point function'' $S(t, x, x_0)$.
\par
As an important application of our results, let us mention  the construction of
local and global fields of extremals.
It is well-known that the construction of global field
of extremals corresponding to a Hamiltonian
$H$  is the crucial step in the construction of WKB-type asymptotic for solutions
of pseudo-differential equations
$$
i \, { \pa u \over \pa t} =
H \big(x, i \, {\pa \over \pa x}\big) \, u
\quad \text{and} \quad
{\pa u \over \pa t} =
H \big(x, - {\pa \over \pa x}\big) \, u
$$
(see e.g. \cite{K1},~\cite{M}).

The method of Hamiltonian shooting can  be
applied also to some degenerate (non strictly convex) Hamiltonians.
For example in \cite{K1} a rather general class of
degenerate quadratic in momentum Hamiltonians was introduced
(called regular in \cite{K1}) for which one can prove not only
local uniqueness and global existence of solutions but also
one can obtain exact asymptotic expansions of the two-point function
that are quite similar to the case
of nondegenerate quadratic Hamiltonians. It is worth mentioning
that while developing the theory of stochastic Hamilton-Jacobi
equations we used the method of Hamiltonian shooting
to construct solutions  for
stochastic Hamiltonian systems driven by semimartingale noise
(see \cite{K1,K2,KST}).

\section{Main results}\label{s2}

We denote by $\mathcal{F}$ the set of functions $h : \mathbb{R}
\to \mathbb{R}$  represented by a series
$h(z)=\sum_{n=0}^\infty a_n z^n$ with the radius of convergence
equal to infinity  such that for some constant $M=M(h)>0$ and  all
$z \geq M$
\begin{equation}\label{28}
|h^{(n)} (z) h^{(m)} (z)| \leq  |h^{(n-1)} (z) h^{(m+1)} (z)|
\quad \forall \, n >m \geq 0 \, .
\end{equation}
Here $h^{(n)} (z)$ is the $n$-the derivative of $h(z)$.  In
particular, class $\mathcal{F}$ contains functions  $h_1 (z) =\exp\{z
\}$ and $h_2(z)= z^k$, $k \in {\mathbb N}$.

\noindent{\bf Notation.} We write $(X(t) , P(t))=(X(t, x_0, p_0) , P(t,
x_0, p_0))$ for the solution of  the system \eqref{4} with initial
conditions $(x_0,p_0)$ at $t=0$ and call  the $x$-projection
$X(t)$ of a solution $(X (t), P(t))$  characteristic of the system
\eqref{4}. Denote by
\begin{equation}\label{94}
\widetilde x(\tau) =\widetilde x(\tau; t,x,x_0)
\end{equation}
a characteristic of \eqref{4} with boundary conditions $\widetilde
x(0)=x_0$, $\widetilde x(t)=x$. We will use these notations
throughout the paper.

\begin{theorem}\label{t1}
Let  $H \in C^4(\mathbb{R}^{2d})$, $d \geq 1$. We assume that for
some $h \in \mathcal{F}$ and $\varepsilon >0$ the following
conditions hold:
\begin{itemize}
\item[(i)]  $ H_{pp} (x, p) \geq \varepsilon
\big(1+|h''(|p|)| \big) \, E_d$ for
all $x, p \in \mathbb{R}^d$,
 where $E_d \in \mathbb{R}^{d \times d}$ is identity matrix;
\item[(ii)]
$$
\sum_{|I|\leq 3, |J|=k} \Big| {\pa^{|I|+|J|} H (x, p) \over \pa
x^I \pa p^J} \Big| \leq | h^{( k )} (|p|) |\chi_\varepsilon
(p)+\varepsilon^{-1}(1-\chi_\varepsilon (p)) \quad
$$
for all $ x, p \in \mathbb{R}^d$ such that
$|p| \geq \varepsilon^{-1}$, where
\[
\chi_\varepsilon (p) =\begin{cases}
1 & \text{if } |p| \geq \varepsilon^{-1} \\
0 & \text{otherwise}
\end{cases},
\]
$I=(i_1,\dots, i_{|I|})$, $J=(j_1,\dots, j_{|J|})$ are
multi-indexes, $k=0,1,2,3$.
\end{itemize}
Then there exist $r>0$ and $T >0$ such that for any $x_0 \in
\mathbb{R}^d$,  $x \in B_r (x_0) =\{y: |y-x_0| \leq r\}$ and $t
\in (0, T)$ there exists $p_0 =p_0 (t,x,x_0)   \in \mathbb{R}^d$
such that
\begin{equation}\label{84}
X(t, x_0, p_0 (t, x, x_0))\equiv x \, .
\end{equation}
Moreover, $p_0 (t,x,x_0)$ is continuously differentiable with
respect to all variables.
\end{theorem}

In other words the theorem claims that the boundary
value problem for the system \eqref{4} is well-posed  in a
neighborhood of any $x_0 \in \mathbb{R}^d$, i.e. for small
$|x-x_0|$ and small $t$ there exists the unique solution of the
system \eqref{4} such that $x(0)=x_0$, $x(t)=x$.

The lengthy assumptions of Theorem \ref{t1} are designed to
include the main examples of Hamiltonian functions
$H(x, p)$, which are used in geometry and  mathematical physics, more
precisely they include:

\noindent{(1)} Convex elliptic polynomials (which for instance represent the
symbols of elliptic differential operators widely studied both in $\mathbb{R}^d$ and
on Riemannian manifolds); the most well-studied particular case is surely given by
quadratic polynomials, the corresponding Hamiltonians describing the energy of
classical mechanical systems in $\mathbb{R}^d$ or on Riemannian manifolds.

\noindent{(2)}
Hamiltonians provided by  the L\'evy-Khinchine formula, namely
\[
H(x, p)={1 \over 2} \, (G(x) p, p)-(A(x), p)
+ \int_{\mathbb{R}^d\setminus \{0\}} \Big( e^{-  (p,
\xi)} -1 +\frac{(p, \xi)}{1+\xi^2} \Big) \, d \nu_x (\xi),
\]
where all elements of $G(x)\in \mathbb{R}^{d \times d}$, $A(x)
\in \mathbb{R}^d$ and their derivatives up to order three are
bounded, $\mu_1 E_d < G(x)< \mu_2 E_d$ for some $\mu_1 , \mu_2 > 0
$ and $\nu_x$ is a L\'evy measure on $\mathbb{R}^d\setminus
\{0\}$ with  bounded support and  some mild regularity
assumptions; these Hamiltonians represent the symbols of
pseudo-differential operators, which describe generators of most
general Feller processes; the solutions of boundary value problem
for these Hamiltonians describe the quasi-classical (or small
diffusion) asymptotics of trajectories of this processes.

It is well known (see \cite{GH}, vol. 1,  Proposition 2, p.330) that
extremal $x(\cdot)$ connecting $x_0$ and $x$ is a strong
minimizer, if it can be embedded into Meyer field covering domain
$\Gamma \subset \mathbb{R}^{d+1}$ and
\begin{equation}\label{21}
 \mathcal{E}_L (z,\mathcal{P} (\tau , z ), q )> 0
\end{equation}
for $(t,z) \in \Gamma $ and $q \not = \mathcal{P} (t,z)$, where
$$
\mathcal{E}_L (x,p,q):=L(x,q) -L(x,p)-(q-p)\cdot L_p(x,p)
$$
is the Weierstrass excess function of the Lagrangian $L(x,p)$ and
$\mathcal{P} (t, x)$ is the slope function of Meyer field.

Theorem \ref{t1} implies the existence of the Meyer field in
$\Gamma (x_0)=(0,T)\times B_{r} (x_0)$ for any $x_0 \in \mathbb{R}^d$ with slope function $\mathcal{P} (t, x)=P(t, x_0, p_0(t, x_0,
x))$. Moreover, condition (i) Theorem \ref{t1} infer that
$H_{pp}(x, p) \geq \varepsilon E_d$, which in turn yields
\eqref{21}. Hence
\begin{equation}\label{92}
S(t, x, x_0) : = \min I_y (t, x, x_0) =I_{\widetilde x (\cdot)}
(t, x, x_0) \, ,
\end{equation}
where minimum is taken over all $y$ lying completely in $B_{r}
(x_0)$ with the boundary conditions $y(0)=x_0$ and $y(t)=x$.

\begin{lemma}\label{l3}
Under the conditions of Theorem \ref{t1} there exist
$r_1 \in (0,r]$, $T_1 \in (0,T]$\,  ($r,T$ as in Theorem \ref{t1})
such that
\begin{equation}\label{17}
\max_{x, x_0 \in \mathbb{R}^d : |x-x_0|\leq r_1} S(t, x,
x_0) < \min_{0 < \tau \leq t} \min_{x, x_0 \in \mathbb{R}^d
: |x-x_0| = r} S(\tau, x, x_0) \,
\end{equation}
for all $0 < t < T_1$. Moreover
\begin{equation}\label{112}
\lim_{t \to 0+} \min_{x, x_0 \in \mathbb{R}^d :
|x-x_0| = r} S(t, x, x_0) =+\infty \, .
\end{equation}
\end{lemma}

The proofs of  Theorem \ref{t1} and Lemma \ref{l3} will be given in
Sections \ref{s3} and \ref{s4} respectively.

Observe that (i) Theorem \ref{t1} implies that $H(x,p)$ is bounded
from below and so is $L(x,v)$. Note that functionals \eqref{25}
with Lagrangians $L(x,v)$ and  $L(x,v)+c$ with $c \in \mathbb{R}$
being some constant have the same minimizing functions. Therefore
without loss of generality we assume that $L(x,v) \geq 0$ and then
$$
I_y (t,x,x_0) \geq 0
$$
for all piecewise smooth $y(\tau)$.

\begin{corollary}\label{c2}
Let $0 <t<T_1$, $x, x_0 \in \mathbb{R}^d$, $|x-x_0| \leq r_1$
($T_1$, $r_1$ as in Lemma \ref{l3}). Then under the conditions of
Lemma \ref{l3} the characteristic $\widetilde x(\tau)$ given by
\eqref{94} provides the unique absolute minimum for the functional
$I_y (t,x,x_0)$.
\end{corollary}

\begin{proof}
As we have seen above $\widetilde x(\tau)$ provides a minimum for
$I_y (t,x,x_0)$ among all curves lying completely in $B_{r}
(x_0)$. Let us suppose that $\widetilde{y}(\tau)$ also provides a
minimum, and   $|\widetilde{y}(s')-x_0|=r$ for some
$s'<t$, $r' \leq r$. By \eqref{92}, \eqref{17} we see
$$
I_{\widetilde{y}} (t, x,x_0)
\geq
I_{\widetilde{y}} (s',\widetilde{y}(s'),x_0)
\geq
S(s', \widetilde{y}(s'),x_0)
>S (t, x,x_0)
=I_{\widetilde x} (t, x,x_0) \, .
$$
\end{proof}

\begin{theorem}[Tonelli's theorem]\label{t2}
Under the conditions of Theorem \ref{t1} for any $t>0$ and $x, x_0
\in \mathbb{R}^d$ there exists a characteristic $\widetilde
x(\tau)$ with boundary conditions $\widetilde x(0)=x_0$,
$\widetilde x(t)=x$ that provides an absolute minimum (probably
not unique) for $I_y (t, x, x_0)$ over all piecewise smooth curves
$y(\tau)$ connecting $x_0$ and $x$ in time $t$.
\end{theorem}

Our proof of the implication Lemma \ref{l3} $\Rightarrow$
Theorem \ref{t2} (and also the deduction of Theorem \ref{t3} given
below) is similar to the one given in \cite[pp. 56-57]{K1}. We
give it here for reader's convenience.

\begin{proof}[Proof of Theorem \ref{t2}]
Let $y_n=y_n(\tau)$ will be a minimizing sequence for  $I_y (t,
x, x_0)$, i.e.
\begin{equation}\label{72}
I_{y_n} (t, x, x_0) \to \inf_{y}
I_{y} (t, x, x_0)
\end{equation}
and $y_n (0)=x_0$, $y_n (t)=x$. Let $k \in {\mathbb N}$ be the
integer part of ${|x-x_0|/r_1}$, namely
\begin{equation}\label{100}
kr_1 \leq |x-x_0| < (k+1)r_1
\end{equation}
and suppose first (in Steps 1 and 2) that
\begin{equation}\label{87}
t \in (0,T_1)
\end{equation}
($T_1$, $r$, $r_1$ as in Lemma \ref{l3}).

\noindent\emph{Step 1.} We show that for all $\tau \in (0,t)$ and $n \in
{\mathbb N}$
\begin{equation}\label{37}
y_n (\tau) \in \mathcal{K} \quad  \text{for some compact} \quad
\mathcal{K} \subset \mathbb{R}^d \, .
\end{equation}
We define $\tau_i=\tau_i (n)$ \, $i \in {\mathbb N}_0$ by the
recurrent formula
$$
\tau_0 =0; \quad \tau_i=\inf\{\tau\in (\tau_{i-1}, t]: |y_n
(\tau)-y_n (\tau_{i-1})| =r\}
$$
($\inf \emptyset := +\infty$) and  put $m=m(n)=\max\{i : \tau_i < \infty\}$.
Since $y(0)=y(\tau_0)=x_0$
$$
|y_n (\tau)-x_0| \leq \sum_{j=1}^{i-1} \big|y_n (\tau_j)-y_n
(\tau_{j-1}) \big| + \big|y_n (\tau)-y_n (\tau_{i-1}) \big| \leq i
r  \leq mr
$$
for $\tau \in (\tau_{i-1}, \tau_i)$
and
$$
|y_n (\tau)-x_0| \leq |y_n (\tau)-y_n (\tau_{m})|+|y_n
(\tau_m)-x_0|\leq (m+1)r
$$
for $\tau \in (\tau_m, t)$.
Thus
\begin{equation}\label{83}
y_n (\tau) \in B_{(m+1) r} (x_0) \, .
\end{equation}
We show that
\begin{equation}\label{82}
m (n)  \leq k+1
\end{equation}
for all but finite number of $n$. Then combining \eqref{83} and
\eqref{82}  proves \eqref{37} with $\mathcal{K}= B_{(k+2) r} (x_0)$.

To prove \eqref{82} we assume by contradiction that $m \geq k+2$.
Let $\widehat y_n (\tau)$ be solution of \eqref{4} on each
interval $[\tau_{i-1}, \tau_{i}]$  $i=1, \dots, k$
 ($k$ as in \eqref{100}) and on the interval $[\tau_{k}, t]$ and
$$
\widehat y_n (\tau_{i})=x_0+{i \over k+1}\, (x-x_0) \quad i=1,
\dots, k \,,
$$
$\widehat y_n (t)=x$. Since $|\widehat y_n (\tau_i)- \widehat y_n
(\tau_{i-1})| < r_1$ and $|y_n (\tau_i)- y_n (\tau_{i-1})|=r$, an
application of \eqref{17} gives
\begin{equation} \label{80}
\begin{aligned}
S(\tau_i-\tau_{i-1},y_n (\tau_i), y_n (\tau_{i-1}))
&> S(\tau_i-\tau_{i-1},\widehat y_n (\tau_i), \widehat y_n
(\tau_{i-1} )) \\
 &= I_{\widehat y_n}
(\tau_i-\tau_{i-1},\widehat y_n (\tau_i), \widehat y_n
(\tau_{i-1})) \, .
\end{aligned}
\end{equation}
Summing \eqref{80} over $i=1, \dots, k$ and using
$S(\tau_{k+1}-\tau_{k},y_n (\tau_{k+1}), y_n (\tau_{k})) \geq
S(t-\tau_{k},x, \widehat y_n (\tau_{k}))$ we obtain
\begin{align*}
I_{y_n}(\tau_{k+1},y_n (\tau_{k+1}), x_0)
&=\sum_{i=1}^{k+1} I_{y_n}(\tau_{i}-\tau_{i-1},y_n (\tau_{i}),y_n
(\tau_{i-1}))
\\
 &\geq \sum_{i=1}^{k+1} S (\tau_{i}-\tau_{i-1},y_n
(\tau_{i}),y_n (\tau_{i-1})) \\
 &\geq I_{\widehat y_n}(t, x , x_0) \, ,
\end{align*}
and so
$$
\inf_{n} \,  I_{y_n}(\tau_{k+1},y_n (\tau_{k+1}), x_0) \geq
\inf_{n} \,  I_{\widehat y_n}(t, x , x_0) \, .
$$
On the other hand,  by \eqref{112} we have
$$
\inf_{n} \, I_{y_n}(\tau_{k+2}-\tau_{k+1} ,y_n (\tau_{k+2}), y_n
(\tau_{k+1}))
>0 \, .
$$
Thus
$$
\inf_{n} I_{y_n}(t,x, x_0) >\inf_{n} I_{\widehat y_n}(t,x, x_0) \,
,
$$
which contradicts \eqref{72}. This contradiction proves
\eqref{82}. Without loss of generality we may assume that
\eqref{82} holds for all $n$. \smallskip

\noindent \emph{Step 2.}
Since the sequence $(\tau_i,y_n (\tau_i))$ lies in the compact
$[0,t] \times \mathcal{K}$ for any $i=1, \dots, m$, then without loss
of generality we assume that
$$
\tau_i (n) \to s_i\, ,
\quad
y_n (\tau_i) \to b_i \quad\text{as}\quad
n \to \infty
$$
$i=1, \dots, m$ for some  $s_i \in (0,t)$, $b_i \in \mathbb{R}^d$.
Let $\widetilde{y}_n (\tau)$ be solution of \eqref{4} on
each interval $[\tau_{i-1}, \tau_{i}]$ \, $i=1, \dots, m$ and on
the interval $[\tau_{m}, t]$ and
$$
\widetilde{y}_n (\tau_{i})=y_n (\tau_{i})
\quad i=1, \dots, k \, ,
$$
$\widetilde{y}_n (t)=x$.
Clearly
\begin{equation}\label{88}
I_{y_n} (t,x,x_0)
\geq
I_{\widetilde{y}_n} (t,x,x_0) \, .
\end{equation}
Let $y (\tau)$ be solution of \eqref{4} on each interval
$[s_{i-1}, s_{i}]$ \, $i=1, \dots, m$ and on the interval
$[s_{m}, t]$ and
$y (s_{i})= b_{i}$, $i=1, \dots, m$,
$y (t)=x$. Theorem \ref{t1} implies
\begin{equation}\label{85}
\lim_{n \to \infty} \left\|y-\widetilde{y}_n
 \right\|_{C^1([s_{i-1}+\delta, \, s_i-\delta])} = 0
\end{equation}
for any $\delta <(s_{i-1}-s_i)/2$,  $i=1, \dots, m$. Note that
for all but finite number $i$  we have $[s_{i-1}+\delta,
s_i-\delta] \subset [ \tau_{i-1}, \tau_i ]$. Therefore,
\begin{equation}\label{86}
\lim_{n \to \infty} I_{\widetilde{y}_n} (t,x,x_0) =I_{ y}
(t,x,x_0) \, .
\end{equation}
Combining \eqref{88} and \eqref{86} we get
$$
\lim_{n \to \infty} I_{y_n} (t,x,x_0) \geq I_{ y}
(t,x,x_0) \, .
$$
It suffices to show smoothness of $y(\tau)$ at $\tau=s_i$
$i=1, \dots, n$. For each $i=1, \dots, m$ we take
$s'_i <s_i < s''_i$ such that $|y(\tau)-y(s_i)| \leq r_1$
for all $\tau \in [s'_i,s''_i]$. Since $y(\tau)$ provides
the unique minimum among all curves lying
completely in $B_{r_1}(y(s_i))$ it should coincide with the
solution of \eqref{4} which passes through points $y(s_i')$,
$y(s''_i)$ in times $s_i'$ and $s''_i$ respectively.
In particular this means that $y$ is
continuously differentiable, i.e. is a solution of \eqref{4}.

\noindent\emph{Step 3.} Previously we have imposed restriction \eqref{87}.
Now let
$$
\ell \, {T_1 \over 2} \leq  t <(\ell+1){T_1 \over 2}
$$
for some $\ell \in {\mathbb N}$ and let $y_n=y_n(\tau)$  be a
minimizing sequence. We take $\widetilde{y}_n =\widetilde{y}_n
(\tau)$ connecting $x_0$ and $x$ such that $\widetilde{y}_n$ is
characteristic of the system \eqref{4} on each interval $(k T_1/2,
(k+1)T_1/2)$ and $\widetilde{y}_n (k T_1/2)=y_n(k T_1/2)$ for $k=1,
\dots , \ell$.

By above proof we have that
$I_{y_n}(t,x,x_0) \geq I_{\widetilde{y}_n}(t,x,x_0)$.
As in Step 1  we  show that graphs of all
$\widetilde{y}_n$ lie in a compact. Hence we may assume that  there
exist  limits $b_k:=\lim_{n \to \infty} \widetilde{y}_n (k
T_1/2)$,   $k=1, \dots, \ell$. We take $y=y(\tau)$ connecting
$x_0$ and $x$ such that $y$ is characteristic of the system
\eqref{4} on each interval $(k T_1/2, (k+1)T_1/2)$ and
$y(k T_1/2)=b_k$,  $k=1, \dots, \ell$. As in Step 2 we show that
$y(\tau)$ is a minimizer and it is smooth at $\tau =k T_1/2$,
$k=1, \dots, \ell$.
\end{proof}

To any solution $(X,P)$ of \eqref{4} there corresponds the
equation in variations
\begin{equation}\label{89}
\begin{gathered}
\dot{v} = H_{xp} (X(\tau), P(\tau))  v+H_{pp} (X(\tau), P(\tau))  w
\\
\dot{w}  = -H_{xx}(X(\tau), P(\tau)) v -H_{xp}(X(\tau), P(\tau)) w
\end{gathered}
\end{equation}
We say that points $X(\tau_1)$, $X(\tau_2)$ are conjugate if there
exists nontrivial (not vanishing identically) solution $(v(\tau),
w(\tau))$ of \eqref{89} such that  $v(\tau_1)=v(\tau_2)=0$.

\begin{proposition}\label{p1}
Suppose Hamiltonian $H(x,p)$ is smooth and strictly convex in $p$.
If a characteristic $X(\tau)$ contains two conjugate points
$X(\tau_1)$, $X(\tau_2)$ then for any $\delta >0$ the curve
 $X(\tau)$  $\tau \in [\tau_1, \tau_2+\delta]$
does not provide even a local minimum among curves joining
$X(\tau_1)$ and  $X(\tau_2+\delta)$ in time $\tau_2-\tau_1+\delta$.
\end{proposition}

The proof of the above Proposition  can be found in
\cite[p.77 Theorem 1]{A}. Following \cite{K1} we say that for
some $x_0 \in \mathbb{R}^d$ the point
$(t, x) \in \mathbb{R}_{+} \times \mathbb{R}^d$ is \emph{regular}
and write $(t,x) \in \mathop{\rm  Reg}(x_0)$
if ({\bf i}) points $x,x_0$ are not conjugate;
({\bf ii}) the absolute minimum is attained on a unique curve;
 ({\bf iii}) this curve is a characteristic $\widetilde  x(\tau,t,x,x_0)$
 with boundary conditions $\widetilde  x(0)=x_0$, $\widetilde  x(t)=x$.

\begin{theorem}\label{t3}
Under the conditions of Theorem \ref{t1} for any $x_0 \in \mathbb{R}^d$
the set of regular points is open, connected and everywhere
dense in $\mathbb{R}_{+}\times \mathbb{R}^d$. For any fixed
$t>0$ the set $\{x \in \mathbb{R}^d: (t, x)  \in \mathop{\rm Reg}(x_0) \}$
is open and everywhere dense in $\mathbb{R}^d$.
\end{theorem}

\begin{proof}
For any $t>0$, $x, x_0 \in \mathbb{R}^d$ we take characteristic
$\widetilde x(\tau)=\widetilde x(\tau;t,x,x_0)$ which delivers
absolute minimum for $I_y (\tau , x,x_0)$. Note that the existence
of such $\widetilde x(\tau)$ is guaranteed by Theorem \ref{t2}. We
show that  for any $\tau \in (0, t)$ \, characteristic $\widetilde
x(s)$, \, $s \in [0,\tau]$ delivers the unique absolute minimum to
$I_y (\tau , \widetilde x(\tau) ,x_0)$.
Clearly  $\widetilde x(s)$ provides an absolute (a priori not
unique) minimum to $I_y (\tau , \widetilde  x(\tau),x_0)$. If
another function $\widetilde{y}=\widetilde{y} (s)$, \, $s \in
[0,\tau]$ with $\widetilde{y} (0)=x_0$,  $\widetilde{y}
(\tau)=\widetilde  x (\tau)$ also provides an absolute minimum,
then defining it on $(\tau,t]$ by $\widetilde{y} (s)=\widetilde x
(s)$, $s \in [\tau,t]$ we deduce that $\widetilde{y}$ also provides
a minimum for $I_y (t, x,x_0)$. Take $s' < \tau < s''$ such that $\widetilde{y}(s'), \widetilde{y}(s'') \in B_{2^{-1} r_1} (\widetilde{y} (\tau))$, and so
$|\widetilde{y}(s')-\widetilde{y}(s'') | \leq
r_1$. By Corollary \ref{c2} the characteristic connecting
$\widetilde{y}(s')$ and $\widetilde{y}(s'')$ in
time $s''-s'$ provides the unique absolute
minimum. Therefore $\widetilde x(s)= \widetilde{y}(s)$ for
$s \in [s', s'']$. Consequently we have
$\widetilde x(s)=\widetilde{y}(s)$ for all $s \in [0, \tau]$.

By Proposition \ref{p1} $\widetilde x(0)$ and $\widetilde x
(\tau)$ are not conjugate. Hence $ (\tau, \widetilde x(\tau))$ is
regular. This immediately implies that Reg $(x_0)$  is connected
and everywhere dense   in $\mathbb{R}_{+} \times \mathbb{R}^d$.
Moreover, $x$-projection of Reg $(x_0)$ is everywhere dense in
$\mathbb{R}^d$. To prove that Reg $(x_0)$ is open, note that if
$(t, x)$ is regular then $\pa X(t, x_0,p_0) /\pa p_0 \not = 0$. An
application of implicit function theorem gives that~$p_0=p_0 (t,
x, x_0)$ is well-defined by \eqref{84} in some neighborhood
$U(t,x) \subset \mathbb{R}^{d+1}$ of $(t,x)$. As we know the
characteristic
$\widetilde x (\tau)= \widetilde x(\tau;t', x', x_0)$
delivers local minimum for any $(t', x') \in U(t,x)$.
Since the quantity $\min_y I_y (t', x', x_0)$ depends continuously
 on $(t', x')$ and
for $(t', x')=(t, x)$ the unique absolute minimum is
provided by $\widetilde x(\tau;t,x,x_0)$, then
$x(\tau;t', x', x_0)$ provides an absolute minimum for any
$(t',x') \in U_0(t,x)$ for some $U_0 (t,x) \subset U (t,x)$.

Similarly fixing $t>0$ one shows that the set
$\{x: (t,x) \in \mathop{\rm Reg} (x_0) \}$ is open.
\end{proof}

\section{Auxiliary results}\label{s5}

In this section we will deduce some implications from \eqref{28}
and (i), (ii) Theorem \ref{t1}.

\noindent{\bf Notation.} Throughout this paper $\varepsilon>0$  will be
from the conditions of Theorem \ref{t1} and $M=M(h)>0$ will be the
constant from \eqref{28}. In sections \mbox{\ref{s5} - \ref{s4}}
we will construct constants $M_1, \dots, M_{11}>0$, $\rho>0$,
$$
1>t_1 \geq t_2  \geq T \geq T_1 >0 \,, \quad 1 >c_1 \geq c_2
>0\, , \quad r \geq r_1>0
$$
which  depend only on $\varepsilon$ and $h(z)$.

\begin{lemma}\label{l5}
The functions $h \in \mathcal{F}$ satisfy the following inequalities
\begin{itemize}
\item[(i)]  $ |h^{(n)} (z)  (h (z))^{n-1} | \leq  | h' (z)
|^n $  $n \in {\mathbb N}_0$,
\item[(ii)] $\Big| h^{(n) }
\Big(  z +  \lambda {  {|h(z)| \over |h' (z)|}} \Big) \Big|
\leq 3  |h^{(n) } (z)| $, $n \in {\mathbb N}_0$
\end{itemize}
for  all $z >M$ and $|\lambda | \leq 1$.
\end{lemma}

\begin{proof}
The case $n=0$ in (i) is trivial. We assume that $n \geq 1$. By
repeated application of \eqref{28} we obtain
$$
|h^{(n)} (z)  (h (z))^{n-1} | \leq |h^{(n-1)} (z)  (h (z))^{n-2}
h' (z) | \leq \dots \leq  | h'  (z)|^n
$$
and (i) follows.
We proceed with (ii). Using  Taylor's development
 $h^{(n)} (z+a) = \sum^{\infty}_{m=0} h^{(n+m)} (z) a^m / m!$
with $ a= | \lambda h (z) /h^{ \prime} (z)|$ gives
$$
h^{(n)}  \Big( z +  \lambda {|h(z) |\over |h' (z)|}\Big) =
\sum_{m=0}^\infty |\lambda|^m {h^{(m+n)} (z) \over  m!} \, {|h
(z)|^{m} \over |h^{ \prime }(z)|^{m}} \, .
$$
Since, by \eqref{28},
$$
|h^{(m+n)} (z)(h (z))^{m}| \leq  |h^{(m+n-1)} (z) h' (z)
(h (z))^{m-1}| \leq \dots \leq |h^{(n)} (z)| |h' (z)|^m\, ,
$$
it follows
$$
\Big| h^{(n)}  \Big( z +  \lambda {|h(z) |\over |h'
(z)|}\Big)\Big| \leq
 |h^{(n)} (z)|
\sum_{m=0}^\infty {|\lambda|^m  \over m!} \leq |h^{(n)}
(z)|\exp\{1\},
$$
where we used $|\lambda| <1$.
\end{proof}

\begin{lemma}\label{l6}
Let $h \in \mathcal{F}$, $H \in C^4 (\mathbb{R}^{2d})$ be such that
conditions (i), (ii) of Theorem \ref{t1} hold. Then for some
constants $M_1, M_2, M_3 >0$
\begin{itemize}
\item[(i)] $ |h^{(m)} (z)|$ is monotone on $(M_1,+\infty)$
for all $m=0, \dots, 3 $,

\item[(ii)] $ |h' (z)|$ increases on $(M_1,+\infty)$,

\item[(iii)] $|H_p (x, p)| \geq \varepsilon |h' (|p|)| -M_2$
 for all $x, p \in \mathbb{R}^d$,

\item[(iv)] $(p, H_p (x, p)) \geq \varepsilon |h' (|p|)|\, |p|
-M_3$  for all $x, p \in \mathbb{R}^d$ .
\end{itemize}
\end{lemma}

\begin{proof}
An application of \eqref{28} with $n=m+2$, $m \in {\mathbb N}_0$
implies
$$
\big((g (z) )^2\big)'' = 2 g'' (z) g(z)+2(g' (z))^2 >0
$$
for  $g(z)=h^{(m)}  (z) $. Therefore, $g(z)$ has at most two
intervals of monotonicity. Hence $g(z)$ is monotone for $z \geq
M_{1, m} $ for some $M_{1, m}>0$. Take
$$
M_1=\varepsilon^{-1}+\max_{m=0, \dots, \, 3} M_{1, m}
$$
and (i) follows.

By (i) Theorem \ref{t1} we have $H_{pp} (x,p) \geq \varepsilon
E_d$. Hence
\begin{align}\label{73}
|p| \, |H_p(x, p)| \geq  \big(p, H_{p} (x, p)\big)&= \big(p, H_{p}
(x, 0)\big) + \int_0^1\big(p, H_{pp} (x, \tau p) p\big) \, d \tau
\\
 &\geq \big(p, H_{p} (x, 0)\big) + \varepsilon \, |p|^2
\\
 &\geq \varepsilon \, |p|^2 -\varepsilon^{-1} |p| \, ,
\end{align}
where we used that,  by (ii) Theorem \ref{t1}, $|H_{p} (x, 0)|
\leq \varepsilon^{-1}$ . Hence
$$
|H_p(x, p)| \geq \varepsilon \, |p| -\varepsilon^{-1} \, .
$$
Using (ii) Theorem \ref{t1} we get
\begin{equation}\label{34}
|h' (z) | \geq \varepsilon \, z -\varepsilon^{-1}
\end{equation}
for $ z \geq M_1$ (recall $M_1 \geq \varepsilon^{-1}$). This and
(i) Lemma \ref{l6} imply (ii) Lemma \ref{l6}.

We proceed with (iii) and (iv). Without loss of generality we may
assume that $h' (z)$ increases for $z \geq M_1$.  (Otherwise
we replace $h$ by $-h$ noticing that the conditions of
Theorem \ref{t1} for $-h$ and $H$ still hold.) So
$$
h'' (z) > 0 \quad \text{for all} \quad z \geq M_1\, .
$$
Hence for $|p| \geq M_1$ we get
\[
\int_0^1|h''(\tau |p|) |\, |p| \, d\tau \geq
\int_{{M_1 \over |p|}}^1 h''(\tau |p|) \, |p| \,
d\tau =h'(|p|)-h'({M_1}) \, .
\]
Consequently, due to (i) Theorem \ref{t1},
\begin{align*}
\int_0^1\big(p, H_{pp} (x, \tau p) p\big) \, d\tau &\geq
\varepsilon |p|^2 \int_0^1(1+|h''(\tau |p|) ) \,
d\tau
\\
&\geq \varepsilon |p| \left(|p|+h'(|p|)-h'(M_1) \right) \, .
\end{align*}
Using this and the first line in \eqref{73} we have
\begin{align}\label{53}
(p, H_p(x, p)) &\geq - \varepsilon^{-1}|p| +\varepsilon |p|
\left(|p|+h'(|p|)-h'(M_1) \right) \\
 &\geq \varepsilon h'(|p|)\, |p|-M_3
 \, ,
\end{align}
where
$$
M_3:=-\min_{z>0} \{- \varepsilon^{-1}z +\varepsilon z (z-
h'(M_1) )\} \, .
$$
Using again \eqref{53} we get
\begin{equation}\label{48}
|H_p(x,p)| \geq - \varepsilon^{-1} +\varepsilon
\left(|p|+h'(|p|)-h'(M_1) \right) \geq
\varepsilon h'(|p|) - \varepsilon^{-1} -\varepsilon
h'(M_1) \, ,
\end{equation}
where
$M_2:=\varepsilon^{-1} +\varepsilon h'(M_1)$.
\end{proof}

\begin{lemma}\label{l1}
Under the conditions of Theorem \ref{t1} there exist $t_1, M_4
>0$ such that for all $c  \in (0, 1/2)$, $t \in (0, t_1)$, $x_0
\in \mathbb{R}^d$,
\begin{equation}\label{6}
p_0 \in V_{c, t}:= \{p \in \mathbb{R}^d : t |h' (|p|)| < c
\}
\end{equation}
and  $\tau \in [0, t]$ we have
\begin{equation}\label{10}
|h^{(n)} ( | P(\tau ) | )| \leq M_4 (|h^{(n)}(  |p_0| )|  +1)\quad n=0,1,2.
\end{equation}
Moreover,
\begin{gather}\label{55}
|X(t, x_0, p_0) -x_0 | \leq M_4 t (|h' (  |p_0| )|  +1) \, , \\
\label{59} |P(t, x_0, p_0) -p_0 | \leq M_4 t (|h (  |p_0| )|  +1) \,.
\end{gather}
\end{lemma}

\begin{proof}
We choose $0 < t_1 <1 $ such that the system \eqref{4} has a
solution on $[-t_1,t_1]$. Let us  first (in Steps 1 and 2) assume
that
\begin{equation}\label{39}
|P (\tau)| \geq M_1 \quad \text{for all} \quad \tau \in [0,t_1]
\, .
\end{equation}
\noindent \emph{Step 1.} Notice that (i), (ii) Lemma \ref{l6} imply
that
\begin{equation}\label{111}
|h(z)| \quad \text{increases for}  \quad z \geq M_1 \, .
\end{equation}
In particular $h(z)$ preserves sign for $z \geq M_1$. Without loss
of generality we may assume (in Steps 1 and 2) that $h(z) > 0$ for
$z \geq M_1$. Using (ii) Theorem \ref{t1}  and $M_1
>\varepsilon^{-1}$ we find from \eqref{39}
and  the system \eqref{4}
$$
|P(t)-p_0| \leq \int_{0}^t |H_x (X(\tau), P(\tau)) | \, d \tau
\leq \int_0^t  h (|P(\tau)|)  \, d \tau
$$
and so
$$
|p_0|-\int_0^t  h (|P(\tau)|)  \, d \tau\leq |P(t)| \leq
|p_0|+\int_0^t  h (|P(\tau)|)  \, d \tau \, .
$$
Due to \eqref{111} and Gronwall Lemma,
$$
y_1(\tau) \leq | P(\tau) | \leq y_2(\tau) ,
$$
where $y_i(\tau)$  $i=1,2$  solve the equation
$$
\dot{y}_i (\tau) = (-1)^i \, h(y_i (\tau))  \, , \quad
y_i(0)=|p_0| .
$$
One readily sees that
$y_i(\tau)= \Phi^{-1} \left( \Phi (|p_0|) +(-1)^i\tau \right)$,
$i=1,2$,
where
$$
\Phi (\lambda) = \int_{M_1}^\lambda {d \zeta \over h(\zeta)} \, .
$$
Hence
\begin{equation}\label{16}
\Phi^{-1} \left( \Phi (|p_0|) -\tau \right)  \leq | P(\tau ) |
\leq \Phi^{-1} \left( \Phi (|p_0|) +\tau \right) .
\end{equation}
\emph{Step 2.} An application of Taylor's formula on $\Phi^{-1}$
yields
\begin{equation}\label{90}
\Phi^{-1} \left( \Phi (z) +\tau \right)= z+ \sum_{n=1}^\infty {a_n
(z) \over n !} \, \tau^n ,
\end{equation}
where
$$
a_n(z) = {d^n \over d \tau^n} \, \Phi^{-1} \left( \Phi (z) +\tau
\right) \big|_{\tau=0} = (\Phi^{-1})^{(n)} (\Phi (z))
$$
or
\begin{equation}\label{60}
a_n (\Phi^{-1} (\kappa)) = (\Phi^{-1} )^{(n)} (\kappa) \,
\end{equation}
with $\kappa = \Phi (z)$. We differentiate \eqref{60} in $\kappa$
to get
\begin{equation}\label{49}
a_{n}' (\Phi^{-1} (\kappa)) (\Phi^{-1} (\kappa))' =
(\Phi^{-1} )^{(n+1)} (\kappa) =a_{n+1} (\Phi^{-1} (\kappa)) \, .
\end{equation}
Consequently, \eqref{49} and $(\Phi^{-1} (\kappa))'= dz /d
\kappa = (\Phi' (z))^{-1}= h (z)$ imply
\begin{equation}\label{61}
a_1 (z) =  h(z)  \quad \text{and} \quad a_{n+1} (z)=a_{n}'
(z) h(z) \,  .
\end{equation}
Using induction we deduce from \eqref{61}
\begin{equation}\label{62}
a_n (z) = {\sum}'  h^{(m_1)} (z)  \dots h^{(m_{n-1})} (z)
h(z)  \quad n \geq 2 \, ,
\end{equation}
where the sum $\sum'$ is taken over some $m_1, \dots ,
m_{n-1} \in {\mathbb N}_0$ such that $m_1+\dots+m_{n-1}=n-1$ and
contains $(n-1)!$ terms. It follows
$$
|  a_n (z)  | \leq (n-1)!  \max_{m_1+\dots+m_{n-1}=n-1} \big|
h^{(m_1)} (z) \dots h^{(m_{n-1})} (z)  h(z) \big|  \, .
$$
By (i) Lemma \ref{l5}  and because of $\sum_{k=1}^{n-1}(m_k-1)=0$
we have
$$
| \, h^{(m_1)} (z)  \dots h^{(m_{n-1})} (z) | =\prod_{k=1}^{n-1}|
\, h^{(m_k)} (z) (h(z))^{m_k-1} | \leq
 |h' (z)|^{n-1}  .
$$
Consequently,
$$
|a_n (z) \tau^n | \leq (n-1)!  \, | \tau  h' (z) |^{n-1} \,
\tau  |h (z)|  .
$$
Since, by $\eqref{6}$, $|\tau h' (|p_0|)  | \leq c $, it
follows that
\begin{equation}\label{93}
\big| {a_n (|p_0|) \tau^n \over n!} \big| < c^{n-1} \, \tau
|h(|p_0|)| .
\end{equation}
Substituting \eqref{93} in \eqref{90} we get
\begin{equation}\label{15}
\Phi^{-1} \left( \Phi (|p_0|) +\tau \right) \leq |p_0| + { 1 \over
1- c }\, \tau   |h(|p_0|)| \leq |p_0| + 2 \tau |h(|p_0|)|
\end{equation}
for $c \in (0,  1/2)$. Similarly we obtain
\begin{equation}\label{150}
\Phi^{-1} \left( \Phi (|p_0|) -\tau \right)  \geq |p_0| - 2 \tau
|h(|p_0|)|
\end{equation}
for $c \in (0,  1/2)$. Combining \eqref{16},  \eqref{15} and
\eqref{150} we obtain
$$
|p_0| - 2 \tau  |h(|p_0|)| \leq | P(\tau) | \leq |p_0| + 2 \tau
|h(|p_0|)|
$$
for $c \in (0,  1/2)$. Using $p_0 \in V_{c, t}$ gives $\tau \leq t
\leq c/|h' (|p_0|)|$ and so
\begin{equation}\label{26}
|p_0| - 2 c \, {|h(|p_0|)| \over |h' (|p_0|)|} \leq |
P(\tau) | \leq |p_0| + 2 c \, {|h(|p_0|)| \over |h'
(|p_0|)|}.
\end{equation}
An application of (ii) Lemma \ref{l5} with $\lambda= 2 c \leq 1$
gives
\begin{equation} \label{101}
\begin{aligned}
| h^{(n) } (  |P(\tau)| ) |
&\leq \max\big\{ h\big(|p_0| + 2 c
\, {|h(|p_0|)| \over |h' (|p_0|)|}\big) ,  h\big(|p_0| -2
c \, {|h(|p_0|)| \over |h' (|p_0|)|}\big)  \big\}
\\
 &\leq 3  |h^{(n)} (|p_0|)| \quad  n=0,1,2.
\end{aligned}
\end{equation}
Similarly one can check (we will need this in the proof of
Lemma \ref{l7}) that
\begin{equation}\label{33}
|h^{(n)} (|P(\tau_1)|)| \leq 3 |h^{(n)} (|P(\tau_2)|)| \quad
n=0,1,2
\end{equation}
for any $\tau_1, \tau_2 \in [0,t]$.

\noindent\emph{Step 3.} Finally  we suppose that \eqref{39} does not hold.
If $|P(\tau)| \leq M_1$ for all $\tau \in [0,t_1]$ then taking
\begin{equation}\label{45}
M_4 :=3+3 \max_{z\in [0, \, M_1], n=0,1,2} |h^{(n)}(z)| \,
\end{equation}
we have
\begin{equation}\label{40}
| h^{(n) } (  |P(\tau)| ) |\leq {1 \over 3} \,  M_4 \quad
n=0,1,2
\end{equation}
for all $\tau$. If $|P(s_0)|=M_1$ and $|P(\tau)| \geq M_1$ on
$[s_0, s_1] \subset [0, t_1]$ for some $s_0 <s_1$, then
\eqref{101} is applicable to $P(\tau)$ on $[s_0, s_1]$ and so
\begin{equation}\label{47}
| h^{(n) } (  |P(\tau)| ) | \leq 3  |h^{(n)} (|M_1|)| \leq  M_4
\quad n=0,1,2
\end{equation}
for $\tau \in [s_0, s_1]$. Combining \eqref{40} and \eqref{47} we
have
\begin{equation}\label{46}
| h^{(n) } (  |P(\tau)| ) |\leq  M_4 \quad n=0,1,2.
\end{equation}
Combining this and \eqref{101} we arrive at \eqref{10}.
Estimates \eqref{55}, \eqref{59} are direct consequences of (ii)
Theorem \ref{t1} and \eqref{10}.
\end{proof}

\begin{lemma}\label{l7}
Let us define $\omega : [M_4 , +\infty) \to \mathbb{R}$
by the identity
\begin{equation}\label{64}
\omega (|h' (z)|) \equiv z \, .
\end{equation}
Then  there exist $c_1 \in (0, 1/2)$ and constants $M_5, M_6 >0$
such that for all $t \in (0,t_1)$, $c \in (0,c_1)$, $x_0 \in
\mathbb{R}^d$, $p_0 \in V_{c, \, t}$ one has
\begin{itemize}
\item[(i)] $$|p_0|   \geq   \omega \big(M_4^{-1} \, {|x-x_0| \over t}
-M_5\big) \quad \text{provided that }  M_4^{-1}
{|x-x_0|\over t} -M_5>M_4 \, ,
$$

\item[(ii)]
$$
|p_0| \leq \omega \big( {2 \over \varepsilon} \, {|x-x_0| \over
t} +M_5\big) \, ,
$$

\item[(iii)] $$ \big(p_0 , {x-x_0 \over t} \big)\geq {\varepsilon
\over 2}\, |p_0| \big(M_4^{-1}{|x-x_0| \over t } -M_5\big)-
M_6 \, , $$
\end{itemize}
where we write for short $x=X(t, x_0, p_0)$.
\end{lemma}

\begin{remark} \label{rmk1} \rm
Notice that (ii) Lemma \ref{l6} and the fact that $M_4>|h'
(M_1)|$ imply the correctness of  definition \eqref{64}.
\end{remark}

\begin{proof} \emph{Step 1.} In this step we show that
\begin{equation}\label{105}
\left|\left(p_0, H_p (X(\tau), P(\tau)) -H_p (x_0, p_0) \right)
\right| \leq 2^{-1} \varepsilon \, |h'(|p_0|)| |p_0| +2
\omega (M_4) ( \varepsilon^{-1}+M_4) \, .
\end{equation}
Let us first  assume that
\begin{equation}\label{13}
|P(\tau)|>M_1 \quad \forall \tau \in [0,t] \, .
\end{equation}
From \eqref{4}, \eqref{33} and (ii) Theorem \ref{t1} (recall
$M_1> \varepsilon^{-1}$) we deduce
\begin{align*}
 \sum_{j=1}^d |(X(\tau)-x_0)_j|
 &\leq  \sum_{j=1}^d \int_0^t \left| {\pa H \over \pa
 p_j}\left(  X(\tau), P(\tau) \right)
 \right| \, d\tau \\
 &\leq
 t \max_{0 \leq \tau \leq t}  |h'(|P(\tau)|)|
\leq 3 t \big|h' (|p_0|)\big|
\end{align*}
and
$$
\sum_{j=1}^d  |(P(\tau)-p_0)_j| \leq t \max_{0 \leq \tau \leq t}
|h(|P(\tau)|)| \leq 3 t   \big|h (|p_0|)\big| \, .
$$
Denote by
\begin{equation}\label{1}
R:=H_p (X(\tau), P(\tau)) -H_p (x_0, p_0) \, ,
\end{equation}
$R= (R_1, \dots, R_d)$. Using the mean value theorem we get
\begin{align*}
R_i&=\sum_{j=1}^d H_{p_i x_j} (\nu_{i},
\xi_{i})(X(t)-x_0)_j+\sum_{j=1}^d H_{p_i p_j} (\nu_{i},
\xi_{i})(P(t)-p_0)_j \, \\
&=:R_i^1+R_i^2
\end{align*}
for some $\nu_{i} \in [x_0, X(\tau)]$, $\xi_{i} \in [p_0,
P(\tau)]$, \, \, $i=1, \dots, d$. It follows that
$$
|R_i^2| \leq \max_{i,j=1, \dots, d} \left| H_{p_i p_j} (\nu_{i},
\xi_{i}) \right|  \Big( \sum_{j=1}^d |(P(\tau)-p_0)_j| \Big)
\, .
$$
Due to $|\xi_i|> M_1 > \varepsilon^{-1}$ and (ii) Theorem \ref{t1}
we get
$$
\left| H_{p_i p_j} (\nu_{i}, \xi_{i}) \right| \leq \big|h'' (|\xi_{i} |)\big| \leq \max \{ |h'' (|p_0|)|
, |h'' (|P(\tau)|)| \} \leq 3 \big|h''
(|p_0|)\big| \quad
$$
$i,j=1, \dots, d$ and so
$$
|R_i^2| \leq 9t \big|h'' (|p_0|) h (|p_0|)\big|
\leq 9 t \big|h' (|p_0|)\big|^2 \, .
$$
Similarly
$|R_i^1| \leq 9 t  \big|h' (|p_0|)\big|^2 $.
Consequently,
$$
|R| \leq \sum_{i=1}^d |R_i| \leq 18 \, d t \big|h'
(|p_0|)\big|^2 \, .
$$
Setting $c_1= \varepsilon /(36 \, d )$ and using $t \leq
|h'(|p_0|)|^{-1} \, c$ we get (under assumption \eqref{13})
\begin{equation}\label{41}
\left|H_p (X(\tau), P(\tau)) -H_p (x_0, p_0)  \right| \leq {
\varepsilon \over 2}  \,  |h'(|p_0|)| \, .
\end{equation}
If \eqref{13} does not hold then, by \eqref{46} and (ii) Theorem
\ref{t1},
$$
|H_p(X(\tau), P(\tau))| \leq
\varepsilon^{-1}+|h'(|P(\tau)|)| \leq \varepsilon^{-1}+ M_4\, .
$$
Using, by \eqref{46}, $|h' (|p_0|)|\leq M_4$ and the fact
that $z \geq \omega(M_4)$ implies $|h' (z)|> M_4$ we obtain
$|p_0| \leq \omega(M_4)$.
Hence
$$
\left|\left(p_0, H_p (X(\tau), P(\tau)) -H_p (x_0, p_0) \right)
\right| \leq 2 \omega(M_4) ( \varepsilon^{-1}+M_4)\, .
$$
Combining this and \eqref{45} we arrive at \eqref{105}.

\noindent\emph{Step 2.} If \eqref{13} holds then, by \eqref{41}
\begin{align*}
|x-x_0| -t |H_p(x_0, p_0)|
&\geq -\left| x-x_0 - t H_p(x_0, p_0)\right|\\
&= -\Big| \int_0^t \left(H_p (X(\tau), P(\tau)) -H_p (x_0, p_0)
\right) \, d \tau \Big|
\\
&\geq  -{ t \varepsilon \over 2}  \, |h'(|p_0|)| \, ,
\end{align*}
and so  using (iii) in Lemma \ref{l6}, we get
\begin{equation}\label{43}
|x-x_0|  \geq {\varepsilon t \over 2} \, |h'(|p_0|)| -t M_2 \,.
\end{equation}
If \eqref{13} does not hold, then, due to \eqref{46},
\begin{equation}\label{42}
|x-x_0| \geq 0 \geq  t |h' (|p_0|)|- M_4 t \, .
\end{equation}
Combining \eqref{43} and \eqref{42}  (recall $\varepsilon <1$) we
arrive at
$$
{|x-x_0| \over t} \geq {  \varepsilon \over 2} \,   |h'
(|p_0|)|-M_2 - M_4 \, .
$$
This and  \eqref{55} yield
\begin{equation}\label{104}
M_4^{-1}{|x-x_0| \over t}-M_5 \leq  |h' (|p_0|)| \leq {2
\over \varepsilon }\, {|x-x_0| \over t} +M_5 \, ,
\end{equation}
where $M_5:= 2 \varepsilon^{-1} \, ( M_2+M_4)$. Applying $\omega
(\cdot)$ to both sides of \eqref{104} proves (i) and (ii)
Lemma \ref{l7}.

\noindent\emph{Step 3.} An application of \eqref{105} and (iv)
Lemma \ref{l6} give
\begin{align}
\left(p_0 , x-x_0\right)
&= t \left(p_0 , H_p (x_0,
p_0)\right)+\int_0^t \big(p_0 , H_p (X(\tau), P(\tau))- H_{p}(x_0,
p_0) \big) \,
d\tau \\
 &\geq t \left(p_0 , H(x_0, p_0)\right) -{\varepsilon t
\over 2}\, |h' (|p_0|)| \, |p_0| - 2 \omega (M_4)  (
\varepsilon^{-1}+M_4)t
\\
 &\geq {\varepsilon t \over 2}\, |h' (|p_0|)| \,
|p_0| - M_3 t- 2 \omega(M_4) ( \varepsilon^{-1}+M_4)t \, .
\end{align}
Using the first inequality in \eqref{104} and setting $M_6:=M_3+2
\omega(M_4) ( \varepsilon^{-1}+M_4)$ we complete the proof.
\end{proof}


\section{Proof of Theorem \ref{t1}} \label{s3}

Let
\begin{equation}\label{96}
\|B\| := \max_{1 \leq i \leq n,\, 1 \leq j \leq m} |(B)_{ij}|
\end{equation}
for any $B \in \mathbb{R}^{n \times m}$. We say that $R(t)= { O}
(r(t))$ \,  $t \in {\bf T} \subset \mathbb{R}$, where $R(t) \in
\mathbb{R}^{n \times m}$, $r (t) \in  \mathbb{R}_{+}$ if
\begin{equation}\label{76}
\|R (t) \| \leq C r (t)
\end{equation}
for some constant $C >0$ and all $t \in {\bf T}$.

\begin{lemma}\label{l2}
Let $c_1, t_1$  be as in Lemma \ref{l7} and the conditions of
Theorem \ref{t1} be satisfied. Then  for  all $t \in (0, t_1)$, $c
\in (0, c_1)$, $x_0 \in \mathbb{R}^d$, $ p_0 \in V_{c, t}$ one
has
\begin{gather} \label{7}
{\pa X (s) \over \pa p_0} = s H_{pp} (x_0, p_0 )+ s \gamma { O}
(c +t) , \\
\label{12} {\pa P (s) \over \pa p_0} = E_d + { O} (c+t) ,
\end{gather}
where  $s \in [0,t]$, $E_d$ is the identity  matrix,
\begin{equation}\label{97}
\gamma=|h'' (|p_0|)|+1
\end{equation}
and ${ O}(\cdot)$ is taken uniformly in $x_0, p_0$ and $s$.
\end{lemma}

\begin{proof}
\emph{Step 1.} From the system \eqref{4} we find
\begin{equation}\label{9}
\ddot{X} (\tau)= A (X(\tau), P(\tau)),
\quad
A (x, p) = H_{px} H_p-H_{pp} H_x.
\end{equation}
Here we omit $x, p$ in arguments of the derivatives of $H$, the
terms $H_{px} H_p$, $H_{pp} H_x$ are understood as matrix products
and $A(x, p) \in \mathbb{R}^d$. Differentiating with respect to
$p_0$ the Taylor's developments
\begin{equation} \label{18}
\begin{gathered}
X(s) = x_0+ \dot{X} (0) s + \int_0^s (s-\tau) \, \ddot{X} (\tau)
\, d \tau ,
\\
 P(s) = p_0 + \int_0^s \dot{P} (\tau) \, d \tau
\end{gathered}
\end{equation}
and using $\pa \dot{X} (0)/ \pa p_0 = H_{pp} (x_0, p_0 )$ gives
\begin{equation}\label{29}
{\pa X (s) \over \pa p_0 } = H_{pp} (x_0, p_0 ) s + \int_0^s
(s-\tau) \, {\pa \ddot{X} (\tau) \over \pa p_0 } \, d \tau
\end{equation}
and
\begin{equation}\label{31}
{\pa P (s)  \over \pa p_0} = E_d + \int_0^s {\pa \dot{P} (\tau)
\over \pa p_0 } \, d \tau
\end{equation}
respectively, where
\begin{gather}\label{35}
{\pa \ddot{X} (\tau) \over \pa p_0 }
= A_x (X(\tau), P(\tau)) \, {\pa X (\tau) \over \pa p_0}
+
A_p  (X(\tau), P(\tau))\,  {\pa P (\tau) \over \pa p_0} \, ,
\\
\label{38}
{\pa \dot{P} (\tau) \over \pa p_0 }
=- H_{xx}  (X( \tau), P( \tau)) {\pa X (\tau)  \over \pa p_0}
-H_{xp}  (X( \tau), P( \tau))  {\pa P (\tau) \over \pa p_0}  \, .
\end{gather}
We take  $2d \times 2d $ matrix
$$
\ell (s, \tau) =
\begin{pmatrix} s^{-1}(s-\tau) \tau A_x (X(\tau), P(\tau))
& s^{-1}(s-\tau) \gamma^{-1} A_p (X( \tau), P( \tau))  \\
 -\tau \gamma H_{xx}  (X( \tau), P(\tau)) &- H_{xp}  (X(  \tau), P(  \tau))
\end{pmatrix} \, ,
$$
where  $\gamma$ is given by \eqref{97}. Define a mapping
 $L :C([0, t], \mathbb{R}^{ 2 d \times d}) \to  C([0, t],
\mathbb{R}^{ 2 d \times d}) $ by
$$
[L M] (s) := \int_0^s \ell(s, \tau) M(\tau) \, d\tau \, ,
$$
$M (\cdot) \in C([0, t], \mathbb{R}^{ 2d \times  d}) $. We
rewrite \eqref{29}-\eqref{31} as
$\mathcal{M}=\mathcal{M}_0+L \mathcal{M}$,
where
$$
\mathcal{M}= \begin{pmatrix}{ {1 \over s} \, {\pa
X (s) \over \pa p_0 }} \\
{ \gamma \, {\pa P (s) \over \pa p_0 } }
\end{pmatrix}
\quad \text{and} \quad \mathcal{M}_0= \begin{pmatrix}
H_{pp} (x_0, p_0 ) \\
\gamma  E_d
\end{pmatrix} \, .
$$
Using (ii) in Theorem \ref{t1}, we get
$\| \mathcal{M}_0 \| =O( \gamma)$.
Thus
\begin{equation}\label{8}
\mathcal{M} = \sum_{n=0}^\infty { L}^n \mathcal{M}_0  = \mathcal{M}_0 +
\|{L}\|  { O} (\gamma)
\end{equation}
provided $\|{L}\| <1$.

\noindent\emph{Step 2.} We now estimate $\|{L}\|$. Using the elementary
formula
\begin{equation}\label{77}
\|B_1 B_2\| \leq \nu \|B_1\| \|B_2\| \quad \forall B_1 \in
\mathbb{R}^{n \times \nu}, B_2 \in \mathbb{R}^{\nu \times m}
\end{equation}
we obtain
$$
\max_{0 \leq s \leq t} \left\| \int_0^s \ell(s, \tau) M(\tau) \,
d\tau \right\| \leq s d \max_{0 \leq  \tau \leq s \leq t} \|
\ell(s, \tau)  \| \, \, \max_{0 \leq \tau \leq t} \| M(\tau) \| \,.
$$
Hence
$$
\|L\| \leq  s d \max_{0 \leq  \tau \leq s \leq t} \| \ell(s, \tau)
\| \, .
$$
Since $\tau \leq s$ and $s^{-1}(s-\tau) \leq 1$, it follows that
\begin{equation} \label{108}
\begin{aligned}
 \max_{0 \leq  \tau \leq s \leq t} \| \ell(s, \tau)  \|
&\leq  s \max_{0 \leq  \tau \leq t}  \|  A_x (X(\tau), P( \tau))
\| + \gamma^{-1} \max_{0 \leq \tau \leq t} \| A_p (X( \tau), P(
\tau)) \|
\\
 &\quad  + s \gamma \max_{0 \leq \tau \leq t} \| H_{xx}
(X( \tau), P( \tau))\| + \max_{0 \leq \tau \leq t} \| H_{xp} (X(
\tau), P( \tau))\| \, .
\end{aligned}
\end{equation}
Applying \eqref{28} and (ii) Theorem \ref{t1} to \eqref{9}, we have
\begin{equation} \label{68}
\begin{aligned}
\|A ( x, p)\| &\leq d \|H_{xp}\|\, \|H_p\|+ d \|H_{pp}\| \, \|H_x\| \\
 &\leq d |h' (|p|)|^2+ d \left|h''
(|p|) h' (|p|)\right| \\
 &\leq 2 d  \,  |h' (| p|)|^2  ,
\end{aligned}
\end{equation}
provided $|p| \geq M_1 $. Similarly we obtain
\begin{gather*}
\| A_x ( x, p) \| \leq 4d   \, |h' (|p|)|^2 \, , \\
\begin{aligned}
\|A_p (x,p)\|
&\leq 3 d \big|h'' (|p|) \,  h' (|p|)\big|
+d \big|h^{\prime \prime \prime} (|p|)  \, h (|p|)\big| \\
&\leq 4 d \big|h'' (|p|)  \, h' (|p|)\big|
\end{aligned}
\end{gather*}
for $|p| \geq M_1$. Consequently,
\begin{gather}\label{56}
A_x ( x, p) = (h' (|p|))^2 { O}(1)+{  O} (1), \\
\label{22} A_p (x,p) = \big|h'' (|p|) \, h'
(|p|)\big| { O}(1)+{ O} (1)
\end{gather}
for all $p \in \mathbb{R}^{d}$.
Hence
$$
s^2  A_x (X (\tau) , P (\tau))= { O}([s h' (|P(\tau)|)]^2)
+{ O} (s^2) \, .
$$
By \eqref{10},  we get
\begin{equation}\label{65}
s |h' (|P(\tau)|)| \leq M_4 (s |h' (|p_0|)|+s) \leq M_4
(c+s)
\end{equation}
and so
\begin{equation}\label{19}
s^2  A_x (X (\tau) , P (\tau)) = { O}(c^2+t^2) .
\end{equation}
Since, by \eqref{10},
$\gamma^{-1} |h''(|P(\tau)|)|= O(1)$,
then using \eqref{22}, \eqref{65}  and $\gamma^{-1} \leq 1$ we
find
\begin{equation}\label{2}
s \gamma^{-1} A_p (X (\tau) , P (\tau)) ={ O} (|sh'
(P(\tau)) |) + \gamma^{-1}{ O} (s)= { O} (c+t).
\end{equation}
Piecing together \eqref{19} and \eqref{2} gives
\begin{equation}\label{110}
s^2 \max_{0 \leq \tau \leq t}  \|  A_x (X(\tau), P( \tau)) \| + s
\gamma^{-1} \max_{0 \leq \tau \leq t} \| A_p (X( \tau), P( \tau))
\|  = O(c+t) \, .
\end{equation}
Similarly  we get
\begin{equation}\label{109}
s^2 \gamma \max_{0 \leq \tau \leq t} \| H_{xx} (X( \tau), P(
\tau))\| + s \max_{0 \leq \tau \leq t} \| H_{xp} (X( \tau), P(
\tau))\| = O(c+t) \, .
\end{equation}
Combining \eqref{108}, \eqref{110}, \eqref{109} we arrive at $s
\max_{0 \leq \tau  \leq s \leq t} \| \ell(s, \tau) \|=O(c+t) $.
Hence $\|{L}\| = O(c+t)$. Consequently we rewrite $\eqref{8}$ as
\begin{gather} \label{32}
{1 \over s}  {\pa X (s) \over \pa p_0 } = H_{pp} (x_0, p_0 ) +
\gamma { O} (c +t),
\\
\label{36} \gamma  {\pa P (s) \over \pa p_0 }  = \gamma (E_d
 + { O} (c +t)).
\end{gather}
Multiplying \eqref{32} and \eqref{36} by $s$ and  $\gamma^{-1}$
respectively we complete the proof.
\end{proof}

\begin{corollary}\label{c1}
Under the conditions of Theorem \ref{t1} there exist  $c_2 \in
(0,c_1)$, $t_2 \in (0, t_1)$ such that for  all $t \in (0, t_2)$, $c
\in (0, c_2) $ and $ p_1, p_2 \in V_{c, t}$ one  has
\begin{equation}\label{70}
|X(t, x_0, p_2)-X(t, x_0, p_1)|^2 \geq {t^2 \varepsilon^2 \over 2}
\, |p_1-p_2|^2 \, .
\end{equation}
\end{corollary}

\begin{proof}
One has
\begin{equation} \label{44}
\begin{aligned}
& \left|X(t,x_0,p_2)-X(t,x_0,p_1) \right|^2    \\
&= \int_{0}^1 \int_{0}^1 {\left(p_2-p_1\right)}^T
    {\Big({\pa X \over \pa p_0 } (t,x_0, p_1+s(p_2-p_1)) \Big)}^T   \\
&\quad \times
  \Big({\pa X \over \pa p_0 }
  (t,x_0, p_1 + \tau  (p_2-p_1))\Big) \left(p_2-p_1\right)  \, d\tau \,ds
  \,,
\end{aligned}
\end{equation}
where $({\pa X /\pa p_0})^T$ is transposed matrix to ${\pa X /\pa
p_0}$. We denote by
$$ q_1=p_1+s (p_2-p_1) \, , \quad q_2=p_1+\tau (p_2-p_1) \, .$$
From \eqref{7}, we obtain
\begin{equation} \label{69}
\begin{aligned}
\Big({\pa X (t, x_0, q_1) \over \pa p_0}\Big)^T
{\pa X (t, x_0, q_2) \over \pa p_0}
&=
t^2( H_{pp} (x_0,q_1)+ \gamma_1 R_1)
( H_{pp} (x_0,q_2)+ \gamma_2 R_2)\\
&=: t^2 H_{pp} (x_0,q_1) H_{pp} (x_0,q_2)+t^2 {R},
\end{aligned}
\end{equation}
where $\gamma_i=|h'' (|q_i|)|+\varepsilon^{-1}$,
$i=1, 2$ and $\|R_i\|\leq (c+t) \kappa$ for some constant
$\kappa > 1$. Using \eqref{77} we get
$$
\| {R} \| \leq d\left( \gamma_1 \|H_{pp} (x_0,q_2)\|\, \|R_1\|+
\gamma_2 \|H_{pp} (x_0,q_1)\| \, \|R_2\| +\gamma_1 \gamma_2 \,
\|R_1\| \, \|R_2\|\right)
$$
Let us take $c_2<c_1, t_2<t_1$ such that
\begin{equation}\label{95}
4d^2 (c_2+t_2) \kappa^2 \varepsilon^{-4} < {1 \over 2} \, .
\end{equation}
Because of (ii) in Theorem \ref{t1},
$\|H_{pp} (x_0,q_i)\| \leq \gamma_i$. Hence
\begin{align*}
\| {R} \|  &\leq d (c+t) \big(\|H_{pp} (x_0,q_1)\| \kappa +
\|H_{pp} (x_0,q_2)\| \kappa + (c+t)\gamma_1 \gamma_2 \kappa^2\big)\\
&\leq
d(c+t)(\gamma_1 \kappa+\gamma_2\kappa+2\gamma_1 \gamma_2 \kappa^2)\\
&\leq 4d(c+t)\gamma_1 \gamma_2 \kappa^2 \\
&= 4d (c+t) \kappa^2 \big(\varepsilon^{-1}+|h''(|q_1|)| \, \big) \big(\varepsilon^{-1}+|h''(|q_2|)| \, \big) \, ,
\end{align*}
where we have used   $\kappa, \gamma_1, \gamma_2 >1$, $c+t<c_1+t_1<2$.
Due to this estimate and the fact that, by (i)
Theorem \ref{t1},
\begin{equation} \label{50}
\begin{aligned}
\int_{0}^1 \int_{0}^1 H_{pp} (x_0,q_1) H_{pp} (x_0,q_2) \, ds d
\tau &= \Big( \int_{0}^1 H_{pp} (x_0,q_1) \, ds \Big)^2 \\
 &\geq \varepsilon^2 \Big( \int_{0}^1 \big(1+|h''(|q_1|)| \, \big) \, ds \Big)^2 E_d
\end{aligned}
\end{equation}
we get
\begin{equation} \label{71}
\begin{aligned}
\int_{0}^1 \int_{0}^1 \|{R}\|  \, ds d \tau \, E_d
&\leq 4d (c+t)
\kappa^2 \varepsilon^{-2} \Big( \int_{0}^1 \big(1+|h''(|q_1|)| \, \big) \, ds \Big)^2 E_d
\\
 &\leq 4d (c+t) \kappa^2 \varepsilon^{-4} \int_{0}^1
\int_{0}^1 H_{pp} (x_0,q_1) H_{pp} (x_0,q_2) \, ds d \tau \,.
\end{aligned}
\end{equation}
Substituting \eqref{95} in \eqref{71} and using the elementary
formula (recall \eqref{96})
$$
-d\|B\| E_d\leq B \leq d \|B\| E_d \quad \forall B \in \mathbb{R}^{d \times d}
$$
we obtain
\begin{equation} \label{66}
\begin{aligned}
\int_{0}^1 \int_{0}^1 R \, ds d \tau
 &\geq -d \int_{0}^1
\int_{0}^1 \|{R}\| \, ds d \tau \, E_d \\
 &\geq -{1 \over 2} \,\int_{0}^1 \int_{0}^1 H_{pp}
(x_0,q_1) H_{pp} (x_0,q_2) \, ds d \tau \, .
\end{aligned}
\end{equation}
Then combining \eqref{69}, \eqref{66} and using again \eqref{50}
we arrive at
\begin{align*}
&\int_{0}^1 \int_{0}^1 \Big({\pa X (t, x_0, q_1) \over
\pa p_0}\Big)^T {\pa X (t, x_0, q_2) \over \pa p_0} \, ds d \tau
\\
&\geq {t^2 \over 2} \,\int_{0}^1 \int_{0}^1 H_{pp} (x_0,q_1)
H_{pp} (x_0,q_2) \, ds d \tau
\\
&\geq {t^2 \varepsilon^2 \over 2} \, E_d \, .
\end{align*}
Combining this and \eqref{44} we complete the proof.
\end{proof}

\begin{proof}[Proof of Theorem \ref{t1}]
Let $t_2, c_2$ be as in Corollary \ref{c1}, $M_4$ is from
Lemma \ref{l1}, $\varepsilon>0$ is  from the conditions of
Theorem \ref{t1}.
\par
Let us take
\begin{gather}\label{78}
M_7:=\max_{|p| \leq M_1} \left[\left(
\varepsilon^{-1}+|h'(|p|)|\right)^2 + \left(
\varepsilon^{-1}+|h''(|p|)|\right) \left(
\varepsilon^{-1}+|h(|p|)|\right) \right] \, ,
\\
\rho:=\min\big\{ {\varepsilon \over 8 d (4 M_4^2+ M_7) }\, , \,
\, c_2 \big\} \, ,
\\
\label{91} T := \min\big\{ {\varepsilon \rho \over 4 M_4
(|h' (0)|^2+1)} \, , \, \, {\varepsilon \rho \over 2 M_2 }
\, \, , \rho,  t_2 \big\} \, ,
\\
 r:= {\varepsilon \rho \over 2} \, .
\end{gather}
Let  $W_t:=V_{\rho, t}$ (recall \eqref{6}) and
\begin{equation}\label{30}
\mathfrak{D}:
p_0 \to X(t, x_0,   p_0) ,  \quad
\mathfrak{D}:
W_t \to \mathbb{R}^d
\end{equation}
\emph{Step 1.} We will show that $B_r (x_0)\subset \mathfrak{D} (W_t)$.
Using \eqref{9}, \eqref{18}, (iii) in Lemma \ref{l6} and the fact
that $\dot{X} (0)=H_p (x_0,p_0) $, we have
\begin{equation} \label{58}
\begin{aligned}
|X(t) -x_0|
&\geq t |\dot{X} (0)|- \int_0^t (t-\tau) \,| \ddot{X} (\tau) | \, d \tau \\
&\geq t | H_p (x_0, p_0)| - \int_0^t (t-\tau) \, |A
  (X(\tau), P(\tau) ) | \, d \tau \\
&\geq \varepsilon t |h' (|p_0|)|-t M_2 - t^2
\max_{ 0 \leq \tau \leq t} \, |A (X(\tau), P(\tau) ) |\,  .
\end{aligned}
\end{equation}
Due to \eqref{78},
\begin{align*}
\|A ( x, p)\|
&\leq d \|H_{xp}\|\, \|H_p\|+ d \|H_{pp}\| \, \|H_x\| \\
&\leq d \, \big[\left( \varepsilon^{-1}+|h'(|p|)|\right)^2+
\left( \varepsilon^{-1}+|h''(|p|)|\right) \left(
\varepsilon^{-1}+|h(|p|)|\right) \big]\\
&\leq d M_7
\end{align*}
for any $x \in \mathbb{R}^d$,  $|p| \leq M_1$.  Piecing together
this and \eqref{68} we obtain
$$
\|A ( x, p)\| \leq 2 d  \,  |h' (| p|)|^2 +dM_7
$$
for all $x, p \in \mathbb{R}^n$. This and \eqref{10} imply
\begin{equation} \label{67}
\begin{aligned}
|A (X(\tau), P(\tau) ) | &\leq 2 d  \,  M_4^2 (|h' (|
p_0|)|+1)^2 +dM_7 \\
 &\leq 4 d  \,  M_4^2 (|h' (| p_0|)|^2+1)
+d M_7 \\
 &\leq  d  \,  (4 M_4^2 +M_7)(|h' (| p_0|)|^2+1)\, .
\end{aligned}
\end{equation}
Substituting \eqref{67} into \eqref{58} and using $2 t M_2
<\varepsilon \rho$, \,  $t |h' (|p_0|)|=\rho$ we obtain
\begin{align*}
|X(t) -x_0|
&\geq \varepsilon t |h' (|p_0|)|-t M_2  -t^2 d
(4 M_4^2+ M_7) (|h' (|p_0|)|^2+1) \\
&\geq {\varepsilon \rho \over 2}  - d (4 M_4^2+ M_7)  (\rho^2+t^2)\,
\end{align*}
for $p_0 \in \pa W_t$, $x_0 \in \mathbb{R}^d$. Since $t < T <
\rho $ and $ \varepsilon > 8 d (4 M_4^2+ M_7)  \rho $, it follows
that
$$
|X(t) -x_0| > {\varepsilon \rho  \over 2} - 2 d (4 M_4^2+ M_7)
\rho^2 > {\varepsilon \rho  \over 4} \,  \,
$$
or
\begin{equation}\label{98}
\min_{p_0 \in \pa W_t} |X(t, x_0, p_0) -x_0| > r
\end{equation}
for any $x_0 \in \mathbb{R}^d$. On the other hand, using
\eqref{55} with $p_0=0$ and \eqref{91} we have
\begin{equation}\label{99}
|X(t, x_0, 0)-x_0| \leq t M_4 (|h'(0)|+1) < T M_4
(|h'(0)|+1) < {\varepsilon \rho  \over 4} = r \, .
\end{equation}
Combining \eqref{98}, \eqref{99} shows that $ x_0 \in \mathfrak{D} (W_t)$. Moreover,  $B_r  (x_0) \subset \mathfrak{D} ( W_t)$.
\par
\emph{Step 2.} Corollary \ref{c1} implies that $\mathfrak{D}$ is
injective. It suffices to notice that, by \eqref{7} and (i)
Theorem \ref{t1}, ${\pa X /\pa p_0} \not = 0$ and so the implicit
function theorem implies that $\mathfrak{D}$ is a local
diffeomorphism for any $t < T$.
\end{proof}

\section{Proof of Lemma \ref{l3}}\label{s4}

For all $x_0, x \in B_r(x_0)$ and $t <T$ we define the \emph{action
function} by
\begin{equation}\label{11}
\sigma (t, x_0, p_0)= \int_0^t P(\tau)\, d X (\tau) -H (X(\tau),
P(\tau)) \, d \tau \, .
\end{equation}
Recall that $X(\tau)=X(\tau, x_0, p_0)$, $P(\tau)=P(\tau,x_0,p_0)$
is solution for \eqref{4} with initial conditions $X(0)=x_0,
P(0)=p_0$ and $p_0(t,x,x_0)$ is defined from the equation $X(t,
x_0, p_0(t,x,x_0))=x$. For any fixed $x_0 \in \mathbb{R}^d$ we
set
$$
p(t,x):=P(t, x_0, p_0 (t,x,x_0)) \, .
$$
The convexity of $H(x,p)$ with respect to the second variable and
\eqref{151} imply
$$
L(x, v) = \sup_{p \in \mathbb{R}^d} (pv -H (x, p)) \,  .
$$
Hence
\begin{equation}\label{162}
I_y (t, x, x_0) = \int_0^t L(y  (\tau) , \dot{y} (\tau)) \, d \tau
\geq  \int_0^t \left[ \dot{y} (\tau) p(\tau, y(\tau)) -H(y(\tau),
p(\tau, y(\tau))) \right]\, d \tau
\end{equation}
for any smooth trajectory $y(\tau)$ with boundary conditions
$y(0)=x_0$, $y(t)=x$. However for $y(\tau)=X (\tau)$ we have
$p(\tau, y(\tau))=P(\tau)$. Thus the r.h.s. of \eqref{162} is
equal to $\sigma (t, x_0, p_0 (t, x, x_0))$. This and \eqref{92}
yield
$$
S(t, x, x_0) = \sigma (t, x_0, p_0 (t, x, x_0)) \, .
$$

\begin{lemma}\label{l4}
For each $t \in (0, T)$, $x_0 \in \mathbb{R}^d$ we have
\begin{equation}\label{51}
S(t, x_0, x_0)  \leq M_8
\end{equation}
for some constant $M_8>0$.
\end{lemma}

\begin{proof}
Using \eqref{70} with $p_1=0$ and $p_2 =p_0 (t, x_0, x_0)$ gives
\begin{equation} \label{57}
\begin{aligned}
|X(t,x_0,0)- x_0 |^2 &=|X(t,x_0,0)- X(t,x_0,p_0
(t, x_0, x_0))|^2
\\
&\geq {t^2 \varepsilon^2  \over 2} \, {|p_0 (t, x_0,
x_0)|}^2 \, .
\end{aligned}
\end{equation}
Due to \eqref{55},
$$
\left|X(t,x_0, 0)- x_0 \right|^2 \leq t^2 M_4^2 \big(1+|h'
(|0|)|\big)^2  \, .
$$
Combining this and \eqref{57} gives
\begin{equation}\label{54}
|p_0 (t, x_0, x_0)|^2 \leq {2 \over \varepsilon^2}\, M_4^2
\big(1+|h' (|0|)|\big)^2 .
\end{equation}
On the other hand, an application of (ii) in Theorem \ref{t1} and
\eqref{26} to \eqref{11} shows that $\sigma(t,x_0, p_0 )$ is
bounded if $|p_0|$ is bounded. This remark together with
\eqref{54} completes the proof.
\end{proof}

\begin{proof}[Proof of Lemma \ref{l3}]
Let us  choose $M_9 >0 $ such that
\begin{gather}\label{23}
{M_9 \over M_4}-M_5 \geq |h' (M_1)|, \\
\label{5}
M_{10}:= {\varepsilon \over 2}\, \omega \big({M_9 \over M_4 }-
M_5 \big) \big({M_9 \over M_4}-M_5 \big)-M_6> 0 \, .
\end{gather}
We take  $t \in (0, T)$, $y, y_0 \in \mathbb{R}^d$ such that
$|y-y_0|=r$. Using
$$
{\pa S (t, y, y_0) \over \pa y_0} =-p_0(t, y ,y_0)
$$
and applying the elementary formula $\phi(1)=\phi(0)+\int_0^1
\phi' (\tau)\, d\tau$ to
\[
\phi(\tau) := S(t, y,y+\tau(y_0-y)),
\]
 $\tau \in [0,1]$ we get
\begin{equation} \label{63}
\begin{aligned}
S(t, y, y_0) &=S(t,y,y)+\int_0^1 \left(p_0 (t,y,y+\tau(y_0-y)),
y-y_0\right) \, d \tau\\
 &=S(t,y,y)+\int_0^1 \left( p_0^\tau , y-\xi_\tau
\right) \, {d \tau \over \tau} \, ,
\end{aligned}
\end{equation}
where $\xi_\tau=y+\tau(y_0-y)$ and $p_0^\tau=p_0 (t,y,\xi_\tau)$.
 By (i) and (iii) in Lemma \ref{l7}, we have
\begin{gather}
\label{24} |p^\tau_0| \geq \omega \big( {r\tau \over t M_4} -
M_5\big) \quad \text{provided that }  {r\tau \over t M_4} -
M_5>M_4 \, , \\
\label{107} \left( p_0^\tau , y-\xi_\tau \right)
\geq {\varepsilon \over 2}\, |p^\tau_0| \big({r \tau \over M_4}-t M_5
\big)-t M_6 \, ,
\end{gather}
where we have used $|y-\xi_\tau |=\tau r$. Setting
$s =t  M_9 / r$
and using \eqref{24}-\eqref{107} we get
\begin{align*}
\left( p_0^\tau , y-\xi_\tau \right)  &\geq {\varepsilon \over
2}\, |p^\tau_0| \big(t \, {M_9 \over M_4}-t M_5 \big)-t M_6
> t M_{10}  > 0
\quad \text{for } \tau  \in [s, 1] \, ,
\end{align*}
where we have used $\tau r \geq  t M_9 $. Notice that due to
\eqref{23} the condition in \eqref{24} is satisfied.

If we assume that $t \leq  r /(2M_9)$,
then $s \leq 1/2$ and so
\begin{equation}\label{20}
\int_0^1 \left( p_0^\tau , y-\xi_\tau \right) \, {d \tau \over
\tau} \geq \int_{1/2}^1 -\Big|\int^{s}_0 \Big| \, .
\end{equation}
Using again \eqref{107} and, due to (i) Lemma \ref{l7},
$$
|p_0^\tau|  \geq \omega \big({\tau r \over t  M_4 }- M_5 \big)
$$
we obtain
\begin{align}\label{102}
( p_0^\tau , y-\xi_\tau)
&\geq {\varepsilon \over 2}|p^\tau_0| \big({r \over 2 M_4}-t M_5 \big)
-t M_6 \\
 &\geq {\varepsilon \over 2} \omega \big({r  \over 2 t
M_4  }- M_5 \big)  \big({r \over 2 M_4}-t M_5 \big)-t M_6
\quad \text{for} \, \, \tau \in [{1 \over 2}, 1]
\, .
\end{align}
On the other hand, due to (ii) Lemma \ref{l7}  for
$0 \leq \tau \leq s$, we have
$$
|p^\tau_0|  \leq \omega \big( {2 \over \varepsilon} \, {r \tau
\over t} +M_5\big)  \leq \omega \big({2 \over \varepsilon } \,
M_9+M_5 \big) =:M_{11}
$$
and so
\begin{equation}\label{103}
\Big| \int_0^s \left( p_0^\tau , y-\xi_\tau \right) \, {d \tau
\over \tau} \Big| \leq r \int_0^s |p_0^\tau| \, d \tau \leq r
M_{11} \, .
\end{equation}
Combining \eqref{63}, \eqref{20}, \eqref{102}, \eqref{103} we
arrive at
\begin{equation} \label{3}
\begin{aligned}
&\min_{|y-y_0|=r} S(t, y, y_0) \\
&\geq {-M_8+ \Big[ {\varepsilon \over 2} \omega \big({r  \over 2 t M_4  }
-M_5 \big)  \big({r \over 2 M_4}-t M_5 \big)- t M_6 \Big]
\ln 2 - r M_{11} }
\end{aligned}
\end{equation}
for $t < r/(2M_9)$.

\noindent\emph{Step 2.}
We choose $r_1 <r$ such that
\begin{equation}\label{74}
2r_1 <{\varepsilon r \ln 2 \over 16 M_4} \,,  \quad
{4r_1 \over \varepsilon} < {r \over 4 M_4} \, .
\end{equation}
Using \eqref{63} and (i) Lemma \ref{l7},  we get
\begin{equation} \label{14}
\begin{aligned}
\max_{|y-y_0|=r_1} S(t, y, y_0)
&\leq M_8+r_1 \int_0^1 |p_0(t,y,y+ \tau(y-y_0))|\, d \tau \\
&\leq M_8+r_1 \omega \big({2r_1 \over \varepsilon t} +M_5 \big)
\end{aligned}
\end{equation}
for $y, y_0 \in \mathbb{R}^d$ such that $|y-y_0|=r_1$.

Since $\omega (z)$ is increasing function and $\omega (z)
\to +\infty$, then there exists $T_1<r/(2M_9)$ such that
for all $t <T_1$
\begin{equation}\label{106}
\text{right-hand side of \eqref{3}}
 \geq {\varepsilon r \ln 2 \over 16
M_4}  \omega \big({r \over 4 t M_4  } \big)
\end{equation}
and
\begin{equation}\label{75}
\text{right-hand side of \eqref{14}} \leq 2 r_1  \omega \big({4r_1
\over \varepsilon t} \big) \, .
\end{equation}
Applying \eqref{74}, \eqref{106}, \eqref{75} to \eqref{3} and
\eqref{14} we arrive at \eqref{17}. Finally we notice that
\eqref{112} is a direct consequence of \eqref{3}.
\end{proof}


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