## IVP and Picard’s

By IVP (Initial Value Problem), we mean the problem about solving

Of course we do hope we can solve this problem with ease, with a simple result. But that won’t happen if the function $f$ is ‘ugly’ enough. Hence the problem is, generally and theoretically, when we can get a unique solution? When does some solution exist? Fortunately Picard make it to ensure that

If $f$ is uniformly Lipschitz continuous in $y$ and continuous in $x$ on $R={(x,y):|x-x_0| \leq a,|y-y_0| \leq b}$, then for some $\varepsilon>0$, there exists a unique solution $y$ to the IVP on the interval $[x_0-\varepsilon,x_0+\varepsilon]$.

Interesting enough, there are several ways on different levels to prove it. This blog post goes with three proofs about that.

## Proving Picard’s existence and uniqueness theorem

### Some preparation

By uniformly Lipschitz continuous, we mean that for all $y \in R$, $f$ satisfies

for some $L > 0$. This condition is useful in many different branch of mathematics.

Also, it’s trivial to verify that the IVP is equivalent to

And yes, our job becomes finding such a $y$ satisfying this equation.

### A sketch of the proof in elementary calculus

Honestly the proof is kind of long. I’ll leave the basic steps here. First, we define the Picard sequence by

for $n=0,1,\cdots$. It can be shown by induction that

where $M = \sup\limits_{(x,y) \in R}|f(x,y)|$ and $\varepsilon = \min\left(a,\frac{b}{M}\right)$. We want to prove that

is the solution to the IVP, where Lipschitz condition comes into play by considering

Finally, it should be shown that $y$ is the unique solution. To do this, it can be shown that, if we have two solutions, say $y=u(x)$ and $y=v(x)$, then $u(x)-v(x)=0$.

### Osgood’s condition partially implies Picard’s (uniqueness)

Osgood’s condition is much weaker than Lipschitz’s. Under Osgood’s condition, it’s easy to check the uniqueness, but there is no way to get the result (while Lipschitz’s gives you the way) through this condition.

$f(x,y)$ has

at most onesolution in every point in $R$ if $f$ is continuous and satisfies theOsgood’s condition, namelyin $R$ where $F$ is a continuous function such that $F(t)>0$ for all $r>0$. Also, $F$ is defined in such a way that

for some $r_1>0$.

Naturally, if we define $F(r)=Lr$, we have $\int_{0}^{r_1}\frac{1}{Lr}dr=\infty$. But we are not g

#### Proof of Osgood’s

We’ll prove this theorem indirectly. That is, if there exists some point $(x_0,y_0) \in R$ such that $f$ has at least two solutions, then $f$ does not satisfy Osgood’s condition, which is equivalent to the statement that if $f$ satisfies Osgood’s, then $f$ has no more than solution. But the existence is not guaranteed.

Suppose now there exists a point $(x_0,y_0) \in R$ such that $y’=f(x,y)$ has two distinct solutions

and $y_1 \neq y_2$ for at $x_1 \neq x_0$. W.L.O.G. we suppose that $x_1 > x_0$. Define

and $r(x)=y_1(x)-y_2(x)$ on $[x_s,x_1]$. The derivative of $r$ is interesting since we have

Then the desired improper integral converges since we have

Therefore $f$ does not satisfy Osgood’s condition.

### Banach FPT is applied onto Picard’s

#### What is Banach FPT

A map $T: X \mapsto X$ defined on a complete metric space $(X,d)$ is a contraction if there exists some $k \in [0,1)$ such that

Banach Fixed Point Theorem states that, $T$ admits a fixed point, namely $T(x)=x$ for some $x \in X$.

The proof is an application of Cauchy sequence (notice that $(X,d)$ is complete). Pick an arbitrary $x_0 \in X$, by defining $T(x_n)=x_{n+1}$, we have

which finally goes to

${x_n}$ is Cauchy then since we have

Since $(X,d)$ is complete, we see ${x_n}$ converges. Also, $T$ is (uniformly) continuous, therefore

Uniqueness follows from the uniqueness of limit.

#### Proving Picard’s using Banach FPT

Fortunately, Picard’s existence and uniqueness theorem can be directly proved using Banach FPT. All we need is a proper translation.

##### Complete metric space

Let $\mathcal{C_B}(R)$ be all bounded continuous function on $R$, then $\mathcal{C_B}(R)$ is complete considering the metric by

##### Contraction map

The functional $T:\mathcal{C_B}(R)\mapsto\mathcal{C_B}(R)$ by

is the contraction we are looking for, if we take uniform Lipschitz’s condition into consideration. Namely, if we have $\varepsilon<\frac{1}{L}$, we can see that

Therefore by Banach FPT, the functional $T$ has a unique fixed point, which is equivalent to Picard’s existence and uniqueness theorem. Further, the solution can be theoretically obtained by taking

where $y(x_0)=y_0$ comes from the initial value problem.