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Ordinary Differential Equations 12 | Picard–Lindelöf Theorem [dark version] thumbnail

Ordinary Differential Equations 12 | Picard–Lindelöf Theorem [dark version]

5 min read

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TL;DR

Rewrite the ODE ẋ = V(x) with x(0)=x0 as the integral equation α(t)=x0+∫_0^t V(α(s))ds and define F(α)(t)=x0+∫_0^t V(α(s))ds.

Briefing

The Picard–Lindelöf theorem guarantees not just that an initial value problem for an ordinary differential equation has a solution, but that—under a local Lipschitz condition—that solution is unique. The key move is turning the differential equation into a fixed-point problem: candidate solutions are functions, and the “integral form” of the ODE becomes a mapping on a carefully chosen space of functions. Once that mapping is shown to be a contraction, Banach’s fixed point theorem delivers existence (and, together with earlier uniqueness work, the full Picard–Lindelöf result).

Start with the standard initial value problem written as ẋ = V(x) with x(0) = x0, where V is locally Lipschitz. Uniqueness had already been established earlier, so the focus here is existence. The method rewrites the ODE in integral form: any solution α should satisfy

F(α)(t) = x0 + ∫[0 to t] V(α(s)) ds.

A fixed point of F—meaning F(α) = α—corresponds exactly to a function α that solves the initial value problem.

To apply Banach’s fixed point theorem, the construction needs two ingredients: a complete metric space and a contraction mapping on it. The metric space is built from continuous functions α: R → R^N, but restricted to a small time interval [−ε, ε] because solutions may only exist locally. The functions in the space are continuous on that interval and satisfy the initial condition α(0) = x0. The distance between two functions α and β is defined using the supremum norm:

D(α, β) = sup_{t in [−ε, ε]} ||α(t) − β(t)||,

where ||·|| is the standard norm on R^N. With boundedness ensured by choosing ε small enough (so functions don’t “blow up”), this function space becomes complete.

The contraction estimate comes from comparing F(α) and F(β). The initial value x0 cancels when taking differences, leaving only an integral of V(α(s)) − V(β(s)). Using the triangle inequality to move the norm inside the integral, the integral is bounded by the “area of a rectangle”: the interval length |t| times the supremum of the integrand. Since |t| ≤ ε on the chosen interval, the bound simplifies to something proportional to ε. Finally, the local Lipschitz property of V supplies a constant L such that

||V(α(s)) − V(β(s))|| ≤ L ||α(s) − β(s)||.

Putting these steps together yields

D(F(α), F(β)) ≤ ε L · D(α, β).

Choosing ε small enough makes εL < 1, turning F into a contraction. Banach’s fixed point theorem then guarantees a fixed point in the space, which is the desired local solution to the initial value problem.

The theorem’s final statement: if V is locally Lipschitz on an open set U ⊂ R^N and x0 ∈ U, then there exists ε > 0 such that the initial value problem has a unique solution α on [−ε, ε]. The existence proof hinges on the contraction mapping built from the integral form of the ODE and the completeness of the function space under the supremum metric.

Cornell Notes

Picard–Lindelöf turns the ODE ẋ = V(x), x(0)=x0 into an integral fixed-point problem: F(α)(t)=x0+∫_0^t V(α(s))ds. Candidate solutions are continuous functions on a small interval [−ε,ε] with α(0)=x0, equipped with the supremum metric D(α,β)=sup_{t∈[−ε,ε]}||α(t)−β(t)||. This function space is complete (with boundedness ensured by taking ε small). Using the local Lipschitz condition on V, one gets the contraction estimate D(F(α),F(β)) ≤ εL·D(α,β). Picking ε so that εL<1 makes F a contraction, so Banach’s fixed point theorem yields a fixed point, i.e., an existence (and, combined with prior work, uniqueness) result for the initial value problem.

How does the differential equation become a fixed-point problem?

A function α solves ẋ = V(x) with α(0)=x0 exactly when it satisfies the integral equation α(t)=x0+∫_0^t V(α(s))ds. Defining F by F(α)(t)=x0+∫_0^t V(α(s))ds, any solution α is a fixed point because F(α)=α. Conversely, a fixed point of F satisfies the integral form and therefore corresponds to a solution of the initial value problem.

Why restrict attention to a small interval [−ε,ε]?

Solutions to ODEs may only exist locally, not for all t. The function space is therefore built from continuous functions on [−ε,ε] with α(0)=x0. The contraction estimate also depends on ε: the bound on D(F(α),F(β)) contains a factor ε, so shrinking ε is what makes the mapping contractive.

What metric makes the function space complete, and why does completeness matter?

The metric is the supremum norm metric: D(α,β)=sup_{t∈[−ε,ε]}||α(t)−β(t)||. With bounded functions on a closed interval, this space is complete, meaning every Cauchy sequence of functions converges to a function in the same space. Banach’s fixed point theorem requires completeness to ensure the iteration converges to a fixed point.

Where does the contraction inequality D(F(α),F(β)) ≤ εL·D(α,β) come from?

Start with F(α)(t)−F(β)(t)=∫_0^t (V(α(s))−V(β(s)))ds, so x0 cancels. Apply the triangle inequality to bound the norm of the integral by the integral of the norm. Then bound the integral by |t| times the supremum of the integrand; since |t|≤ε on [−ε,ε], this contributes the ε factor. Finally, local Lipschitz continuity gives ||V(α(s))−V(β(s))|| ≤ L||α(s)−β(s)||, replacing the integrand with L times the pointwise difference and yielding D(F(α),F(β)) ≤ εL·D(α,β).

How does local Lipschitz continuity of V enter the proof?

Local Lipschitz continuity provides a constant L (on the relevant region) such that differences in V are controlled by differences in inputs: ||V(u)−V(v)|| ≤ L||u−v||. This turns the integral estimate into a bound proportional to the metric D(α,β). Without Lipschitz control, the mapping F might not shrink distances and Banach’s theorem would not apply.

Review Questions

  1. What is the exact definition of the mapping F used to apply Banach’s fixed point theorem to the initial value problem?
  2. Which step introduces the factor ε in the contraction estimate, and how is it tied to the choice of the interval [−ε,ε]?
  3. How does the local Lipschitz constant L determine whether F is a contraction (in terms of the condition εL<1)?

Key Points

  1. 1

    Rewrite the ODE ẋ = V(x) with x(0)=x0 as the integral equation α(t)=x0+∫_0^t V(α(s))ds and define F(α)(t)=x0+∫_0^t V(α(s))ds.

  2. 2

    Choose a complete metric space of continuous functions on a small interval [−ε,ε] with the constraint α(0)=x0.

  3. 3

    Use the supremum metric D(α,β)=sup_{t∈[−ε,ε]}||α(t)−β(t)|| to measure distances between candidate solutions.

  4. 4

    Show F maps the function space into itself by checking continuity and the initial condition (x0 cancels in differences).

  5. 5

    Bound ||F(α)(t)−F(β)(t)|| by moving norms inside the integral (triangle inequality) and estimating the integral by |t| times a supremum.

  6. 6

    Apply the local Lipschitz condition ||V(u)−V(v)|| ≤ L||u−v|| to obtain D(F(α),F(β)) ≤ εL·D(α,β).

  7. 7

    Pick ε small enough so εL<1, making F a contraction and guaranteeing a fixed point, hence existence of a local solution.

Highlights

The existence proof hinges on converting the ODE into an integral fixed-point map F(α)(t)=x0+∫_0^t V(α(s))ds.
The supremum metric on continuous functions over [−ε,ε] provides the completeness needed for Banach’s theorem.
The contraction constant is essentially εL: shrinking the time window makes the mapping contractive.
Local Lipschitz continuity supplies the crucial inequality that turns differences in V into differences in the candidate functions.
Once F is a contraction, Banach’s fixed point theorem produces a fixed point, which is the solution to the initial value problem.

Mentioned

  • ODE