The Inverse Function Theorem
If the linear approximation to $f$ at $a$ is invertible, then $f$ itself is invertible near $a$. That sentence is the theorem, and it is the first place in the course where a statement about the derivative — an infinitesimal object — buys you a statement about $f$ on an actual neighbourhood.
- State the theorem precisely, including every word of "local".
- Prove the contraction mapping principle and use it to build the inverse.
- Explain why $C^1$ is needed and why $\det Jf(a)\ne0$ alone is not enough for a global inverse.
- Differentiate an inverse you cannot write down.
Solving $f(x)=y$ for $x$ is impossible in closed form for almost every $f$. The theorem says you do not need a formula: an invertible derivative is already a guarantee that a solution exists, is unique nearby, and depends smoothly on $y$.
Newton's method is the proof turned into an algorithm, and its quadratic convergence comes from the same estimate. Coordinate changes in mechanics, the change of variables formula in Unit 10, and the chart maps of Unit 13 all invoke it.
Banach's fixed point theorem (1922) is what made the modern proof short, and the same argument runs unchanged in Banach spaces, giving the infinite-dimensional version used for differential equations. Whether a global version can hold under a determinant condition alone is the still-open Jacobian conjecture in the polynomial setting.
The contraction mapping principle
Let $X$ be a nonempty closed subset of $\mathbb{R}^n$ and $T:X\to X$ satisfy $\|T(x)-T(y)\|\le c\|x-y\|$ for a constant $c<1$. Then $T$ has exactly one fixed point in $X$.
Completeness is doing the real work. This is why the theorem lives in analysis and not in algebra.
Statement and proof
Let $f:A\to\mathbb{R}^n$ be $C^1$ on an open $A\subseteq\mathbb{R}^n$, and suppose $Df(a)$ is invertible. Then there are open sets $U$ containing $a$ and $V$ containing $f(a)$ such that $f:U\to V$ is a bijection, the inverse $f^{-1}:V\to U$ is $C^1$, and
Note the domain and codomain have the same dimension. Nothing here applies to $f:\mathbb{R}^2\to\mathbb{R}^3$.
$g(r,\theta)=(r\cos\theta,r\sin\theta)$ has $\det Jg=r$, nonzero whenever $r>0$. So $g$ is locally invertible away from the origin. It is not globally injective — $\theta$ and $\theta+2\pi$ collide — which is precisely the gap between local and global that the theorem does not close.
$f(x,y)=(e^x\cos y,\,e^x\sin y)$ has $\det Jf=e^{2x}>0$ everywhere, so it is locally invertible at every point of $\mathbb{R}^2$, yet it is $2\pi$-periodic in $y$ and therefore infinitely-to-one. This is the complex exponential, and it is the standard demonstration that "invertible derivative everywhere" and "invertible" are different claims.
What each hypothesis is buying
$f(x)=x+2x^2\sin(1/x)$ with $f(0)=0$ has $f'(0)=1\ne0$, but $f'$ is discontinuous at $0$ and takes negative values in every neighbourhood. So $f$ is not monotone near $0$ and has no local inverse there.
Differentiability at the single point $a$ is not enough. The proof used control of $Df$ on a whole ball, and this example shows that use was not laziness.
If $f$ is $C^1$ on $A$ and $Df(x)$ is invertible for every $x\in A$, then $f(A)$ is open, and more generally $f$ maps open subsets of $A$ to open sets. Apply the theorem at each point: every image point has an open $V$ around it inside the image.
• Concluding $f$ is injective on all of $A$ from an everywhere-nonzero
Jacobian determinant. The complex exponential above refutes it.
• Using the theorem when domain and codomain have different dimensions.
That case is the rank theorem, not this one.
• Checking only that $Df(a)\ne0$. The condition is that $Df(a)$ is
invertible, that is $\det Jf(a)\ne0$.
• Assuming differentiability at $a$ suffices. The hypothesis is $C^1$ on
a neighbourhood.
• Forgetting the inverse inherits smoothness: if $f$ is $C^k$ so is
$f^{-1}$, which follows by induction on the formula for
$D(f^{-1})$.
Practice
Original problems written for this guide in the style of Spivak and Munkres exercises. Write a full solution before opening the answer.
For $f(x,y)=(x^2-y^2,\,2xy)$, at which points does the theorem apply?
Solution
With the same $f$, compute $D(f^{-1})$ at $f(1,1)=(0,2)$.
Solution
Show $T(x)=\tfrac12\cos x$ has a unique fixed point on $\mathbb{R}$.
Solution
Explain why $x_{k+1}=x_k-Df(x_k)^{-1}f(x_k)$ is the proof made computational.
Solution
Does $f(x)=x^3$ on $\mathbb{R}$ contradict the theorem at $0$?
Solution
If $f$ is $C^\infty$ with invertible derivative, is $f^{-1}$ smooth?
Solution
Compute $\det Jg$ for $g(\rho,\varphi,\theta)=(\rho\sin\varphi\cos\theta,\rho\sin\varphi\sin\theta,\rho\cos\varphi)$ and say where $g$ is a local diffeomorphism.
Solution
If $f$ is $C^1$ and injective on a compact $K$ with invertible derivative throughout, must $f^{-1}$ be continuous on $f(K)$?
Solution
Expanded topic checklist
Course coverage. This unit is part of the complete MAT257Y1 topic map. It should cover the following items before you move on:
- Contraction mapping. Statement, proof, and the role of completeness.
- Inverse function theorem. Full statement, the four-step proof, and the formula for the inverse's derivative.
- Local versus global. The complex exponential, and why the theorem cannot be upgraded.
- Hypothesis audit. Why $C^1$ on a neighbourhood, and why equal dimensions.
Spivak proves the theorem with a compactness argument rather than a contraction; Munkres uses the fixed point route given here. Both are worth reading, and the syllabus decides which one is examinable.
Completeness gives the contraction principle, which gives the inverse function theorem, which gives the implicit function theorem in Unit 7, which gives the manifold charts in Unit 13. This is the longest single chain of dependence in the course.
Deep practice extensions
Use these after the main practice set. They are designed to force definition-level reasoning, theorem selection, and mixed application rather than routine calculation only.
State the theorem in one sentence.
Guide
Which map is contracted in the proof, and why does its fixed point solve the equation?
Guide
Give the standard map with invertible derivative everywhere that is not injective.
Guide
What replaces the theorem when the derivative has constant rank but is not square?