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Picard theorem

math Maturity 11-13 Next article →

In the field of complex analysis, mathematicians study how functions behave across the complex plane. A function is a rule that takes an input and gives an output. Sometimes, these functions behave in very predictable ways, while others become extremely complex. Émile Picard was a mathematician who discovered two profound rules regarding the range of these functions. These rules are known as the Little Picard Theorem and the Great Picard Theorem. They describe how many values a function can actually reach.

Cplot of exp(1z)
Cplot of exp(1z)

The Little Picard Theorem focuses on a specific type of function called an entire function. An entire function is one that is analytic, or smooth, across the entire complex plane. If such a function is not a constant, it must cover a vast amount of territory. The theorem states that the range of a non-constant entire function is either the entire complex plane or the plane missing a single point. If the function misses a value, that specific value is called a lacunary value. This is a much stronger result than Liouville's theorem. Liouville's theorem only states that the image of a non-constant entire function must be unbounded. Picard's discovery shows that it must actually hit almost every single point.

To understand the mechanism of the Little Picard Theorem, we can look at how proofs are constructed. Émile Picard's original proof relied on the properties of the modular lambda function. This function is used to create a holomorphic universal covering of a twice-punctured plane using a unit disc. This process is part of the theory of elliptic functions. If a function were to omit two different values, mathematicians could use this covering map to show the function is actually constant. This follows from Liouville's theorem. Later, mathematicians developed other ways to prove this, including Schottky's theorem, which provides a quantitative version of the idea.

The Great Picard Theorem deals with an even more intense mathematical situation. It looks at what happens near an essential singularity. An essential singularity is a point where a function behaves in a very wild and unpredictable manner. The theorem states that if an analytic function has an essential singularity at a point, it will take on all possible complex values in any tiny neighborhood around that point. The only exception is that it might miss at most one value. Furthermore, it does not just hit these values once; it hits them infinitely often. This is a massive improvement over the Casorati–Weierstrass theorem. That older theorem only guaranteed that the function's range would be dense in the complex plane.

We can see a clear example of these rules using the function $e^z$. This is an entire, non-constant function. However, it never attains the value of 0. This shows why both theorems must allow for a single exception. In this case, 0 is the lacunary value for the function.

Cplot of exp(1z)
Cplot of exp(1z)

Another example involves the function $f(z) = 1/(1 - e^{1/z})$. This function is meromorphic on the complex plane with the origin deleted. It has an essential singularity at $z = 0$. This function attains the value of infinity infinitely often near the singularity. However, it does not attain the values 0 or 1.

There is also a more general version of the Great Picard Theorem that applies to meromorphic functions. A meromorphic function is one that can be thought of as working on a Riemann sphere, which includes the point at infinity. In this version, if a function has an essential singularity on a Riemann surface, it will attain all but at most two points of the Riemann sphere infinitely often. This broader rule actually allows the Little Picard Theorem to be seen as a special case. This is because any entire function that is not a polynomial will have an essential singularity at infinity.

These theorems connect deeply to the study of complex geometry and the structure of mathematical spaces. They help mathematicians understand the limits of how much a function can avoid certain values. The study of these functions continues through modern research and conjectures. For example, there are conjectures regarding how differentials glue together on a punctured unit disk. These ideas explore how local properties of functions can define the shape of a larger system. Picard's work remains a cornerstone for understanding the incredible density and reach of complex functions.

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