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Polynomial contractions of Cd\mathbb C^d and degree growth

This paper constructs a polynomial contraction automorphism of Cd\mathbb{C}^d (for d3d \ge 3) with unbounded degree growth, thereby providing an example of an algebraic automorphism that is holomorphically linearizable but not algebraically linearizable.

Original authors: Dmitrii Korshunov

Published 2026-05-29
📖 3 min read🧠 Deep dive

Original authors: Dmitrii Korshunov

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine you have a magical machine that takes a point in space and moves it to a new location. If you keep pressing the "run" button on this machine over and over again, the point eventually gets sucked into a single, tiny black hole at the center (the origin). In math terms, this is called a contraction.

Now, imagine this machine is built out of simple rules (polynomials). Usually, when you run these simple rules repeatedly, the complexity of the machine's instructions stays manageable. It's like a recipe that, no matter how many times you follow it, never gets more than a few pages long.

The Big Question
The author of this paper, Dmitrii Korshunov, asked a specific question: Is it possible to build a contraction machine in 3D (or higher) space where the instructions get infinitely more complicated every time you run it?

Think of it like a story.

  • In 2D (Flatland): If you have a story that always ends with the hero returning home, the plot can only get so wild before it loops back. The paper proves that in 2D, the "story length" (mathematical degree) is always limited. You can't make the instructions infinitely complex.
  • In 3D (and beyond): The author says, "Yes, we can!" He built a specific machine where, every time you run it, the instructions get slightly longer and more twisted. After a million runs, the instructions are a million pages long. The complexity grows without bound.

How the Machine Works
The author created a specific 3D machine with three dials: xx, yy, and zz.

  1. It shrinks everything slightly (using numbers like 0.1 or 0.2).
  2. But here's the trick: It mixes the dials in a sneaky way. The new position of xx depends on yy plus the product of xx and zz.
  3. Because xx and zz are multiplied together, every time the machine runs, it creates a new "layer" of complexity. It's like a snowball rolling down a hill that keeps picking up more snow, but in a way that the snowball never stops growing in size, even though it's rolling toward a stop.

The "Double Life" of the Machine
This is where the paper gets really interesting. The author shows that this machine has two different "personalities":

  1. The Smooth Personality (Holomorphic): If you look at the machine through a "smooth" mathematical lens (ignoring the fact that it's made of simple algebraic rules), it behaves exactly like a simple, straight-line machine. You can stretch and twist space smoothly to make it look like a simple linear map. This is guaranteed by a famous rule called the Poincaré–Dulac theorem.
  2. The Rigid Personality (Algebraic): However, if you try to fix the machine using only "rigid" algebraic rules (polynomials), you cannot make it look like a simple straight-line machine. The complexity keeps growing, so it can never be simplified into a basic form using these rules.

The Takeaway
The paper proves a surprising fact about the geometry of 3D space (and higher dimensions):

  • You can have a system that looks perfectly simple and linear if you are allowed to bend space smoothly.
  • But if you are forced to use only rigid, polynomial rules, that same system is actually incredibly complex and can never be simplified.

In short: In 3D, a machine can be "smoothly simple" but "algebraically messy." This answers a question posed by other mathematicians and shows that the rules of 2D space don't always apply when you add a third dimension.

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