← Latest papers
🔢 mathematics

Shadowing and Stability of Non-Invertible pp-adic Dynamics

This paper establishes sufficient conditions for strong shadowing and stability in non-invertible pp-adic dynamical systems on Zp\mathbb{Z}_p and Qp\mathbb{Q}_p, specifically for maps that are right-invertible through contractions or are left-invertible contractions, thereby extending stability theory to zero-dimensional non-invertible dynamics.

Original authors: D. A. Caprio, F. Lenarduzzi, A. Messaoudi, I. Tsokanos

Published 2026-04-30
📖 5 min read🧠 Deep dive

Original authors: D. A. Caprio, F. Lenarduzzi, A. Messaoudi, I. Tsokanos

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 are trying to navigate a very strange, fractal-like city called p-adic City. In this city, the rules of distance are different from our normal world. Here, two points are considered "close" not because they are physically near each other, but because they share a long history of similar digits in their mathematical makeup. This city is made of two main neighborhoods: Zp (the compact, closed-off integers) and Qp (the open, expansive numbers).

The authors of this paper are studying how things move and change within this city. Specifically, they are looking at dynamical systems—which is just a fancy way of saying, "If I apply a rule to a number, what happens next? And if I apply that rule again and again, where does it end up?"

The paper focuses on two main questions about these movements:

  1. Shadowing: If I give you a slightly wrong map (a "pseudo-orbit" where the steps are a little bit off), can you find a real path that stays very close to your wrong map?
  2. Stability: If I slightly tweak the rules of the city (change the map a tiny bit), does the overall behavior of the city stay the same, or does it completely fall apart?

The Core Problem: One-Way Streets

In many classic studies of these cities, the rules were "reversible" (like a two-way street). If you went from point A to B, you could always go back from B to A. But in this paper, the authors look at non-invertible dynamics. Think of these as one-way streets or folding maps. You can go from A to B, but you can't necessarily go back. This makes predicting the future (and checking stability) much harder.

The Main Discovery: The "Right Inverse" Key

The authors found a special key to unlock stability in these one-way systems. They call it having "right inverses through contractions."

Here is the analogy:
Imagine a machine that takes a complex, high-resolution photo and shrinks it down to a tiny thumbnail (this is the "contraction"). If you have a machine that can take that tiny thumbnail and perfectly reconstruct the original photo, that's a "right inverse."

The paper proves that if your "shrinking machine" (the map ff) has a set of "reconstruction machines" (the contractions RiR_i) that:

  1. Can perfectly undo the shrinking (mathematically, fRi=identityf \circ R_i = \text{identity}).
  2. Are "shrinking" themselves (they pull points closer together).
  3. Cover the entire city without overlapping (they partition the space).

Then, the system is stable. It has the Shadowing Property (you can always find a real path close to a fake one) and Structural Stability (if you slightly change the rules, the system behaves almost exactly the same way).

Real-World Examples in the Paper

The authors show that this theory applies to several known "famous" maps in p-adic math:

  • The Shift Map: Imagine a number written as a long string of digits. The shift map chops off the first digit and slides everything else to the left. The paper confirms this is stable because you can "un-shift" it by adding a digit back in (a contraction).
  • Affine Contractions: These are simple maps like $R(x) = vx + w$ where vv is small. The paper proves these are stable if they are "bi-Lipschitz" (they stretch and shrink distances in a very controlled, predictable way).

The Warning: Not All One-Way Streets Are Safe

The paper also provides a crucial warning. Just because a map has a "right inverse" (a way to go back), it doesn't guarantee stability.

  • The Counter-Example: The authors construct a specific map that has a contraction as a right inverse but fails to be stable. It's like having a key that fits the lock, but the door is jammed.
  • The Condition: For the stability to hold, the "reconstruction machines" (the contractions) must be open maps (they must cover the space nicely) and bi-Lipschitz (they must not squish distances too wildly). If these conditions aren't met, the system can become chaotic and unpredictable.

Summary of the "Big Results"

  1. The Good News: If a p-adic system can be "un-done" by a set of shrinking, non-overlapping maps, it is robust. It can handle small errors in measurement (shadowing) and small changes in the rules (stability).
  2. The Bad News: If the "undoing" maps aren't perfectly structured (specifically, if they aren't bi-Lipschitz or don't cover the space openly), the system can break. The paper gives a concrete example of a system that looks stable but isn't.
  3. The "Nowhere Locally Constant" Rule: The paper also extends a previous result, showing that if a system is stable and never gets "stuck" in a constant state (it's always moving/changing), it automatically has the shadowing property.

In a Nutshell

This paper is a guidebook for navigating the complex, one-way streets of p-adic mathematics. It tells us exactly what conditions are needed to ensure that even if we make small mistakes or slightly change the rules, the system's behavior remains predictable and stable. It confirms that for a specific, well-structured class of "folding" maps, the chaos is under control, but warns us that without the right structure, even simple-looking systems can become unstable.

Drowning in papers in your field?

Get daily digests of the most novel papers matching your research keywords — with technical summaries, in your language.

Try Digest →