Information Dynamics: Gravity as a Projection of the Information Field -- Inversion and Test via the Orbital Clustering of Planet Nine

We propose an Information Dynamics framework. Here “dynamics” means the field is not static; it is driven by a competition between self‑organization (creating order) and dissipation (breaking order). The balance of these two forces is measured by a single number, the information purity \(p_{\mathrm{ID}}\) . To understand what the information field is, consider how a computer works. A programmer writes a high‑level program (say Python). That code is translated into binary machine code that the CPU executes. The machine code is real and determines what the computer does. Yet if you look only at the binary stream, you never directly see the programmer’s ideas like “variables” or “loops”. The high‑level logic is a different layer of description, even though it perfectly determines the lower‑layer behaviour. In the same way, the information field is not a new substance. It is the higher‑level pattern – the “source code” – of the underlying quantum fields and spacetime geometry. The physical laws we observe (including Newtonian gravity) are like the machine code: they are real, they work, but they are projections of this deeper information field. The information purity \(p_{\mathrm{ID}}\) measures how orderly that source code is. But what makes the information field evolve? In the computer example, the source code is usually static unless a programmer edits it. Now imagine an AI that can write and improve its own code. It evaluates its performance: if the output is messy, it detects the “error” and rewrites itself to do better next time. That error signal is the driving force. In our framework, the information field behaves like such a self‑improving AI. It is driven by an “information gradient” – a pressure to reduce chaos and increase order. This drive constantly adjusts the underlying source code, projecting a more structured reality. Gravity, in this view, is one of the patterns that emerges as the field “learns” to arrange matter in the most stable way possible. Under macroscopic, low‑velocity, weak‑field conditions we derive Newtonian gravity as an effective phenomenon. The framework predicts that Planet Nine is not a massive body but an information eigenmode – a stable pattern in the field – explaining why it has never been directly seen. The same dynamics that organises the orbits of distant asteroids also shapes the laws of gravity. This work introduces two major inventions. First, the Information Dynamics framework itself. It shows that gravity is not a fundamental force but a macroscopic projection of an underlying information field. By treating physical reality as emerging from a complex scalar information field governed by a generalized complex Ginzburg‑Landau equation, we obtain Newtonian gravity as the low‑energy effective description. This unifies the concept of information purity with classical gravity in a single coherent picture and offers a new perspective on the origin of gravitational phenomena. Second, the quantitative inversion and test using the orbital clustering of extreme trans‑Neptunian objects (ETNOs). We analyze the argument of perihelion (\(\omega\)) distribution of 43 ETNOs from the MPCORB database (March 2026 release). Using a mixture of two von Mises distributions separated by \(180^\circ\), we invert the concentration parameter \(\kappa = 1.22\) (68% CI \([0.80, 1.86]\)). This yields an information purity \(p_{\mathrm{ID}} = \kappa/(1+\kappa) = 0.55\) (68% CI \([0.44, 0.65]\)). The single parameter \(p_{\mathrm{ID}}\) self‑consistently predicts the observed clustering fraction of \(83.7\%\) (36 out of 43 objects) within two opposite \(60^\circ\) windows. The framework therefore explains why Planet Nine has never been directly imaged: it is not a conventional massive planet but a stable information eigenmode of the field. It also accounts for the exact clustering fraction without extra assumptions and for the long‑term stability of the alignment over billions of years. Together these two inventions provide a testable alternative to the conventional Planet Nine hypothesis. They make concrete predictions for the upcoming LSST survey and open a new pathway to understanding gravity as an emergent information phenomenon. The results are fully reproducible from the supplied data and analysis code. As independent researchers, we welcome collaboration and funding opportunities. We are deeply committed to the highest standards of Scientific Responsibility. Keywords: Information Dynamics; gravity emergence; Planet Nine; ETNO clustering; von Mises mixture; information purity; eigenmode The Value of Information Dynamics: A New Perspective, Not Just New Predictions Information Dynamics is not intended to replace or overturn the current physical laws. Its role is analogous to that of a high‑level programming language—the binary code compiled from a high‑level language may be functionally identical to hand‑written assembly, yet the value of the high‑level language lies in simpler abstractions, greater unifying power, and the ability to solve complex problems. Similarly, starting solely from binary code, there are several ways to prove the existence of a high‑level programming language (e.g., bootstrapping, cross‑platform consistency, solving problems impractical in binary, information compression, extensibility, etc.). However, each of these approaches requires substantial time and broad collaboration. This paper serves only as the beginning of such an ambitious endeavor, presenting the core ideas and initial constructions. This paper takes only the first step—demonstrating the basic syntax and core ideas of Information Dynamics as a “high‑level language.” We sincerely invite colleagues in the academic community to collaborate and together complete this grand bootstrapping project. Upload note:This is the final preprint version updated on April 1, 2026. All figures, data, and code are included in the GitHub repository: https://github.com/hkaiopen/InformationDynamics_PlanetNine.