Thanks to AI, astronomers model our galaxy’s 100 billion stars individually

Milky Way simulation with AI

Scientists have used artificial intelligence to build a detailed simulation of the Milky Way, modeling roughly 100 billion stars one by one within a virtual galaxy. The work overcomes long‑standing computational limits that previously forced researchers to simplify or average stellar properties across large regions of space.

Why simulating each star is hard

Traditional galaxy simulations must balance resolution with computing power, which usually leads to combining many stars into coarse “particles” instead of tracking each star individually. This approach hides fine‑grained structures, such as local star clusters, stellar streams, and the precise distribution of stellar ages and compositions.

AI‑based methods help compress and predict complex stellar behavior, allowing models to keep track of far more individual objects without linearly increasing the cost of computation. As a result, researchers can follow the evolution of single stars while still capturing the dynamics of the whole galaxy.

Role of artificial intelligence

In this project, AI algorithms learn patterns from high‑quality astrophysical simulations and observational data, then generate or refine the state of individual stars throughout the Milky Way model. Neural networks or similar architectures replace parts of the expensive physics calculations with fast, data‑driven approximations.

This hybrid strategy preserves key physical laws while accelerating tasks such as estimating star formation histories, stellar orbits, and interactions with gas and dark matter. The AI effectively acts as a surrogate model, filling in detailed stellar properties in regions where full numerical calculations would be too time‑consuming.

Scientific insights from the model

A star‑by‑star digital Milky Way lets astronomers test ideas about how spiral arms, the central bar, and the stellar halo form and evolve over billions of years. It also improves predictions of where to find rare or short‑lived objects, such as massive stars on the verge of explosion or stars that have migrated far from their birthplaces.

Comparing the simulated galaxy with high‑precision surveys, for example from Gaia and other observatories, helps identify where current theories of star formation, feedback, and galactic dynamics need revision. The model becomes a laboratory for exploring how small‑scale stellar processes shape the large‑scale structure of the Milky Way.

Future applications

Such detailed simulations can guide observing strategies for upcoming telescopes by highlighting regions of special interest in the galactic disk and halo. They may also support searches for exoplanets and habitable environments by providing better maps of stellar populations similar to the Sun.

Beyond the Milky Way, the same AI‑driven techniques could be adapted to other galaxies, enabling comparative studies of galactic evolution across different environments and cosmic epochs.

Author’s summary: Using AI, researchers built a high‑resolution digital Milky Way that tracks about 100 billion stars individually, overcoming past computing limits and opening new tests of galactic evolution theories.

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Techno-Science.net Techno-Science.net — 2025-11-28

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