Scientists Run the Largest Universe Simulation Yet, Tracking Dark and Ordinary Matter
An international team of astronomers has conducted the largest computer simulation to date of how the Universe evolves, accounting for both dark matter and regular matter. The effort appears in the scientific journal MNRAS, a leading publication in the field of astronomy. The aim was to reproduce cosmic history by following the motion and interactions of matter under the laws of physics, providing a synthetic view that can be compared with real sky observations. This work builds on decades of modeling and observational data, and it marks a milestone in computational cosmology. The study demonstrates how different components of the cosmos influence one another across cosmic time, helping researchers tease apart the roles of gravity, gas dynamics, and particle physics in shaping the large-scale structure of the Universe.
The simulation, named FLAMINGO, tracks the evolution of space components with a level of detail that pushes the limits of current computing. It uses 300 billion resolution elements, each representing a mass distribution comparable to that of a small galaxy, to model a cubic region ten billion light-years on each side. In this framework, the distribution of matter is not treated as a smooth field but as a collection of discrete elements that interact under gravity and other forces. By resolving such a vast range of scales, FLAMINGO aims to bridge the gap between how galaxies form and how the cosmic web emerges on the largest scales. The sheer scale of this effort required enormous computing power and careful numerical techniques to maintain accuracy over billions of years of simulated time. Researchers describe the project as a comprehensive census of matter moving through an expanding universe, a synthetic laboratory in which theories can be tested against observations from telescopes and surveys. (Citable context: Prieto et al., 2024).
Modeling ordinary baryonic matter along with dark matter adds substantial complexity. Although baryonic matter constitutes only about 16 percent of the current cosmic inventory, it interacts not only via gravity but also through gas pressure, radiative cooling, and feedback from stars and black holes. This combination leads to phenomena such as winds driven by supernovae and active galactic nuclei that can push gas out of galaxies. Such winds influence the distribution of matter on large scales, altering how structures grow and how galaxies acquire their gas supply. Getting these processes right is essential for simulations to match what astronomers see when they observe the light from distant galaxies and the distribution of matter inferred from gravitational effects. The team emphasizes that capturing the interplay between gravity and baryonic physics is key to making realistic predictions about the universe’s evolution. (Observational anchor: van Daalen et al., 2019).
Beyond gravity and gas dynamics, the simulation must also account for neutrinos, the lightest known subatomic particles that still carry mass. Neutrinos travel at nearly the speed of light and can subtly influence how matter clumps together. Their movement has not been fully mapped in prior models, so including their behavior adds another layer of refinement to predictions. The researchers note that neutrinos help damp small-scale clustering while leaving larger structures relatively unaffected, a nuance that can shift the interpretation of forthcoming sky surveys. Integrating neutrino physics with baryonic and dark matter interactions is a frontier in cosmology and one of the distinguishing features of the FLAMINGO approach. (Neutrino effects: Lesgourgues & Pastor, 2006).
Initial results indicate that both neutrinos and ordinary matter are necessary for accurate predictions of observed cosmic patterns. Yet, even with these advancements, some tensions remain between different cosmological observations. The team views this not as a failure but as a prompt to refine models further, to reassess assumptions about gas cooling, feedback efficiencies, and the detailed behavior of dark matter on various scales. The ongoing effort highlights that a single, definitive picture of the universe remains elusive, and multiple lines of evidence must be reconciled to build confidence in our cosmological model. The researchers also stress the importance of cross-validation with independent data sets, including galaxy surveys, weak-lensing measurements, and the cosmic microwave background. (Cross-check: Planck Collaboration, 2018).
Looking ahead, advances in machine learning are expected to accelerate the interpretation of complex cosmic simulations. Data-driven methods can help identify patterns, optimize parameter choices, and predict a wide range of cosmic events with increasing speed and accuracy. The fusion of high-performance computing and artificial intelligence holds the promise of turning elaborate simulations like FLAMINGO into practical tools for exploring the history of the universe, validating theoretical frameworks, and guiding future observational campaigns. As computational power grows and algorithms improve, researchers anticipate more precise reconstructions of how galaxies form, how matter redistributes itself, and how the cosmos evolves toward its present structure. (Forecasting: Heitmann et al., 2020).
In related lines of inquiry, prior modeling suggested that turbulent flows can hinder ambitious urban mobility projects like air taxis in densely built environments. While not directly connected to cosmology, this parallel underscores how complex fluid dynamics can influence outcomes in both celestial and terrestrial settings. In both cases, the interplay of turbulence, energy input, and environmental conditions shapes the system’s evolution in ways that challenge straightforward prediction. The broader takeaway is that complex fluids require careful treatment and a nuanced understanding of how small-scale processes propagate to large-scale consequences. (Engineering note: Stryk & Juchem, 2021).