ASTRID traces 13.5 billion years of black hole and galaxy evolution
In dark skies at night, distant starlight twinkles and speaks to vast cosmic histories almost as old as time itself. New data from instruments such as NASA's James Webb Space Telescope are helping astrophysicists probe deep cosmic mysteries, including the evolution of black holes and galaxies.
This article examines the extensive research conducted using the ASTRID simulation, tracing black hole and galaxy evolution over 13.5 billion years. Led by Carnegie Mellon University, the project involved researchers from multiple institutions and utilized supercomputers, notably Frontera at the Texas Advanced Computing Center (TACC), to perform the calculations.
The simulations began at z = 99, representing the early universe shortly after the Big Bang, and extended to the present day (z = 0). The researchers modeled 166 billion particles within a volume of space 815 million light-years across, capturing the growth of black holes and the formation of galaxies. The data generated by the simulations, with each snapshot totaling 30 terabytes, were stored in TACC's Ranch archive system.
The NSF provided the necessary resources for the simulations, enabling the team to achieve high resolution and full physical accuracy across a mass range of seven orders of magnitude. Looking forward, the ASTRID team plans to utilize the upcoming Horizon supercomputer, which is expected to enter production in 2026, to further refine their models and explore new questions posed by observations from the James Webb Space Telescope (JWST).
These observations suggest that massive black holes were more common in the early universe than previously thought, leading to new insights into their formation and growth. By analyzing ASTRID simulations, researchers aim to improve predictions of gravitational wave sources and contribute to the development of future gravitational-wave detectors like LISA and the Pulsar Timing Array.
Written by urgent.news from Phys.org's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.