Science1 distinct publisher2 min readPublished
The Carnegie Mellon team has released a 13.5-billion-year hydrodynamic run that ends at the present day, which lets JWST's crowd of early massive black holes be tested against a model that also has to produce a recognizable today.
The Scientist · Science desk

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Divide the box by the particle count and the design choice becomes legible. Spreading 166 billion particles across a volume 815 million light-years wide [5] leaves a mean spacing of roughly 148,000 light-years between them [13]. That average describes a mostly empty universe, and inside a collapsed halo the same particles sit far closer together, which is the sense in which Tiziana Di Matteo, the run's principal investigator at Carnegie Mellon, claims coverage over seven orders of magnitude in mass with the full physics [8][14]. The average is still the number worth holding onto, because it is what the volume cost.
Volume is also what the JWST comparison needs. The observations prompting this work suggest massive black holes were far more common early on than existing theory anticipated [11], and an abundance claim is a count per unit volume. Testing one requires a box large enough to hold a fair sample of rare objects while still resolving the gas inside them, which is a harder requirement than either alone. The team calls ASTRID the largest cosmological hydrodynamic simulation [4], and for this particular question the size is a functional requirement.
The endpoint does separate work. Redshift is a clock read backwards, with high z meaning greater distance and earlier times [15], and ASTRID began at z = 99 and ran 13.5 billion years to z = 0 [2]. A simulation that stops while the universe is still young can be adjusted until its early black holes resemble the observed ones, without ever answering for the galaxies and black holes we can count nearby. One that finishes has to land on both ends of the record. Zhou and colleagues published the completed run in The Astrophysical Journal in March 2026 [3].
What remains open is which channel actually produced those early black holes. Black hole feedback in a run this size is a prescription written by hand, and Zhou says the team is refining its gravitational and black hole feedback models as it prepares for new hardware [10]. A match between ASTRID's high-redshift output and JWST's counts would therefore be consistency between an observation and a model with adjustable interiors; the question of how those objects formed and grew so quickly stays open [11]. Di Matteo's own framing stops at making predictions and probing the puzzles [12]. What is new here is a full-history run at this volume that other groups can hold their own models against [1].
Ranked by verification strength, evidence, and original report placement.
Yihao Zhou, a PhD student in Carnegie Mellon University's Department of Physics, said the most important information about the study is that the team evolved the ASTRID simulation to z = 0 and that these data are available.
Zhou's team started their cosmological simulations at z = 99, covering the cosmic dawn, and ASTRID traced 13.5 billion years of galactic structure and black hole evolution to z = 0, the present day.
Zhou and colleagues published their study in The Astrophysical Journal in March 2026.
Di Matteo used the Frontera supercomputer at the Texas Advanced Computing Center, which gave the ASTRID team the computational power to model 166 billion particles across a volume of space 815 million light-years across.
The researchers solved gravity and hydrodynamics for each time step, which required building gravity trees to compute long- and short-range gravitational forces across billions of particles; Zhou said only large compute clusters like Frontera can do this.
Each ASTRID simulation snapshot totaled 30 terabytes, and Zhou said TACC's Ranch archive system saved the ASTRID data.
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phys.org
1 article · August 27, 2026
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Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
Peer-reviewed run behind a single institutional account
The cluster rests on one institution-sourced article, but it cites a peer-reviewed Astrophysical Journal paper and gives checkable, internally consistent numbers (z = 99 to z = 0, 13.5 billion years, 166 billion particles, 815 million light-year box, 30 TB snapshots) that even support a derivable mean particle spacing. Nothing is independently corroborated, and the superlative and capability claims are unverified.
Run delivered and data said to be available; no external uptake shown
There is real, completed usage: a full campaign on Frontera with archived multi-terabyte snapshots and a stated data release. But the cluster shows no third party using the dataset, no downstream papers, no access endpoint, and the Horizon follow-on is only planned, so adoption beyond the originating team is unevidenced.
Modestly overstated: superlatives and puzzle-solving framing outrun shown results
The measurable core (run to z = 0, particle count, box size, snapshot size, CPU-only code) is delivered plainly. Overstatement sits in the unbenchmarked 'largest / biggest volume / highest resolution with full physics' framing and in the claim that ASTRID can resolve JWST's early massive black hole puzzles, since the cluster shows no ASTRID-versus-JWST comparison, plus forward references to Horizon in 2026 and LISA in 2035.
Facility- and team-promotional framing
The account is built from quotes by the ASTRID PhD student and principal investigator and repeatedly credits NSF-funded TACC systems (Frontera, Ranch) while promoting the forthcoming Horizon machine, a pattern consistent with supercomputing-center and university communications. Every superlative and capability statement originates with parties who benefit from continued allocations and facility visibility, and no counter-source is present.
Single publisher, single source, no corroboration
Confidence is limited by structure rather than by internal contradiction: one publisher, one article, no independent reporting, and no primary-document links for the dataset or the Horizon schedule. The descriptive facts are specific and mutually consistent, which supports moderate confidence in the run's parameters while leaving superlatives and forward-looking items weakly held.