The <scp>thesan</scp> project: public data release of radiation-hydrodynamic simulations matching reionization-era <i>JWST</i> observations
Bibliographic record
Abstract
ABSTRACT Cosmological simulations serve as invaluable tools for understanding the Universe. However, the technical complexity and substantial computational resources required to generate such simulations often limit their accessibility within the broader research community. Notable exceptions exist, but most are not suited for simultaneously studying the physics of galaxy formation and cosmic reionization during the first billion years of cosmic history. This is especially relevant now that a fleet of advanced observatories (e.g. James Webb Space Telescope, Nancy Grace Roman Space Telescope, SPHEREx, ELT, SKA) will soon provide an holistic picture of this defining epoch. To bridge this gap, we publicly release all simulation outputs and post-processing products generated within the thesan simulation project at www.thesan-project.com. This project focuses on the z ≥ 5.5 Universe, combining a radiation-hydrodynamics solver (arepo-rt), a well-tested galaxy formation model (IllustrisTNG) and cosmic dust physics to provide a comprehensive view of the Epoch of Reionization. The thesan suite includes 16 distinct simulations, each varying in volume, resolution, and underlying physical models. This paper outlines the unique features of these new simulations, the production and detailed format of the wide range of derived data products, and the process for data retrieval. Finally, as a case study, we compare our simulation data with a number of recent observations from the James Webb Space Telescope, affirming the accuracy and applicability of thesan. The examples also serve as prototypes for how to utilize the released data set to perform comparisons between predictions and observations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.020 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".