Character and detectability of the dark ages and the epoch of reionization: the view from the simulations
Bibliographic record
Abstract
Direct detection of the Dark Ages and the Epoch of Reionization (EOR) is among the main scientific objectives of all current and future low-frequency radio facilities.In this paper we summarize and discuss recent results, based on state-of-the-art numerical simulations, regarding the fundamental EOR properties and its observability with current and future radio arrays, like the Giant Metrewave Radio Telescope (GMRT), the Low Frequency Array (LOFAR), the 21-CM Array (21CMA), the Murchison Widefield Array (MWA) and the Square Kilometre Array (SKA).Results show that the optimal observational frequencies for statistical detection are 140-160 MHz.The signals are strongly non-Gaussian at late times.The correlation widths between 21-cm maps at neighbouring frequencies are short, of order 300-800 kHz, which should help with the cleaning of the strong foregrounds.Direct comparison of the resolutions and expected sensitivities of GMRT and MWA indicate that their optimal sensitivity ranges are similar, at scales k ∼ 0.2 -0.4 h -1 Mpc, however, all else being equal the former should require shorter integration times due to its significantly larger collecting area.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".