The galaxy-IGM connection in THESAN: observability and information content of the galaxy-Lyman- <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:mi>α</a:mi> </a:math> cross-correlation at <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"> <b:mi>z</b:mi> <b:mo>≥</b:mo> <b:mn>6</b:mn> </b:math>
Bibliographic record
Abstract
The galaxy–Lyman- α cross-correlation (GaLaCC) is a promising tool to study the interplay of galaxies and inter-galactic medium (IGM) in the first billion years of the Universe. Here we thoroughly characterise the impact of observational limitations on our ability to retrieve the intrinsic GaLaCC and provide new physical insights on its origin and connection to other IGM properties. This is extremely relevant to identify promising datasets, design future surveys and assess the limitations of current measurements. We find that sightline-to-sightline variations demand at least 25 independent sightlines to quantitatively recover the true signal. Once this condition is met, the intrinsic signal can be recovered even for a relatively low signal-to-noise ratio and spectral resolution. The galaxy selection method does not affect the inferred GaLaCC and lightcone effects are only relevant for redshift windows Δ z ≳ 0.4 . We discuss the implications of these findings for previous theoretical studies. We elucidate explicitly for the first time the physical origin of the GaLaCC and demonstrate that this signal is collectively sourced by the ensemble of galaxies residing in overdense regions rather than individual objects. We show that GaLaCC measured for opaque sightlines shows a larger peak at smaller scales with respect to transparent lines of sight. We connect this to the evolution of the mean free path of ionizing photons, showing that GaLaCC peak position has a very similar evolution but on smaller scales, as it probes only the core of ionised regions. Finally, we discuss which ongoing surveys can be used to measure the GaLaCC and provide an initial analysis of future developments, including using galaxies as background sources. Our results outline a bright future for the GaLaCC as a tool to unveil the galaxy-IGM interplay during the first billion years of the Universe.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".