First Identification of a CMB Lensing Signal Produced by 1.5 Million Galaxies at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>z</mml:mi><mml:mo>∼</mml:mo><mml:mn>4</mml:mn></mml:mrow></mml:math>: Constraints on Matter Density Fluctuations at High Redshift
Bibliographic record
Abstract
We report the first detection of the dark matter distribution around Lyman break galaxies (LBGs) at high redshift through the cosmic microwave background (CMB) lensing measurements with the public Planck PR3 κ map. The LBG sample consists of 1 473 106 objects with the median redshift of z∼4 that are identified in a total area of 305 deg^{2} observed by the Hyper Suprime-Cam Strategic Survey Program survey. After careful investigations of systematic uncertainties, such as contamination from foreground galaxies and cosmic infrared background, we obtain the significant detection of the CMB lensing signal at 5.1σ that is dominated by 2-halo term signals of the LBGs. Fitting a simple model consisting of the Navarro-Frenk-White profile and the linear-bias model, we obtain the typical halo mass of M_{h}=2.9_{-2.5}^{+9.5}×10^{11} h^{-1} M_{⊙}. Combining the CMB lensing and galaxy-galaxy clustering signals on the large scales, we demonstrate the first cosmological analysis at z∼4 that constrains (Ω_{m0},σ_{8}). We find that our constraint on σ_{8} is roughly consistent with the Planck cosmology, while this σ_{8} constraint is lower than the Planck cosmology over the 1σ level. This study opens up a new window for constraining cosmological parameters at high redshift by the combination of CMB and high-z galaxies, as well as studying the interplay between galaxy evolution and large-scale structure at such high redshift, by upcoming CMB and optical and near-infrared imaging surveys.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".