Constraining cosmology with the Gaia-unWISE Quasar Catalog and CMB lensing: structure growth
Bibliographic record
Abstract
Abstract We study the angular clustering of Quaia, a Gaia - and unWISE -based catalog of over a million quasars with an exceptionally well-defined selection function. With it, we derive cosmology constraints from the amplitude and growth of structure across cosmic time. We divide the sample into two redshift bins, centered at z = 1.0 and z = 2.1, and measure both overdensity auto-correlations and cross-correlations with maps of the Cosmic Microwave Background convergence measured by Planck . From these data, and including a prior from measurements of the baryon acoustic oscillations scale, we place constraints on the amplitude of the matter power spectrum σ 8 = 0.766 ± 0.034, and on the matter density parameter Ω m = 0.343 +0.017 -0.019 . These measurements are in reasonable agreement with Planck at the ∼ 1.4 σ level, and are found to be robust with respect to observational and theoretical uncertainties. We find that our slightly lower value of σ 8 is driven by the higher-redshift sample, which favours a low amplitude of matter fluctuations. We present plausible arguments showing that this could be driven by contamination of the CMB lensing map by high-redshift extragalactic foregrounds, which should also affect other cross-correlations with tracers of large-scale structure beyond z ∼ 1.5. Our constraints are competitive with those from state-of-the-art 3×2-point analyses, but arise from a range of scales and redshifts that is highly complementary to those covered by cosmic shear data and most galaxy clustering samples. This, coupled with the unprecedented combination of volume and redshift precision achieved by Quaia, allows us to break the usual degeneracy between Ω m and σ 8 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".