Cosmology and neutrino mass with the minimum spanning tree
Bibliographic record
Abstract
ABSTRACT The information content of the minimum spanning tree (MST), used to capture higher order statistics and information from the cosmic web, is compared to that of the power spectrum for a νΛCDM model. The measurements are made in redshift space using haloes from the Quijote simulation of mass $\ge 3.2\times 10^{13}\, h^{-1}\, {\rm M}_{\odot }$ in a box of length $L_{\rm box}=1\, h^{-1}\, {\rm Gpc}$. The power spectrum multipoles (monopole and quadrupole) are computed for Fourier modes in the range $0.006\, h{\rm Mpc}^{-1} \lt k \lt 0.5\, h{\rm Mpc}^{-1}$. For comparison the MST is measured with a minimum length-scale of $l_{\min }\simeq 13\, h^{-1}\, {\rm Mpc}$. Combining the MST and power spectrum allows for many of the individual degeneracies to be broken; on its own the MST provides tighter constraints on the sum of neutrino masses Mν and cosmological parameters h, ns, and Ωb but the power spectrum alone provides tighter constraints on Ωm and σ8. Combined we find constraints that are a factor of two (or greater) on all parameters with respect to the power spectrum (for Mν there is a factor of four improvement). These improvements appear to be driven by the MST’s sensitivity to small scale clustering, where the effect of neutrino free-streaming becomes relevant, and high-order statistical information in the cosmic web. The MST is shown to be a powerful tool for cosmology and neutrino mass studies, and therefore could play a pivotal role in ongoing and future galaxy redshift surveys (such as DES, DESI, Euclid, and Rubin-LSST).
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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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".