Papers › A model-independent reconstruction of the matter power spectrum
A model-independent reconstruction of the matter power spectrum
Gen Ye, Jun-Qian Jiang, Alessandra Silvestri
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
We propose a new model-independent reconstruction method for the matter power spectrum based on its time dependence and a combination of observations from different redshifts. The method builds on a perturbative expansion in terms of the linear growth function, with each coefficient in the expansion being a free function of scale, to be reconstructed from the data. When using the linear growth function of a specific cosmological model, e.g. ΛCDM, the reconstruction can serve as a consistency check for non-linear modeling in that given model, as well as a new method for detecting departures from the assumed model in the data. As an application, we show how using DES Y3 3x2pt and Planck PR4 CMB lensing data, assuming a ΛCDM linear growth and first order expansion, the reconstructed matter power spectrum Pₘ(k) is compatible with that computed from ΛCDM and halo model. In particular, we show that the method reconstructs the non-linear part of Pₘ(k) for k≳1 Mpc⁻¹ without the need of assuming a non-linear model.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections