The Most Probable Behaviour of the Dark Energy Equation of State Indicates a Thawing Quintessence Field: Tomographic Alcock-Paczy\'nski Test with Redshift-Space Correlation Function II
Fuyu Dong, Changbom Park

TL;DR
This study applies an extended Alcock-Paczyński test to SDSS data to constrain dark energy models, finding results consistent with a thawing quintessence field and no phantom crossing at low redshift, especially when combined with other cosmological data.
Contribution
It introduces an extended AP test using the full shape of the redshift-space correlation function calibrated with simulations to constrain dark energy parameters.
Findings
Constraints favor a thawing quintessence model.
No evidence of phantom-divide crossing at z<0.7.
Combining with CMB data suggests low-redshift phantom crossing.
Abstract
We apply an extended Alcock-Paczy\'nski (AP) test to the Sloan Digital Sky Survey data to constrain the dark energy models with the Chevallier-Polarski-Linder (CPL) parametrization of the dark energy equation of state. The extended AP test method uses the full shape of redshift-space two-point correlation funcion(CF) as the standard shape in order to measure the expansion history of the universe. We calibrate the standard shape by using the cosmology-dependent nonlinear evolution of the CF shape in the Multiverse simulations. Further validation of the method and calibration of possible systematics are performed based on mock samples from the Horizon Run 4 simulation. Using the AP test alone, we constrain the flat CDM plus CPL-type dark energy model (flat CDM) to have , , and . When…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCosmology and Gravitation Theories · Galaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research
