Papers
Topics
Authors
Recent
Search
2000 character limit reached

The role of LRG1 and LRG2's monopole in inferring the DESI 2024 BAO cosmology

Published 3 May 2024 in astro-ph.CO | (2405.02168v2)

Abstract: The Dark Energy Spectroscopic Instrument (DESI) collaboration recently released its first year of data (DR1) on baryon acoustic oscillations (BAO) in galaxy, quasar, and Lyman-$\alpha$ forest tracers. When combined with CMB and SNIa data, DESI BAO results suggest potential thawing behavior in dark energy. Cosmological analyses utilize comoving distances along ($D_H$) and perpendicular to ($D_M$) the line of sight. Notably, there are $1\sim2\sigma$ deviations in $D_M$ and $D_H$ from Planck cosmology values in the luminous red galaxies (LRG) bins LRG1 and LRG2.This study examines the role of LRG1 and LRG2 in diverging DESI 2024 BAO cosmology from Planck cosmology. We use angle-averaged distance $D_V$ and the ratio $F_{\rm AP}=D_M/D_H$, which are more directly related to the measured monopole and quadrupole components of the galaxy power spectrum or correlation function, instead of the officially adopted $D_M$ and $D_H$. This transformation aims to isolate the influence of monopoles in LRG1 and LRG2 on deviations from $w=-1$. Our findings indicate that removing the $D_V$ data point in LRG2 aligns DESI + CMB + SNIa data compilation with $w=-1$ within a $2\sigma$ contour and reduces the $H_0$ discrepancy from the Planck 2018 results from $0.63\sigma$ to $0.31\sigma$. Similarly, excluding the $D_V$ data point from LRG1 shifts the $w_0/w_a$ contour toward $w=-1$, although no intersection occurs. This highlights the preference of both LRG1 and LRG2 BAO monopole components for the thawing dark energy model, with LRG2 showing a stronger preference. We provide the $D_V$ and $F_{\rm AP}$ data and their covariance alongside this paper.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (18)
  1. M. Chevallier and D. Polarski, Int. J. Mod. Phys. D 10, 213 (2001), arXiv:gr-qc/0009008 .
  2. E. V. Linder, Phys. Rev. Lett. 90, 091301 (2003), arXiv:astro-ph/0208512 .
  3. S. Alam et al. (eBOSS), Phys. Rev. D 103, 083533 (2021), arXiv:2007.08991 [astro-ph.CO] .
  4. R. R. Caldwell and E. V. Linder, Phys. Rev. Lett. 95, 141301 (2005), arXiv:astro-ph/0505494 .
  5. D. Wang, arXiv e-prints , arXiv:2404.06796 (2024a), arXiv:2404.06796 [astro-ph.CO] .
  6. M. Cortês and A. R. Liddle, arXiv e-prints , arXiv:2404.08056 (2024), arXiv:2404.08056 [astro-ph.CO] .
  7. Y. Tada and T. Terada,   (2024), arXiv:2404.05722 [astro-ph.CO] .
  8. O. Luongo and M. Muccino, arXiv e-prints , arXiv:2404.07070 (2024), arXiv:2404.07070 [astro-ph.CO] .
  9. H. Wang and Y.-S. Piao,   (2024), arXiv:2404.18579 [astro-ph.CO] .
  10. C. Escamilla-Rivera and R. Sandoval-Orozco,   (2024), arXiv:2405.00608 [astro-ph.CO] .
  11. W. Yin,   (2024), arXiv:2404.06444 [hep-ph] .
  12. D. Wang, arXiv e-prints , arXiv:2404.13833 (2024b), arXiv:2404.13833 [astro-ph.CO] .
  13. G. Efstathiou and S. Gratton, The Open Journal of Astrophysics 4 (2021), 10.21105/astro.1910.00483.
  14. P. J. E. Peebles and J. T. Yu, Astrophys. J.  162, 815 (1970).
  15. J. Torrado and A. Lewis, “Cobaya: Bayesian analysis in cosmology,” Astrophysics Source Code Library, record ascl:1910.019 (2019).
  16. J. Torrado and A. Lewis, J. Cosmol. Astropart. Phys. 2021, 057 (2021), arXiv:2005.05290 [astro-ph.IM] .
  17. A. Lewis, arXiv e-prints , arXiv:1910.13970 (2019), arXiv:1910.13970 [astro-ph.IM] .
  18. A. Gelman and D. B. Rubin, Statistical Science 7, 457 (1992).
Citations (8)

Summary

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.

Tweets

Sign up for free to view the 3 tweets with 2 likes about this paper.