Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 88 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 21 tok/s Pro
GPT-5 High 13 tok/s Pro
GPT-4o 81 tok/s Pro
Kimi K2 175 tok/s Pro
GPT OSS 120B 450 tok/s Pro
Claude Sonnet 4 39 tok/s Pro
2000 character limit reached

Joint Constraints on the Hubble Constant, Spatial Curvature, and Sound Horizon from the Late-time Universe with Cosmography (2310.16512v2)

Published 25 Oct 2023 in astro-ph.CO and gr-qc

Abstract: In this paper, using the latest Pantheon+ sample of Type Ia supernovae (SNe Ia), Baryon Acoustic Oscillation (BAO) measurements, and observational Hubble data (OHD), we carry out a joint constraint on the Hubble constant $H_0$, the spatial curvature $\Omega_{\rm K}$, and the sound horizon at the end of drag epoch $r_{\rm d}$. To be model-independent, four cosmography models, i.e., the Taylor series in terms of redshift $y_1=z/(1+z)$, $y_2=\arctan(z)$, $y_3=\ln(1+z)$, and the Pad\'e approximants, are used without the assumption of flat Universe. The results show that the $H_0$ is anti-correlated with $\Omega_{\rm K}$ and $r_{\rm d}$, indicating smaller $\Omega_{\rm K}$ or $r_{\rm d}$ would be helpful in alleviating the Hubble tension. And the values of $H_0$ and $r_{\rm d}$ are consistent with the estimate derived from the Planck Cosmic Microwave Background (CMB) data based on the flat $\Lambda$CDM model, but $H_0$ is in 2.3$\sim$3.0$\sigma$ tension with that obtained by \cite{Riess2022} in all these cosmographic approaches. Meanwhile, a flat Universe is preferred by the present observations under all approximations except the third order of $y_1$ and $y_2$ of the Taylor series. Furthermore, according to the values of the Bayesian evidence, we found that the flat $\Lambda$CDM remains to be the most favored model by the joint datasets, and the Pad\'e approximant of order (2,2), the third order of $y_3$ and $y_1$ are the top three cosmographic expansions that fit the datasets best, while the Taylor series in terms of $y_2$ are essentially ruled out.

Citations (2)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

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

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

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

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube