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 82 tok/s
Gemini 2.5 Pro 45 tok/s Pro
GPT-5 Medium 25 tok/s Pro
GPT-5 High 36 tok/s Pro
GPT-4o 110 tok/s Pro
Kimi K2 207 tok/s Pro
GPT OSS 120B 469 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Litmus tests of the flat $Λ$CDM model and model-independent measurement of $H_0r_\mathrm{d}$ with LSST and DESI (2407.07847v3)

Published 10 Jul 2024 in astro-ph.CO and gr-qc

Abstract: In this analysis we apply a model-independent framework to test the flat $\Lambda$CDM cosmology using simulated SNIa data from the upcoming Legacy Survey of Space and Time (LSST) and combined with simulated Dark Energy Spectroscopic Instrument (DESI) five-years Baryon Acoustic Oscillations (BAO) data. We adopt an iterative smoothing technique to reconstruct the expansion history from SNIa data, which, when combined with BAO measurements, facilitates a comprehensive test of the Universe's curvature and the nature of dark energy. The analysis is conducted under four different mock true cosmologies: Two curvatures ($\Omega_{k,0}=0$ and 0.1) and two models of dark energy: a cosmological constant $\Lambda$ and the phenomenologically emergent dark energy. We forecast that our reconstruction technique can constrain cosmological parameters, such as the curvature ($\Omega_{k,0}$) and $c/(H_0 r_\mathrm{d})$, with spread due to the SNIa uncertainties up to $\pm 4\%$ and $\pm 0.1$ respectively, without assuming any form of dark energy.

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.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

This paper has been mentioned in 2 posts and received 2 likes.