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 71 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 27 tok/s Pro
GPT-5 High 30 tok/s Pro
GPT-4o 93 tok/s Pro
Kimi K2 207 tok/s Pro
GPT OSS 120B 460 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Observational constraints on one-parameter dynamical dark-energy parametrizations and the $H_0$ tension (1810.05141v2)

Published 11 Oct 2018 in astro-ph.CO and gr-qc

Abstract: The phenomenological parametrizations of dark-energy (DE) equation of state can be very helpful, since they allow for the investigation of its cosmological behavior despite the fact that its underlying theory is unknown. However, although there has been a large amount of research on DE parametrizations which involve two or more free parameters, the one-parameter parametrizations seem to be underestimated. We perform a detailed observational confrontation of five one-parameter DE models, with observational data from cosmic microwave background (CMB), Joint light-curve analysis sample from Supernovae Type Ia observations (JLA), baryon acoustic oscillations (BAO) distance measurements, and cosmic chronometers (CC). We find that all models favor a phantom DE equation of state at present time, while they lead to $H_0$ values in perfect agreement with its direct measurements and therefore they offer an alleviation to the $H_0$-tension. Finally, performing a Bayesian analysis we show that although $\Lambda$CDM cosmology is still favored, one-parameter DE models have similar or better efficiency in fitting the data comparing to two-parameter DE parametrizations, and thus they deserve a thorough investigation.

Citations (93)

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.