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 43 tok/s
Gemini 2.5 Pro 48 tok/s Pro
GPT-5 Medium 21 tok/s Pro
GPT-5 High 20 tok/s Pro
GPT-4o 95 tok/s Pro
Kimi K2 180 tok/s Pro
GPT OSS 120B 443 tok/s Pro
Claude Sonnet 4.5 32 tok/s Pro
2000 character limit reached

Constraining a variable dark energy model from the redshift-luminosity distance relations of gamma-ray bursts and type Ia supernovae (1611.04309v1)

Published 14 Nov 2016 in astro-ph.CO

Abstract: There are many kinds of models which describe the dynamics of dark energy (DE). Among all we adopt an equation of state (EoS) which varies as a function of time. We adopt Markov Chain Monte Carlo method to constrain the five parameters of our models. As a consequence, we can show the characteristic behavior of DE during the evolution of the universe. We constrain the EoS of DE with use of the avairable data of gamma-ray bursts and type Ia supernovae (SNe Ia) concerning the redshift-luminosity distance relations. As a result, we find that DE is quintessence-like in the early time and phantom-like in the present epoch or near the future, where the change occurs rather rapidly at $z\sim0.3$.

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.