THE AGE-REDSHIFT RELATIONSHIP OF OLD PASSIVE GALAXIES

Jun Jie Wei, Xue Feng Wu, Fulvio Melia, Fa Yin Wang, Hai Yu

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

We use 32 age measurements of passively evolving galaxies as a function of redshift to test and compare the standard model (λCDM) with the R<inf>h</inf> = ct universe. We show that the latter fits the data with a reduced χ<inf>dof</inf><sup>2</sup> = 0.435 for a Hubble constant = H<inf>0</inf> 67.2<inf>-4.0</inf> <sup>+4.5</sup> km s<sup>-1</sup> Mpc<sup>-1</sup>. By comparison, the optimal flat λCDM model, with two free parameters (including ω<inf>m</inf> = 0.12<inf>-0.11</inf><sup>+0.54</sup> and = - H 94.3+ 0 35.8 32.7 km s?1 Mpc-1), fits the age-z data with a reduced c = 0.428 dof 2 . Based solely on their cdof 2 values, both models appear to account for the data very well, though the optimized ?CDM parameters are only marginally consistent with those of the concordance model (Wm = 0.27 and H0 = 70 km s-1 Mpc-1). Fitting the age-z data with the latter results in a reduced χ<inf>dof</inf><sup>2</sup> = 0.523. However, because of the different number of free parameters in these models, selection tools, such as the Akaike, Kullback and Bayes Information Criteria, favor R<inf>h</inf> = ct over ?CDM with a likelihood of ?66.5%80.5% versus ∼19.5%33.5%. These results are suggestive, though not yet compelling, given the current limited galaxy age-z sample. We carry out Monte Carlo simulations based on these current age measurements to estimate how large the sample would have to be in order to rule out either model at a ∼99.7% confidence level. We find that if the real cosmology is λCDM, a sample of ?45 galaxy ages would be sufficient to rule out Rh = ct at this level of accuracy, while ?350 galaxy ages would be required to rule out λCDM if the real universe were instead Rh = ct. This difference in required sample size reflects the greater number of free parameters available to fit the data with λCDM.

Original languageEnglish (US)
Article number35
JournalAstronomical Journal
Volume150
Issue number1
DOIs
StatePublished - Jul 1 2015

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galaxies
universe
Hubble constant
cosmology
confidence
estimates
simulation
parameter

Keywords

  • cosmology: observations
  • cosmology: theory
  • early universe
  • Galaxy: general

ASJC Scopus subject areas

  • Space and Planetary Science
  • Astronomy and Astrophysics

Cite this

THE AGE-REDSHIFT RELATIONSHIP OF OLD PASSIVE GALAXIES. / Wei, Jun Jie; Wu, Xue Feng; Melia, Fulvio; Wang, Fa Yin; Yu, Hai.

In: Astronomical Journal, Vol. 150, No. 1, 35, 01.07.2015.

Research output: Contribution to journalArticle

Wei, Jun Jie ; Wu, Xue Feng ; Melia, Fulvio ; Wang, Fa Yin ; Yu, Hai. / THE AGE-REDSHIFT RELATIONSHIP OF OLD PASSIVE GALAXIES. In: Astronomical Journal. 2015 ; Vol. 150, No. 1.
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abstract = "We use 32 age measurements of passively evolving galaxies as a function of redshift to test and compare the standard model (λCDM) with the Rh = ct universe. We show that the latter fits the data with a reduced χdof2 = 0.435 for a Hubble constant = H0 67.2-4.0 +4.5 km s-1 Mpc-1. By comparison, the optimal flat λCDM model, with two free parameters (including ωm = 0.12-0.11+0.54 and = - H 94.3+ 0 35.8 32.7 km s?1 Mpc-1), fits the age-z data with a reduced c = 0.428 dof 2 . Based solely on their cdof 2 values, both models appear to account for the data very well, though the optimized ?CDM parameters are only marginally consistent with those of the concordance model (Wm = 0.27 and H0 = 70 km s-1 Mpc-1). Fitting the age-z data with the latter results in a reduced χdof2 = 0.523. However, because of the different number of free parameters in these models, selection tools, such as the Akaike, Kullback and Bayes Information Criteria, favor Rh = ct over ?CDM with a likelihood of ?66.5{\%}80.5{\%} versus ∼19.5{\%}33.5{\%}. These results are suggestive, though not yet compelling, given the current limited galaxy age-z sample. We carry out Monte Carlo simulations based on these current age measurements to estimate how large the sample would have to be in order to rule out either model at a ∼99.7{\%} confidence level. We find that if the real cosmology is λCDM, a sample of ?45 galaxy ages would be sufficient to rule out Rh = ct at this level of accuracy, while ?350 galaxy ages would be required to rule out λCDM if the real universe were instead Rh = ct. This difference in required sample size reflects the greater number of free parameters available to fit the data with λCDM.",
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AB - We use 32 age measurements of passively evolving galaxies as a function of redshift to test and compare the standard model (λCDM) with the Rh = ct universe. We show that the latter fits the data with a reduced χdof2 = 0.435 for a Hubble constant = H0 67.2-4.0 +4.5 km s-1 Mpc-1. By comparison, the optimal flat λCDM model, with two free parameters (including ωm = 0.12-0.11+0.54 and = - H 94.3+ 0 35.8 32.7 km s?1 Mpc-1), fits the age-z data with a reduced c = 0.428 dof 2 . Based solely on their cdof 2 values, both models appear to account for the data very well, though the optimized ?CDM parameters are only marginally consistent with those of the concordance model (Wm = 0.27 and H0 = 70 km s-1 Mpc-1). Fitting the age-z data with the latter results in a reduced χdof2 = 0.523. However, because of the different number of free parameters in these models, selection tools, such as the Akaike, Kullback and Bayes Information Criteria, favor Rh = ct over ?CDM with a likelihood of ?66.5%80.5% versus ∼19.5%33.5%. These results are suggestive, though not yet compelling, given the current limited galaxy age-z sample. We carry out Monte Carlo simulations based on these current age measurements to estimate how large the sample would have to be in order to rule out either model at a ∼99.7% confidence level. We find that if the real cosmology is λCDM, a sample of ?45 galaxy ages would be sufficient to rule out Rh = ct at this level of accuracy, while ?350 galaxy ages would be required to rule out λCDM if the real universe were instead Rh = ct. This difference in required sample size reflects the greater number of free parameters available to fit the data with λCDM.

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