David Wiltshire: Cosmic Clocks, Cosmic Variance & Cosmic Averages

  • Context: Graduate 
  • Thread starter Thread starter Kea
  • Start date Start date
  • Tags Tags
    Cosmology
Click For Summary

Discussion Overview

The discussion revolves around David Wiltshire's paper titled "Cosmic clocks, cosmic variance and cosmic averages," which critiques the concept of dark energy (DE) and presents alternative interpretations of supernova data. Participants engage with the paper's arguments, its treatment of observational data, and implications for cosmological models.

Discussion Character

  • Debate/contested
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • Some participants express interest in Wiltshire's paper, noting its well-written nature but questioning the persuasiveness of its conclusions.
  • Concerns are raised regarding the treatment of supernova data (SNIa), with one participant suggesting it appears dismissive.
  • David Wiltshire responds, indicating that criticisms may stem from not fully engaging with the entire paper, which is lengthy. He highlights that apparent acceleration is now obtained in his analysis, contrasting it with earlier rough approximations.
  • Wiltshire mentions that the goodness of fit for his model is statistically indistinguishable from the Lambda CDM model and discusses the implications of including the "Hubble bubble" in the analysis.
  • He suggests that the differences in residuals between the Lambda CDM and his model could provide a means to distinguish between them with more extensive data in the future.
  • One participant acknowledges a misunderstanding of the implications in the paper and commits to a more careful reading.

Areas of Agreement / Disagreement

Participants do not reach a consensus; there are competing views regarding the treatment of supernova data and the validity of Wiltshire's claims about dark energy.

Contextual Notes

Some limitations include the length of the paper, which may affect thorough engagement with its content, and the ongoing debate about the interpretation of supernova data and its implications for cosmological models.

Kea
Messages
859
Reaction score
0
People might be interested in a new paper, namely

Cosmic clocks, cosmic variance and cosmic averages
David L. Wiltshire
72 pages, 5 figures
http://www.arxiv.org/abs/gr-qc/0702082

which demolishes DE (yet again!).
 
Space news on Phys.org
I like the paper, it is well written as usual [he has a way with words]. But the conclusions are not convincing. The treatment of SNIa data, for example, appears to be dismissive, IMO.
 
comment from D. Wiltshire

DLW wishes to advise that the statement that the treatment of SNIa data, for example, appears to be dismissive would seem to have been made without reading all of the paper, which is understandable given it is 72 pages long. In view of the length of the paper, he has placed a summary of observational results and a faq at

http://www2.phys.canterbury.ac.nz/~dlw24/universe/

In relation to the supernova data, see Figs 2 and 3, surrounding discussion and section 7.5. Apparent acceleration is now obtained, unlike in the rough approximations of earlier work. Moreover, the goodness of fit is now statistically indistinguishable from the Lambda CDM model. (Further details will be released in a paper with Leith and Ng, ref [16].) For those who wish to actually pay attention to data, the question of whether or not the "Hubble bubble" should be included (a difference between Riess04 and Riess06 gold data sets), is a serious issue for the Lambda CDM paradigm, as the supernovae data teams have pointed out (in a quiet way) in their recent eprints astro-ph/0612666, astro-ph/0701041. This feature has a natural explanation in the FB model, as discussed in section 7.5, and should ultimately be open to quantitative testing. The difference of the residuals between the Lambda CDM models and the FB model in Fig. 3 also indicate that supernovae data may prove to be a good way to distinguish the models once some thousands or tens of thousands of data points are collected, even though the present data cannot distinguish the two models.
 
Point conceded. I did not fully appreciate the implications suggested in this passage during my initial reading. Will give the paper a more careful reading [I do tend to gloss at times].
 
Last edited:

Similar threads

  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
3K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 3 ·
Replies
3
Views
3K
Replies
1
Views
3K
  • · Replies 6 ·
Replies
6
Views
3K