Lesson plan
Source counts
The source counts distribution of radio-sources from a radio-astronomical survey is the cumulative distribution of the number of sources (N) brighter than a given flux density (S). As it is usually plotted on a log-log scale its distribution is known as the log N – log S plot. It is one of several cosmological tests that were conceived in the 1930s to check the viability of and compare new cosmological models. Early work to catalogue radio sources aimed to determine the source count distribution as a discriminating test of different cosmological models. For example, a uniform distribution of radio sources at low redshift, such as might be found in a 'steady-state Euclidean universe,' would produce a slope of −1.5 in the cumulative distribution of log(N) versus log(S). Data from the early Cambridge 2C survey (published 1955) apparently implied a (log(N), log(S)) slope of nearly −3.0. This appeared to invalidate the steady state theory of Fred Hoyle, Hermann Bondi and Thomas Gold. Unfortunately many of these weaker sources were subsequently found to be due to 'confusion' (the blending of several weak sources in the side-lobes of the interferometer, producing a stronger response). By contrast, analysis from the contemporaneous Mills Cross data (by Slee and Mills) were consistent with an index of −1.5.…
Article summary
The source counts distribution of radio-sources from a radio-astronomical survey is the cumulative distribution of the number of sources (N) brighter than a given flux density (S). As it is usually plotted on a log-log scale its distribution is known as the log N – log S plot. It is one of several cosmological tests that were conceived in the 1930s to check the viability of and compare new cosmological models. Early work to catalogue radio sources aimed to determine the source count distribution as a discriminating test of different cosmological models. For example, a uniform distribution of radio sources at low redshift, such as might be found in a 'steady-state Euclidean universe,' would produce a slope of −1.5 in the cumulative distribution of log(N) versus log(S). Data from the early Cambridge 2C survey (published 1955) apparently implied a (log(N), log(S)) slope of nearly −3.0. This appeared to invalidate the steady state theory of Fred Hoyle, Hermann Bondi and Thomas Gold. Unfortunately many of these weaker sources were subsequently found to be due to 'confusion' (the blending of several weak sources in the side-lobes of the interferometer, producing a stronger response). By contrast, analysis from the contemporaneous Mills Cross data (by Slee and Mills) were consistent with an index of −1.5.…
Key claims
- publication date: 1955 — source: Wikipedia · confidence 0.95
Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- The record states that the publication date is "1955". What evidence would count against this claim?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
- Wikipedia https://en.wikipedia.org/w/index.php?oldid=1188206305
Key claims and bibliography are generated from the same tracked claims and sources as the article page.