Originally Posted by

**Hornblower**
I have tried reading that paper, and I have a hard time trying to figure out just what you are saying technically. It makes me think of two possibilities:

1. Written for colleagues who understand writing language that includes jargon known and understood by advanced researchers in this field but not necessarily by general audiences.

2. Creative doubletalk designed to dazzle novices.

Let's hope it is #1. In my opinion we need to go paragraph by paragraph, with some sketches to illustrate just what you are talking about at each step. I cannot dope it out from the graphs and equations around the middle of the paper. You need to show us how the raw light curves are typically obtained for these faint objects, and walk us through the potential booby traps in language that can be understood by ordinary readers of this forum. If it is not explainable without resorting to mathematical techniques beyond what can reasonably be expected of most of us, it is pointless to argue your case in a forum like this.

The essence of David’s argument can be found in figure 2 and in figure 3:

Figure two plots the light curve widths of supernova (type 1a) as they explode over time. David has used a templating process just like researchers in the field, but without correction for time dilation. What he has plotted is the light curve widths in multiple wavelengths verses time. Notice that they are almost, but not quite, normally distributed about the x-axis, which is what you would expect to see if there was a small selection effects towards brighter events with increasing distance. But this is NOT the normal distribution one expects to see if redshifted space is also corrected for relativistic effects – this is the red line in David’s plot. If supernova events are consistent over time, the light curve widths should be normally distributed about the red line in David’s plot.

I have plotted a distribution curve for supernova based upon the magnitude lost in 15 days, which is inversely correlated with light curve width, and concluded the same thing: light curves are normally distributed if you do not correct the width for time dilation, but they appear to be absurdly smaller with increasing distance after correcting for time dilation.

There is no reason to look at the statistical significance of David ‘s plot: The ‘red line’ expected by the current cosmology so utterly fails to follow the observational data that it is obvious there is a gross error in the way supernova are analyzed. Cosmologists such as Ned Wright are completely aware of this phenomenon, and to the best of my knowledge they are still trying to understand it. I am surprised the trend has been so constant.

Figure three is a plot of the calculated absolute magnitude of supernova events when their light curve widths are correlated with local events. Here again it is clear that without the time dilation included in the magnitude calculation, the distant supernova events have very near the same average intensity as local events, but when time dilation is included the absolute magnitude appears to be decreasing dramatically if not absurdly.

Again, these are not new observations, just an extension of the ‘weirdness’ of supernova data that has persisted for two decades. A similar trend is apparent in gamma ray burst data, but it is currently to widely scattered to draw hard conclusions.

Last edited by Jerry; 2018-Jan-03 at 05:41 AM.

“It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” ― Arthur Conan Doyle, Sherlock Holmes