Jensen's paper

<blockquote id="quote"><font size="2" face="Verdana, Arial, Helvetica" id="quote">quote:<hr height="1" noshade id="quote"><i>Originally posted by mhelland</i>
<br />Regarding Jensen's paper...<hr height="1" noshade id="quote"></blockquote id="quote"></font id="quote">That was referenced and discussed in the "Supernova" thread under "Meta Science", for those not following that topic.

<blockquote id="quote"><font size="2" face="Verdana, Arial, Helvetica" id="quote">quote:<hr height="1" noshade id="quote">How possible do you suppose it would be to give a decent summary of what a Malmquist Type II bias for this board in order for readers to sound somewhat educated about the idea if they wish to discuss it with others?<hr height="1" noshade id="quote"></blockquote id="quote"></font id="quote">Visualize intrinsic brightness plotted along the x-axis (increasing to the right), and number counts along the y-axis. Then most types of cosmological things, including supernovas, will approximate a normal distribution curve (which looks like a hill). There will be relatively few intrinsically very bright or very faint members of the set, but lots of near-average members (the peak of the hill).

All is well when we can observe a representative sampling of all supernovas. However, in the real universe, we have two factors that can distort the statistics. One is that the volume of space sampled goes up with the cube of distance. The other is that apparent brightness goes down with at least the square of distance. (An argument can be made that apparent brightness actually falls with the cube or fourth power of distance.)

But fainter members of our set are harder to discover. At really large distances, they may even be impossible to discover. So when we start collecting data from high redshifts, we tend to find only the intrinsically brightest members of the set because the fainter ones are difficult or impossible to find. In short, we sample only members sitting at the brightside foot of the hill that represents the distribution of the set of all members.

That means that we tend to see only the intrinsically brightest supernovas at the greatest distances. But those happen to be the ones with the widest (in time) light curves, the ones that take 60 days or more to rise and fall instead of the more typical 30 days. So even without any time dilation, we will see our sample of high-redshift supernovas tend toward longer-duration light curves with increasing distance. And if we make no allowance to correct for this type of sampling bias, we will fool ourselves into thinking that we have detected a time dilation effect even if none exists.

<blockquote id="quote"><font size="2" face="Verdana, Arial, Helvetica" id="quote">quote:<hr height="1" noshade id="quote">And do you know if Jensen has a website that would contain the most up-to-date information on his paper (any criticisms or rebuttles, how its being received, ect.)?<hr height="1" noshade id="quote"></blockquote id="quote"></font id="quote">You can be certain that, if a fault exists, much will be made of it; but if none can be seen, the reaction will be silence. That is how the mainstream in any field protects itself and stays in control. -|Tom|-

Cool! That really makes it click.

mhelland@techmocracy.net

Tom, In addition to distance making it harder to detect novas doesn't one also have to take into account time since one is looking farther back in time as well? In a Big Bang universe wouldn't we expect to find fewer novas looking back in time because the stars are younger and few of them are old enough to go nova?

<blockquote id="quote"><font size="2" face="Verdana, Arial, Helvetica" id="quote">quote:<hr height="1" noshade id="quote"><i>Originally posted by Jeremy</i>
<br />doesn't one also have to take into account time since one is looking farther back in time as well? In a Big Bang universe wouldn't we expect to find fewer novas looking back in time because the stars are younger and few of them are old enough to go nova?<hr height="1" noshade id="quote"></blockquote id="quote"></font id="quote">Novas and supernovas have different causes and differ greatly in brightness, frequency, and diversity. We were discussing only supernovas.

High-mass stars are prime candidates to become supernovas. The largest of these have total lifetimes of only millions of years, not billions. So they are still very abundant even at the earliest epochs we can observe. And their frequency of occurence is not a factor in the analysis. -|Tom|-

Tom, do you know the difference between a Malmquist Type I and a Type II bias? I can't find anything on this.

mhelland@techmocracy.net

<blockquote id="quote"><font size="2" face="Verdana, Arial, Helvetica" id="quote">quote:<hr height="1" noshade id="quote"><i>Originally posted by mhelland</i>
<br />Tom, do you know the difference between a Malmquist Type I and a Type II bias? I can't find anything on this.<hr height="1" noshade id="quote"></blockquote id="quote"></font id="quote">The reference Jensen gives for this is: [Teerikorpi et al., “Observational Selection Bias affecting the Determination of the Extragalactic Distance Scale”, Annual Review of Astronomy and Astrophysics, Vol. 35, 1997]. I have not consulted the reference; but by implication and usage, the two Malmquist bias types are the same basic phenomenon, but manifest slightly differently depending on how the sample is selected.

For example, most surveys are brightness-selected, and I presume that would be the Type I bias. But some samples are redshift-selected (for example when certain filters are used), and I presume that is the most likely case that might lead to defining a Type II bias. The high-z redshift survey is obviously a redshift-selected sample. -|Tom|-