Thanks for calling attention to this article. It is in my field of interest.
Yes it is very dense but I think I get most of it. The article wants to
narrow the field of what is probable in the universe by eliminating what is
impossible and all the interrelated things that are impossible, leaving a
smaller field of the probable.

The passage you quote was focusing on the two main components that can
reduce the # of probable outcomes of the 31 parameter probability
distribution f(p). Our 31 mysterious constants that defy explanation!

There are two main components. f (prior) of p and f(selection) of p.
f (prior) refers to the reduced number of possible setups for our universe,
prior to its observation. The content of this part of the paper focuses on
astrophysical selection effects which include the dark matter density
parameter, dark energy density, and seed fluctuation density, to ensure the
formation of dark matter halos, galaxies and stable solar systems.
f(selection) refers to the observer or selection effect that corresponds to
f (prior). Go to page 10 for this discussion.
"Edward Green" wrote in message
ups.com...
I should be able to understand the following discussion in

http://arxiv.org/PS_cache/astro-ph/pdf/0511/0511774.pdf

"Let us group the 31 parameters of Table 1 into a 31-
dimensional vector p. In a fundamental theory where
inflation populates a landscape of possibilities, some or
all of these parameters will vary from place to place as
described by a 31-dimensional probability distribution
f(p). Testing this theory observationally corresponds
to confronting that theoretically predicted distribution
with the values we observe. Selection effects make this
challenging [9, 12]: if any of the parameters that can
vary affect the formation of (say) protons, galaxies or ob-
servers, then the parameter probability distribution dif-
fers depending on whether it is computed at a random
point, a random proton, a random galaxy or a random
observer [12, 14]. A standard application of conditional
probabilities predicts the observed distribution

f(p) ~ f_prior(p) f_selec(p) (1)

where f_prior(p) is the theoretically predicted distribution
at a random point at the end of inflation and f_selec(p) is
the probability of our observation being made at that
point. This second factor f_selec(p), incorporating the
selection effect, is simply proportional to the expected
number density of reference objects formed (say, protons,
galaxies or observers)."

However, even conditioning on a prior knowledge of conditional
probabilities and Bayesian inference, I am unable to make heads or
tails of it. The passage contains elements which sound not unlike
standard noises made in statistics, others likely to make a
statistician cringe, and combinations of these which maddeningly
suggest meaning but bound away just out of bow-shot, like the white
stag.

Does anybody wish to defend their thought?