This is pure speculation, but the mystery of the missing antimatter from the Big Bang may be explained by forming a separate antimatter universe in conjunction with ours. During the period of inflation, the universe expanded much faster than the speed of light. If the two universes; one matter, the other antimatter; were driven apart during the inflationary period, we would not be able to observe the second universe because the light from it would not have reached us. I wonder if there is such a thing as anti-light. There may well be several universes we cannot see or may have seen, but not recognized.

Food for thought – Bill

Keep looking up and Happy New Year.

B.

Meaning, if I had to wager whether the constants must be what they are, or whether they can vary in a grander multiverse, I’d bet against the latter. But I do see how, at the moment, variation in the fundamental constants is an open question and that my position (searching for a deeper cause for the constants, in say number theory) is stagnant, and also that there are new directions to search for variation (as Matt has described above).

So although I would more naturally side with your option “a”, I can see how option “2″ is currently a more active and productive area of research.

Matt, thanks for expanding on the vacuum bit.

Cody – In the context of string theory, the many “vacua” I am referring to arise from the many ways one can imagine hiding the extra dimensions predicted by string theory. This is typically accomplished by compactifying the extra dimensions. The shape and size of the compactified extra dimensions (along with other ingredients like branes, etc) determines the properties of the four-dimensional physics we know and love. So, for every shape and size, one obtains a different set of physical constants (like the planck scale, vacuum energy, etc), and perhaps a different set of interactions (perhaps there is another force in other vacua on top of the four we observe in our own universe).

Aaron – The CMB is certainly anisotropic. One typically characterizes the statistics of these anisotropies in terms of the power spectrum (and higher point correlation functions). Tests have been applied to determine if there is any variation on the sky in these statistics, yielding some evidence for statistical anisotropy. However, if one is looking for a local fluctuation in the temperature of the CMB of a very specific form (as we were), these types of statistics are typically not the most useful thing to look at. Indeed, many things could be buried in the data which would, say, yield a negligible “bump” in the power spectrum compared to experimental errors and cosmic variance (ie the small sample size of large-scale modes). This perhaps gets at the sentence you wanted to see in our paper: Before doing our analysis, we can rule out features in the data with an amplitude much larger than the characteristic amplitude of features set by the power spectrum (around 10^{-4} kelvin or so), or other measured statistical properties of the CMB.

Peter – We comment briefly on how one can obtain a “sigma” from the Bayesian evidence ratio in the longer paper (see the discussion near Eq. 28). There are various assumptions made in doing so, but very roughly, you can interpret our results as near 3-sigma.

Bee – The probability that we 1) have a bubble collision in our past and 2) it yields a signal strength consistent with current data, is highly uncertain. It could very well be negligible. For detailed discussion of these issues, you can check out the review paper I wrote with Anthony Aguirre (arXiv:0908.4105). What previous work has shown is that the criteria for observing bubble collisions can be satisfied in some cases. Without a more detailed picture of, say, the string theory landscape, it is difficult to ascertain the theoretical prior on what to expect. Nevertheless, we have the data, some idea of what the signature of bubble collisions should look like, and some theories where we expect to see them, so our philosophy was: they might be there, so why not go look?

Now all I need to do is find those signatures in CMB, and everyone will have to accept my theory, right? RIGHT?

So the question then becomes: why these particular values and not others? With most aspects of nature, everything not mandatory is forbidden: in other words, if a certain variation in a property is allowed, we expect to see the variation. If we don’t see the variation, we begin to suspect that such variation is not, in fact, allowed. So given that we have these fundamental “constants” that could really be parameters, we’re driven to find out whether there’s a) some constraining rule that we’re missing, or 2) look for somewhere where the values are different.

Thanks for taking the time to blog. I’m still wondering how plausible is it to expect a signal in the suitable parameter range to begin with? Is there some range of parameters that would seem natural? Best,

B.

I am not quite sure what you mean… when WMAP released its first dataset it showed variation at the level of 10^{-5}. The period from discovery (~1960) to mid-1980s there was no evidence for non-uniformity in the CMB as measurements were not good enough. BOOMERANG, MAXIMA and taco were the first experiments to see deviations from uniformity.

The Planck or Wmap papers would be a good place to start looking. If you meant non-gaussianty rather than non-uniformity then we are still waiting for a verdict.

Previous tests for non-uniformity in the WMAP dataset statistically eliminate effect sizes greater than or equal to X at a significance of Y (insert citations), this leave open the possibility of detecting non-uniformities of characteristic angular size Z and temperature variation T or smaller, this paper analyzes …

Until the hypothesis that the CMB is uniform has been statistically demonstrated to be false, other inferences and hypotheses are moot.

There are many statistical tests for non-randomness, especially in the cryptography and random number generation literature (e.g. information entropy measures), I would hope some of them would be applied to the CMB data to first test the hypothesis of uniformity; before proceeding to characterizing the non-uniformity.