Applying the BIC in practice is far from straightforward and fraught with difficulties because it requires the regularization of space-time infinities by implementing some cosmic “measure.” Furthermore, a suitable physical quantity must be chosen as proxy for the number of reference class observers in some given space-time region. Unfortunately, the choices made in this procedure are prone to being exploited – often unintentionally – by the researchers as so-called researcher degrees of freedom (a term from the social science literature) to yield those results that would best conform to their theoretical preferences. In the light of this difficulty, the prospects for obtaining compelling evidence in favor of any specific multiverse theory by testing whether our observations are those that typical multiverse inhabitants would make do look bad. As it turns out, the multiverse theories that have the best chances of being successfully tested empirically are those that do not behave as typical multiverse theories in important respects – i.e., those multiverse theories according to which all universes in the multiverse are similar or identical in a significant number of ways.

This chapter turns to the prospects for empirically testing specific cosmological multiverse theories such as the landscape multiverse scenario or cyclic multiverse models. The most commonly pursued strategy to extract concrete empirical consequences from specific multiverse theories is to regard them as predicting what typical multiverse inhabitants observe if the theories are correct, where "“typical” is spelled out as “randomly selected from some suitably chosen reference class.” I scrutinize a proposal by Srednicki and Hartle to treat the self-sampling assumption and the reference class to which it is applied as matters of empirical fact that are themselves amenable to empirical tests. Unfortunately, this proposal turns out to be incoherent. A much better idea, which coheres well with the intuitive motivation for the self-sampling assumption, is that we should make this assumption with respect to some reference class of observers precisely if our background information is consistent with us being any of those observers and neutral between them. I call this principle the “background information constraint” (BIC) and point out that it at least formally solves the problem of selecting the appropriate observer reference class.

Two models of galaxy formation were being investigated simultaneously on the 1970’s. The bottom-up model was championed by Peebles, and the top-down model by Zeldovich. At first, dark matter was not part of either model, but this effort to explain the origin of galaxies eventually stalled for both models the because the temperature fluctuations in the cosmic background radiation are too small to accommodate galaxy formation from baryons alone. At first massive neutrinos were introduced as dark matter, and when this failed to word, cold dark matter (CDM) was introduced. CDM forms early halos, and then baryons eventually fall into these halos. The first CDM computer models of galaxy formation were introduced by Melott and Shandarin and later developed by the “Gang of Four” (White, Davis, Efstathiou and Frenk). Eventually, the top-down and bottom-up models gracefully merged, and the concept of “biasing” became part of the final model.

The standard model of cosmology called LCDM has its origins in the work of great scientists including Einstein, Friedmann, Slipher, Hubble, Lemaitre, and Gamow. Lemaitre’s 1930s “Cosmic Egg” or “Primeval Nucleus” was the basis for the Big Bang model. In its new variant called LCDM, “L” represents the cosmological constant Lambda and “CDM” represents Cold Dark Matter. These two components, L and CDM, account for 95 percent of the mass–energy content of the Universe. Edwin Hubble correctly showed in the 1930s that galaxies are distributed on the largest scales in a homogeneous and isotropic way, but on a more local scale of 300 million light-years Hubble failed to recognize significant inhomogeneities. Hubble and Humason validated the velocity–distance relation for galaxies and galaxy clusters demonstrating the expansion of the Universe. They did not call out how significant the velocity–distance relationship would become in our effort to determine the 3D structure in the galaxy distribution.

An overview is presented of the breakthroughs that led to the discovery of cosmic voids and supercluster structure in the galaxy distribution and of those who did the work. The first step was the introduction of the image intensified camera to observatories in Arizona and its early use in the spectroscopy of galaxies. After a sufficient number of galaxy redshifts were collected, 3D maps of the local Universe were created. These maps revealed the dramatic structure including cosmic voids. Next, theoretical models were proposed to explain the observed structure. This step included a face-off between bottom-up evolutionary models in the west and top-down models from the USSR. As the models matured, it was recognized that normal matter (baryons) were insufficient to explain the observed structure in the galaxy distribution and that dark matter was a necessary new constituent. In recent years, cosmic voids have become a tool for precision cosmology.