Star formation is regulated through a variety of feedback processes. In this study, we treat feedback by metal injection and a UV background as well as by X-ray irradiation. Our aim is to investigate whether star formation is significantly affected when the ISM of a proto-galaxxy enjoys different metallicities and when a star forming cloud resides in the vicinity of a strong X-ray source. We perform cosmological Enzo simulations with a detailed treatment of non-zero metallicity chemistry and thermal balance. We also perform FLASH simulations with embedded Lagrangian sink particles of a collapsing molecular cloud near a massive, 107 M⊙, black hole that produces X-ray radiation.

We find that a multi-phase ISM forms for metallicites as small as 10−4 Solar at z = 6, with higher (10−2Z⊙) metallicities supporting a cold (<100 K) and dense (>103 cm−3) phase at higher (z = 20) redshift. A star formation recipe based on the presence of a cold dense phase leads to a self-regulating mode in the presence of supernova and radiation feedback. We also find that when there is strong X-ray feedback a collapsing cloud fragments into larger clumps whereby fewer but more massive protostellar cores are formed. This is a consequence of the higher Jeans mass in the warm (50 K, due to ionization heating) molecular gas. Accretion processes dominate the mass function and a near-flat, non-Salpeter IMF results.

We review an approach to observation-theory comparisons we call “Taste-Testing.” In this approach, synthetic observations are made of numerical simulations, and then both real and synthetic observations are “tasted” (compared) using a variety of statistical tests. We first lay out arguments for bringing theory to observational space rather than observations to theory space. Next, we explain that generating synthetic observations is only a step along the way to the quantitative, statistical, taste tests that offer the most insight. We offer a set of examples focused on polarimetry, scattering and emission by dust, and spectral-line mapping in star-forming regions. We conclude with a discussion of the connection between statistical tests used to date and the physics we seek to understand. In particular, we suggest that the “lognormal” nature of molecular clouds can be created by the interaction of many random processes, as can the lognormal nature of the IMF, so that the fact that both the “Clump Mass Function” (CMF) and IMF appear lognormal does not necessarily imply a direct relationship between them.

In this paper I relate progress in the simulation of star formation to a remarkable early (1962) paper by Fowler and Hoyle who analyzed star formation in terms of the relevant energies starting from the formation of a large (100 pc) cloud and ending with the final mass distribution of the stars. The way in which modern simulations have clarified and corrected the Fowler-Hoyle picture, and areas where we could improve our simulations, are discussed.

Advances in available computing facilities, judiciously employed by our colleagues, have undoubtedly enhanced our understanding of the processes by which stars (and planets) form, from very diffuse gas to something you could almost live around. Nevertheless we remain very far from being able to describe (let alone explain) what is going on in many cases. And this is likely to remain true even as Moore's Law growth begins to hit its head against energy and power considerations. A large fraction of long-standing questions appear to have honest answers of the general form, “yes and no”, “all of the above”, or “some of them are and some of them aren't”. This includes many of my favorites, like triggering, formation of binary populations, and the role of magnetic fields. Rather few questions have actually been retired from the universe of discourse in recent years.