Cosmology

Abstract:

The structure of magnetic fields in galaxies remains poorly constrained, despite the importance of magnetism in the evolution of galaxies. Radio synchrotron and far-infrared (FIR) polarization and polarimetric observations are the best methods to measure galactic scale properties of magnetic fields in galaxies beyond the Milky Way. We use synthetic polarimetric observations of a simulated galaxy to identify and quantify the regions, scales, and interstellar medium (ISM) phases probed at FIR and radio wavelengths. Our studied suite of magnetohydrodynamical cosmological zoom-in simulations features high-resolutions (10 pc full-cell size) and multiple magnetization models. Our synthetic observations have a striking resemblance to those of observed galaxies. We find that the total and polarized radio emission extends to approximately double the altitude above the galactic disk (half-intensity disk thickness of h I radio ∼ h PI radio = 0.23 ± 0.03 kpc) relative to the total FIR and polarized emission that are concentrated in the disk midplane (h I FIR ∼ h PI FIR = 0.11 ± 0.01 kpc). Radio emission traces magnetic fields at scales of ≳300 pc, whereas FIR emission probes magnetic fields at the smallest scales of our simulations. These scales are comparable to our spatial resolution and well below the spatial resolution (<300 pc) of existing FIR polarimetric measurements. Finally, we confirm that synchrotron emission traces a combination of the warm neutral and cold neutral gas phases, whereas FIR emission follows the densest gas in the cold neutral phase in the simulation. These results are independent of the ISM magnetic field strength. The complementarity we measure between radio and FIR wavelengths motivates future multiwavelength polarimetric observations to advance our knowledge of extragalactic magnetism.

Abstract:

During the last decade, cosmological simulations have managed to reproduce realistic and morphologically diverse galaxies, spanning the Hubble sequence. Central to this success was a phenomenological calibration of the few included feedback processes, while glossing over higher complexity baryonic physics. This approach diminishes the predictive power of such simulations, preventing to further our understanding of galaxy formation. To tackle this fundamental issue, we investigate the impact of cosmic rays (CRs) and magnetic fields on the interstellar medium and the launching of outflows in a cosmological zoom-in simulation of a Milky Way-like galaxy. We find that including CRs decreases the stellar mass of the galaxy by a factor of 10 at high redshift and ∼4 at cosmic noon, leading to a stellar mass to halo mass ratio in good agreement with abundance matching models. Such decrease is caused by two effects: (i) a reduction of cold, high-density, star-forming gas, and (ii) a larger fraction of supernova (SN) events exploding at lower densities, where they have a higher impact. SN-injected CRs produce enhanced, multiphase galactic outflows, which are accelerated by CR pressure gradients in the circumgalactic medium of the galaxy. While the mass budget of these outflows is dominated by the warm ionized gas, warm neutral and cold gas phases contribute significantly at high redshifts. Importantly, our work shows that future JWST observations of galaxies and their multiphase outflows across cosmic time have the ability to constrain the role of CRs in regulating star formation.

Abstract:

Inflation is a highly favored theory for the early Universe. It is compatible with current observations of the cosmic microwave background and large scale structure and is a driver in the quest to detect primordial gravitational waves. It is also, given the current quality of the data, highly underdetermined with a large number of candidate implementations. We use a new method in symbolic regression to generate all possible simple scalar field potentials for one of two possible basis sets of operators. Treating these as single-field, slow-roll inflationary models we then score them with an information-theoretic metric ("minimum description length") that quantifies their efficiency in compressing the information in current data. We explore two possible priors on the parameter space of potentials, one related to the functions' structural complexity and one that uses a Katz back-off language model to prefer functions that may be theoretically motivated. This enables us to identify the inflaton potentials that optimally balance simplicity with accuracy at explaining current data, which may subsequently find theoretical motivation. Our exploratory study opens the door to extraction of fundamental physics directly from data, and may be augmented with more refined theoretical priors in the quest for a complete understanding of the early Universe.