The Square Kilometre Array (SKA)

Abstract:

Familiar concepts in physics, such as Lorentz symmetry, are expected to be broken at energies approaching the Planck energy scale as predicted by several quantum-gravity theories. However, such very large energies are unreachable by current experiments on Earth. Current and future Cherenkov telescope facilities may have the capability to measure the accumulated deformation from Lorentz symmetry for photons traveling over large distances via energy-dependent time delays. One of the best natural laboratories to test Lorentz Invariance Violation~(LIV) signatures are Gamma-ray bursts~(GRBs). The calculation of time delays due to the LIV effect depends on the cosmic expansion history. In almost all previous works calculating time lags due to the LIV effect, the standard $\Lambda$CDM (or concordance) cosmological model is assumed. In this paper, we investigate whether the LIV signature is significantly different when assuming alternatives to the $\Lambda$CDM cosmological model. Specifically, we consider cosmological models with a non-trivial dark-energy equation of state ($w \neq -1$), such as the standard Chevallier-Polarski-Linder~(CPL) parameterization, the quadratic parameterization of the dark-energy equation of state, and the Pade parameterizations. We find that the relative difference in the predicted time lags is small, of the order of at most a few percent, and thus likely smaller than the systematic differences of possible measurements currently or in the near future.

Abstract:

U-band observations with the LSST have yet to be fully optimized in cadence. The straw man survey design is a simple coverage of the medium-deep-fast survey. Here we argue that deep coverage of the four deep drilling fields (XMM-LSS, ECDFS, ELAIS-S1 and COSMOS) has a much higher scientific return, given that these are also the target of the Southern Hemisphere's Square Kilometer Array Pathfinder, the MeerKAT specifically, deep radio observations.

Abstract:

The Large Synoptic Survey Telescope (LSST) will enable revolutionary studies of galaxies, dark matter, and black holes over cosmic time. The LSST Galaxies Science Collaboration has identified a host of preparatory research tasks required to leverage fully the LSST dataset for extragalactic science beyond the study of dark energy. This Galaxies Science Roadmap provides a brief introduction to critical extragalactic science to be conducted ahead of LSST operations, and a detailed list of preparatory science tasks including the motivation, activities, and deliverables associated with each. The Galaxies Science Roadmap will serve as a guiding document for researchers interested in conducting extragalactic science in anticipation of the forthcoming LSST era.

Abstract:

We analyse the velocity dispersion properties of 472 z~0.9 star-forming galaxies observed as part of the KMOS Redshift One Spectroscopic Survey (KROSS). The majority of this sample is rotationally dominated (83 +/- 5% with v_C/sigma_0 > 1) but also dynamically hot and highly turbulent. After correcting for beam smearing effects, the median intrinsic velocity dispersion for the final sample is sigma_0 = 43.2 +/- 0.8 km/s with a rotational velocity to dispersion ratio of v_C/sigma_0 = 2.6 +/- 0.1. To explore the relationship between velocity dispersion, stellar mass, star formation rate and redshift we combine KROSS with data from the SAMI survey (z~0.05) and an intermediate redshift MUSE sample (z~0.5). While there is, at most, a weak trend between velocity dispersion and stellar mass, at fixed mass there is a strong increase with redshift. At all redshifts, galaxies appear to follow the same weak trend of increasing velocity dispersion with star formation rate. Our results are consistent with an evolution of galaxy dynamics driven by disks that are more gas rich, and increasingly gravitationally unstable, as a function of increasing redshift. Finally, we test two analytic models that predict turbulence is driven by either gravitational instabilities or stellar feedback. Both provide an adequate description of the data, and further observations are required to rule out either model.