Synergy between the Large Synoptic Survey Telescope and the Square Kilometre Array

We provide an overview of the science benefits of combining information from the Square Kilometre Array (SKA) and the Large Synoptic Survey Telescope (LSST). We first summarise the capabilities and timeline of the LSST and overview its science goals. We then discuss the science questions in common between the two projects, and how they can be best addressed by combining the data from both telescopes. We describe how weak gravitational lensing and galaxy clustering studies with LSST and SKA can provide improved constraints on the causes of the cosmological acceleration. We summarise the benefits to galaxy evolution studies of combining deep optical multi-band imaging with radio observations. Finally, we discuss the excellent match between one of the most unique features of the LSST, its temporal cadence in the optical waveband, and the time resolution of the SKA.Comment: SKA Synergies Chapter, Advancing Astrophysics with the SKA (AASKA14) Conference, Giardini Naxos (Italy), June 9th-13th 201

Synergy between the Large Synoptic Survey Telescope and the Square Kilometre Array

We provide an overview of the science benefits of combining information from the Square Kilometre Array (SKA) and the Large Synoptic Survey Telescope (LSST). We first summarise the capabilities and timeline of the LSST and overview its science goals. We then discuss the science questions in common between the two projects, and how they can be best addressed by combining the data from both telescopes. We describe how weak gravitational lensing and galaxy clustering studies with LSST and SKA can provide improved constraints on the causes of the cosmological acceleration. We summarise the benefits to galaxy evolution studies of combining deep optical multi-band imaging with radio observations. Finally, we discuss the excellent match between one of the most unique features of the LSST, its temporal cadence in the optical waveband, and the time resolution of the SKA

Astroinformatics

As President of Commission on Astroinformatics and Astrostatistics of the International Astronomical Union, I welcome you to the first IAU Symposium on astroinformatics. This is not the first meeting in the field: the 26th meeting on ADASS (Astronomical Data Analysis Software and Systems) was held last weak in Trieste (and members of that group are here today), and this symposium has a strong heritage in workshops held in recent years at Caltech, Seattle, and Sydney. But this is the first time that the broader community of astronomers, through the IAU in collaboration of the giant IEEE organization has recognized this new field of study devoted to the challenges of Big Data and advanced methodology in astronomical research. This is the first time experts from around the world have gathered to share experiences and plan for the future. I have a comment to make. The typical IAU Symposium treats some well-established field of stars or galaxies or cosmology where the leading groups know each other well. But astroinformatics is such a young field, that we do not know each other and we do not know what ideas will emerge from this meeting. So I encourage each of us to have a creative approach to this meeting, work hard to talk to strangers, and help generate a community of scholars who can lead this field into the future

From Dark Matter to the Earth's Deep Interior: There and Back Again

This thesis is a two-way transfer of knowledge between cosmology and seismology, aiming to substantially advance imaging methods and uncertainty quantification in both fields. I develop a method using wavelets to simulate the uncertainty in a set of existing global seismic tomography images to assess the robustness of mantle plume-like structures. Several plumes are identified, including one that is rarely discussed in the seismological literature. I present a new classification of the most likely deep mantle plumes from my automated method, potentially resolving past discrepancies between deep mantle plumes inferred by visual analysis of tomography models and other geophysical data. Following on from this, I create new images of the upper-most mantle and their associated uncertainties using a sparsity-promoting wavelet prior and an advanced probabilistic inversion scheme. These new images exhibit the expected tectonic features such as plate boundaries and continental cratons. Importantly, the uncertainties obtained are physically reasonable and informative, in that they reflect the heterogenous data distribution and also highlight artefacts due to an incomplete forward model. These inversions are a first step towards building a fully probabilistic upper-mantle model in a sparse wavelet basis. I then apply the same advanced probabilistic method to the problem of full-sky cosmological mass-mapping. However, this is severely limited by the computational complexity of high-resolution spherical harmonic transforms. In response to this, I use, for the first time in cosmology, a trans-dimensional algorithm to build galaxy cluster-scale mass-maps. This new approach performs better than the standard mass-mapping method, with the added benefit that uncertainties are naturally recovered. With more accurate mass-maps and uncertainties, this method will be a valuable tool for cosmological inference with the new high-resolution data expected from upcoming galaxy surveys, potentially providing new insights into the interactions of dark matter particles in colliding galaxy cluster systems

Bayesian Variational Regularisation for Dark Matter Reconstruction with Uncertainty Quantification

Despite the great wealth of cosmological knowledge accumulated since the early 20th century, the nature of dark-matter, which accounts for ~85% of the matter content of the universe, remains illusive. Unfortunately, though dark-matter is scientifically interesting, with implications for our fundamental understanding of the Universe, it cannot be directly observed. Instead, dark-matter may be inferred from e.g. the optical distortion (lensing) of distant galaxies which, at linear order, manifests as a perturbation to the apparent magnitude (convergence) and ellipticity (shearing). Ensemble observations of the shear are collected and leveraged to construct estimates of the convergence, which can directly be related to the universal dark-matter distribution. Imminent stage IV surveys are forecast to accrue an unprecedented quantity of cosmological information; a discriminative partition of which is accessible through the convergence, and is disproportionately concentrated at high angular resolutions, where the echoes of cosmological evolution under gravity are most apparent. Capitalising on advances in probability concentration theory, this thesis merges the paradigms of Bayesian inference and optimisation to develop hybrid convergence inference techniques which are scalable, statistically principled, and operate over the Euclidean plane, celestial sphere, and 3-dimensional ball. Such techniques can quantify the plausibility of inferences at one-millionth the computational overhead of competing sampling methods. These Bayesian techniques are applied to the hotly debated Abell-520 merging cluster, concluding that observational catalogues contain insufficient information to determine the existence of dark-matter self-interactions. Further, these techniques were applied to all public lensing catalogues, recovering the then largest global dark-matter mass-map. The primary methodological contributions of this thesis depend only on posterior log-concavity, paving the way towards a, potentially revolutionary, complete hybridisation with artificial intelligence techniques. These next-generation techniques are the first to operate over the full 3-dimensional ball, laying the foundations for statistically principled universal dark-matter cartography, and the cosmological insights such advances may provide

Assessing the performance of Digital Micromirror Devices for use in space-based multi-object spectrometers

A current need in space-based instrumentation is a reconfigurable slit mask. Several techniques for slit masks have been employed for ground-based astronomical spectrographs. These ground-based instruments have used large discrete components, which are impractical for remote operation in space-based deployment. The Texas Instruments\u27 Digital Micromirror Device (DMD) was originally conceived purely for display purposes, but is a viable candidate to be use as a slit mask in a space-based multi-object spectrograph (MOS). The Integrated Circuit (IC) manufacturing industry has enabled the robust integration of both silicon transistors and Micro-Electrical Mechanical Systems (MEMS) optical components into a very reliable monolithic chip (the DMD). The focus of this work was in three areas that addressed the suitability of proposing DMDs for future space missions. The DMDs were optically characterized to assess their utility in a spectrograph. The DMDs were also cooled in a liquid nitrogen dewar to determine their minimum operating temperature. The low temperature tests indicated that the DMD can operate to temperatures as low as 130 K. In addition, several DMDs were irradiated with high-energy protons at the LBNL 88 Cyclotron to determine how robust the devices are to ionizing radiation (protons). The radiation testing results indicate that DMDs would survive medium to long duration space missions with full operability. Based on preliminary tests in these three areas, the DMD should be considered as an excellent candidate for deployment in future space missions

The habitable exoplanet observatory (HabEx) mission concept study interim report

For the first time in human history, technologies have matured sufficiently to enable a mission capable of discovering and characterizing habitable planets like Earth orbiting sunlike stars other than the Sun. At the same time, such a platform would enable unique science not possible from ground-based facilities. This science is broad and exciting, ranging from new investigations of our own solar system to a full range of astrophysics disciplines. The Habitable Exoplanet Observatory, or HabEx, is one of four studies currently being undertaken by NASA in preparation for the 2020 Astrophysics Decadal Survey. HabEx has been designed to be the Great Observatory of the 2030s, with community involvement through a competed and funded Guest Observer (GO) program. This interim report describes the HabEx baseline concept, which is a space-based 4-meter diameter telescope mission concept with ultraviolet (UV), optical, and near-infrared (near-IR) imaging and spectroscopy capabilities. More information on HabEx can be found at https://www.jpl.nasa.gov/habexPublished versio