Sparse Bayesian mass-mapping with uncertainties: hypothesis testing of structure

A crucial aspect of mass-mapping, via weak lensing, is quantification of the uncertainty introduced during the reconstruction process. Properly accounting for these errors has been largely ignored to date. We present results from a new method that reconstructs maximum a posteriori (MAP) convergence maps by formulating an unconstrained Bayesian inference problem with Laplace-type $\ell_1$-norm sparsity-promoting priors, which we solve via convex optimization. Approaching mass-mapping in this manner allows us to exploit recent developments in probability concentration theory to infer theoretically conservative uncertainties for our MAP reconstructions, without relying on assumptions of Gaussianity. For the first time these methods allow us to perform hypothesis testing of structure, from which it is possible to distinguish between physical objects and artifacts of the reconstruction. Here we present this new formalism, demonstrate the method on illustrative examples, before applying the developed formalism to two observational datasets of the Abel-520 cluster. In our Bayesian framework it is found that neither Abel-520 dataset can conclusively determine the physicality of individual local massive substructure at significant confidence. However, in both cases the recovered MAP estimators are consistent with both sets of data

Life, Death and Preferential Attachment

Scientific communities are characterized by strong stratification. The highly skewed frequency distribution of citations of published scientific papers suggests a relatively small number of active, cited papers embedded in a sea of inactive and uncited papers. We propose an analytically soluble model which allows for the death of nodes. This model provides an excellent description of the citation distributions for live and dead papers in the SPIRES database. Further, this model suggests a novel and general mechanism for the generation of power law distributions in networks whenever the fraction of active nodes is small.Comment: 5 pages, 2 figure

Geodynamic implications for zonal and meridional isotopic patterns across the northern Lau and North Fiji Basins

We present new Sr-Nd-Pb-Hf-He isotopic data for sixty-five volcanic samples from the northern Lau and North Fiji Basin. This includes forty-seven lavas obtained from forty dredge sites spanning an east-west transect across the Lau and North Fiji basins, ten ocean island basalt (OIB)-type lavas collected from seven Fijian islands, and eight OIB lavas sampled on Rotuma. For the first time we are able to map clear north-south and east-west geochemical gradients in 87Sr/86Sr across the northern Lau and North Fiji Basins: lavas with the most geochemically enriched radiogenic isotopic signatures are located in the northeast Lau Basin, while signatures of geochemical enrichment are diminished to the south and west away from the Samoan hotspot. Based on these geochemical patterns and plate reconstructions of the region, these observations are best explained by the addition of Samoa, Rurutu, and Rarotonga hotspot material over the past 4 Ma. We suggest that underplated Samoan material has been advected into the Lau Basin over the past ∼4 Ma. As the slab migrated west (and toward the Samoan plume) via rollback over time, younger and hotter (and therefore less viscous) underplated Samoan plume material was entrained. Thus, entrainment efficiency of underplated plume material was enhanced, and Samoan plume signatures in the Lau Basin became stronger as the trench approached the Samoan hotspot. The addition of subducted volcanoes to the Cook-Austral Volcanic Lineament material, first from the Rarotonga hotspot, then followed by the Rurutu hotspot, contributes to the extreme geochemical signatures observed in the northeast Lau Basin

The effect of magnetic fields on star cluster formation

We examine the effect of magnetic fields on star cluster formation by performing simulations following the self-gravitating collapse of a turbulent molecular cloud to form stars in ideal MHD. The collapse of the cloud is computed for global mass-to-flux ratios of infinity, 20, 10, 5 and 3, that is using both weak and strong magnetic fields. Whilst even at very low strengths the magnetic field is able to significantly influence the star formation process, for magnetic fields with plasma beta < 1 the results are substantially different to the hydrodynamic case. In these cases we find large-scale magnetically-supported voids imprinted in the cloud structure; anisotropic turbulent motions and column density structure aligned with the magnetic field lines, both of which have recently been observed in the Taurus molecular cloud. We also find strongly suppressed accretion in the magnetised runs, leading to up to a 75% reduction in the amount of mass converted into stars over the course of the calculations and a more quiescent mode of star formation. There is also some indication that the relative formation efficiency of brown dwarfs is lower in the strongly magnetised runs due to the reduction in the importance of protostellar ejections.Comment: 16 pages, 9 figures, 8 very pretty movies, MNRAS, accepted. Version with high-res figures + movies available from http://www.astro.ex.ac.uk/people/dprice/pubs/mcluster/index.htm

FSI simulations for explosions very near reinforced concrete structures

The analysis of explosives in contact or very near to reinforced concrete (RC) structures is an important aspect in the design of protective structures and vulnerability assessments. Although this remains a topic of high importance for defence, a more widespread interest has developed as civilian structures become the targets of terrorism. This type of assessment requires a robust simulation method for coupled fluid-structural interactions (FSI) which can handle the explosive detonation, air blast propagation, structural deformation, and damage evolution. This paper describes the application of a loose-coupling method which combines the FEFLO CFD code and SAIC’s CSD code for 3D numerical simulations of unconfined and semi-confined explosions near RC structures. This approach takes advantage of the unstructured tetrahedral mesh for the CFD and an embedded method for CSD structures inside the fluid domain. Comparisons of simulations with experiment provide validation, but also reveal some weaknesses of the method. A good agreement between simulation and experiment is found with moderate explosive loading. However, a severe explosive loading with confinement results in extensive damage to the structure which is difficult to reproduce in simulations

Fast emulation of anisotropies induced in the cosmic microwave background by cosmic strings

Cosmic strings are linear topological defects that may have been produced during symmetry-breaking phase transitions in the very early Universe. In an expanding Universe the existence of causally separate regions prevents such symmetries from being broken uniformly, with a network of cosmic string inevitably forming as a result. To faithfully generate observables of such processes requires computationally expensive numerical simulations, which prohibits many types of analyses. We propose a technique to instead rapidly emulate observables, thus circumventing simulation. Emulation is a form of generative modelling, often built upon a machine learning backbone. End-to-end emulation often fails due to high dimensionality and insufficient training data. Consequently, it is common to instead emulate a latent representation from which observables may readily be synthesised. Wavelet phase harmonics are an excellent latent representations for cosmological fields, both as a summary statistic and for emulation, since they do not require training and are highly sensitive to non-Gaussian information. Leveraging wavelet phase harmonics as a latent representation, we develop techniques to emulate string induced CMB anisotropies over a 7.2 degree field of view, with sub-arcminute resolution, in under a minute on a single GPU. Beyond generating high fidelity emulations, we provide a technique to ensure these observables are distributed correctly, providing a more representative ensemble of samples. The statistics of our emulations are commensurate with those calculated on comprehensive Nambu-Goto simulations. Our findings indicate these fast emulation approaches may be suitable for wide use in, e.g., simulation based inference pipelines. We make our code available to the community so that researchers may rapidly emulate cosmic string induced CMB anisotropies for their own analysis