A Monte Carlo Approach to Evolution of the Far-Infrared Luminosity Function with BLAST

We constrain the evolution of the rest-frame far-infrared (FIR) luminosity function out to high redshift, by combining several pieces of complementary information provided by the deep Balloon-borne Large-Aperture Submillimeter Telescope surveys at 250, 350 and 500 micron, as well as other FIR and millimetre data. Unlike most other phenomenological models, we characterise the uncertainties in our fitted parameters using Monte Carlo Markov Chains. We use a bivariate local luminosity function that depends only on FIR luminosity and 60-to-100 micron colour, along with a single library of galaxy spectral energy distributions indexed by colour, and apply simple luminosity and density evolution. We use the surface density of sources, Cosmic Infrared Background (CIB) measurements and redshift distributions of bright sources, for which identifications have been made, to constrain this model. The precise evolution of the FIR luminosity function across this crucial range has eluded studies at longer wavelengths (e.g., using SCUBA and MAMBO) and at shorter wavelengths (e.g., Spitzer), and should provide a key piece of information required for the study of galaxy evolution. Our adoption of Monte Carlo methods enables us not only to find the best-fit evolution model, but also to explore correlations between the fitted parameters. Our model-fitting approach allows us to focus on sources of tension coming from the combination of data-sets. We specifically find that our choice of parameterisation has difficulty fitting the combination of CIB measurements and redshift distribution of sources near 1 mm. Existing and future data sets will be able to dramatically improve the fits, as well as break strong degeneracies among the models. [abridged]Comment: 20 pages, 14 figures, accepted to MNRA

Systematic effects on dark energy from 3D weak shear

We present an investigation into the potential effect of systematics inherent in multi-band wide field surveys on the dark energy equation of state determination for two 3D weak lensing methods. The weak lensing methods are a geometric shear-ratio method and 3D cosmic shear. The analysis here uses an extension of the Fisher matrix framework to jointly include photometric redshift systematics, shear distortion systematics and intrinsic alignments. We present results for DUNE and Pan-STARRS surveys. We show that assuming systematic parameters are fixed, but possibly biased, results in potentially large biases in dark energy parameters. We quantify any potential bias by defining a Bias Figure of Merit. We also show the effect on the dark energy Figure of Merit of marginalising over each systematic parameter individually. We find that the largest effect on the Figure of Merit comes from uncertainty in the photometric redshift systematic parameters. These can reduce the Figure of Merit by up to a factor of 2 to 4 in both 3D weak lensing methods, if no informative prior on the systematic parameters is applied. Shear distortion systematics have a smaller overall effect. Intrinsic alignment effects can reduce the Figure of Merit by up to a further factor of 2. This, however, is a worst case scenario. By including prior information on systematic parameters the Figure of Merit can be recovered to a large extent. We conclude that, as a rule of thumb, given a realistic current understanding of intrinsic alignments and photometric redshifts, then including all three primary systematic effects reduces the Figure of Merit by at most a factor of 2, but that in reality this factor should be much less. [abridged]Comment: 20 pages, 11 figures, submitted to MNRA

From cosmic voids to collapsed structures: HPC methods for Astrophysics and Cosmology

Computational methods, software development and High Performance Computing awareness are of ever-growing importance in Astrophysics and Cosmology. In this context, the additional challenge comes from the impossibility of reproducing experiments in the controlled environment of a laboratory, making simulations unavoidable for testing theoretical models. In this work I present a quite heterogeneous ensemble of projects we have performed in the context of simulations of the large scale structure of the Universe. The connection being the development and usage of original computational tools for the analysis and post-processing of simulated data. In the first part of this manuscript I report on the efforts to develop a consistent theory for the size function of cosmic voids detected in biased tracers of the density field. Upcoming large scale surveys will map the distribution of galaxies with unprecedented detail and up to depths never reached before. Thanks to these large datasets, the void size function is expected to become a powerful statistics to infer the geometrical properties of space-time. In spite of this, the existing theoretical models are not capable of describing correctly the distribution of voids detected, neither in unbiased nor in biased simulated tracers. We have improved the void selection procedure, by developing an algorithm that redefines the void ridges and, consequently, their radii. By applying this algorithm, we validate the volume conserving model of the void size function on a set of unbiased simulated density field tracers. We highlight the difference in the internal structure between voids selected in this way and those identified by the popular VIDE void finder. We also extend the validation of the model to the case of biased tracers. We find that a relation exists between the tracer used to sample the underlying dark matter density field and its unbiased counterpart. Moreover, we demonstrate that, as long as this relation is accounted for, the size function is a viable approach for studying cosmology with voids. Finally, by parameterising the size function in terms of the linear effective bias of tracers, we perform an additional step towards analysing cosmic voids in real surveys. The proposed size function model has been accurately calibrated on halo catalogues, and used to validate the possibility to provide forecasts on the cosmological constraints, namely on the matter density parameter, $Omega_M$, and on the normalisation of the linear matter power spectrum, $sigma_8$. oindent The second part of the manuscript is focused in presenting the hybrid C++/python implementation of ScamPy, our empirical framework for ``painting'' galaxies on top of the Dark Matter Halo/Sub-Halo hierarchy obtained from N-body simulations. Our confidence on the reliability of N-body Dark Matter-only simulations stands on the argument that the evolution of the non-collisional matter component only depends on the effect of gravity and on the initial conditions. The formation and evolution of the luminous component (i.e. galaxies and intergalactic baryonic matter) are far from being understood at the same level as the dark matter. Among the possible approaches for modelling the luminous component, empirical methods are designed to reproduce observable properties of a target (observed) population of objects at a given moment of their evolution. With respect to ab initio approaches (i.e. hydrodynamical N-body simulations and semi-analytical models), empirical methods are typically cheaper in terms of computational power and are by design more reliable in the high redshift regime. Building an empirical model of galaxy occupation requires to define the hosted-object/hosting-halo connection for associating to the underlying DM distribution its baryonic counterpart. The method we use is based on the sub-halo clustering and abundance matching (SCAM) scheme which requires observations of the 1- and 2-point statistics of the target population we want to reproduce. This method is particularly tailored for high redshift studies and thereby relies on the observed high-redshift galaxy luminosity functions and correlation properties. The core functionalities of ScamPy are written in C++ and exploit Object Oriented Programming, with a wide use of polymorphism, to achieve flexibility and high computational efficiency. In order to have an easily accessible interface, all the libraries are wrapped in python and provided with an extensive documentation. I present the theoretical background of the method and provide a detailed description of the implemented algorithms. We have validated the key components of the framework, demonstrating it produces scientifically meaningful results with satisfying performances. Finally, we have tested the framework in a proof-of-concept application at high-redshift. Namely, we paint a mock galaxy population on top of high resolution dark matter only simulation, mimicking the luminosity and clustering properties of high-redshift Lyman Break Galaxies retrieved from recent literature. We use these mock galaxies to infer the ionizing radiation spatial and statistical distribution during the period of Reionization

Galaxy alignments: An overview

The alignments between galaxies, their underlying matter structures, and the cosmic web constitute vital ingredients for a comprehensive understanding of gravity, the nature of matter, and structure formation in the Universe. We provide an overview on the state of the art in the study of these alignment processes and their observational signatures, aimed at a non-specialist audience. The development of the field over the past one hundred years is briefly reviewed. We also discuss the impact of galaxy alignments on measurements of weak gravitational lensing, and discuss avenues for making theoretical and observational progress over the coming decade.Comment: 43 pages excl. references, 16 figures; minor changes to match version published in Space Science Reviews; part of a topical volume on galaxy alignments, with companion papers at arXiv:1504.05546 and arXiv:1504.0546

Conformational behaviour of amphiphilic molecules in aqueous solution and at a water/air interface: computational studies at the molecular level

Previous experimental studies have indicated that the amphiphilic graft co-polymer polynorbornene-g-poly(ethylene oxide) (PNB-g-PEO) undergoes interesting conformational behaviour when placed at a water/air interface. This polymer adopts different conformations depending upon surface concentration, as elucidated through neutron reflectometry measurements. The work in this thesis details the preparation for, and execution of atomistic molecular dynamics simulations of this system at a range of surface concentrations. Three commonly used water models were assessed for computational expense and accuracy in the reproduction of key experimental properties, particularly density. It was found that the TIP4P water model was the most appropriate, and was therefore used to generate a water/vapour interface configuration. The OPLS-AA force field was then examined in detail on the basis of ab initio structural optimisation calculations on 1,2-dimethoxyethane (DME), a model molecule for poly (ethylene oxide) (PEO). Torsion parameters for the 0-C-C-O and C-O-C-C dihedral potentials were fitted to these ab initio data in an attempt to obtain a force field capable of reproducing the conformational behaviour of DME in the bulk liquid as measured previously by experiment. Using this fitted force field, fully atomistic simulations of PNB-g'-PEO at the water/vapour interface were performed at a range of surface concentrations coinciding with the experimental study. Excellent agreement was found between simulated and experimental neutron reflectivity profiles for low surface concentrations. Agreement at higher concentrations was slightly poorer, but still much better than that obtained in a previous simulation study without explicit water. Four force fields were then compared in "simulations of a PEO chain in aqueous solution. Dihedral angle analysis was performed on these PEO chains and compared to the behaviour of the PEO side chains in PNB-g-PEO. Agreement with conformational populations was confirmed between the two studies, however the frequency of conformational transitions was found to differ significantly between the two sets of simulation

Supernova-driven Turbulence and Magnetic Field Amplification in Disk Galaxies

Supernovae are known to be the dominant energy source for driving turbulence in the interstellar medium. Yet, their effect on magnetic field amplification in spiral galaxies is still poorly understood. Analytical models based on the uncorrelated-ensemble approach predicted that any created field will be expelled from the disk before a significant amplification can occur. By means of direct simulations of supernova-driven turbulence, we demonstrate that this is not the case. Accounting for vertical stratification and galactic differential rotation, we find an exponential amplification of the mean field on timescales of 100Myr. The self-consistent numerical verification of such a "fast dynamo" is highly beneficial in explaining the observed strong magnetic fields in young galaxies. We, furthermore, highlight the importance of rotation in the generation of helicity by showing that a similar mechanism based on Cartesian shear does not lead to a sustained amplification of the mean magnetic field. This finding impressively confirms the classical picture of a dynamo based on cyclonic turbulence.Comment: 99 pages, 46 figures (in part strongly degraded), 8 tables, PhD thesis, University of Potsdam (2009). Resolve URN "urn:nbn:de:kobv:517-opus-29094" (e.g. via http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-29094) for a version with high-resolution figure

Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

PhD thesis submitted to the University of Manchester, School of Physics and Astronomy, August 2017. Abstract: This thesis presents a practical guide to applying shear measurements as a cosmological tool. We first present one of two science-ready galaxy shape catalogues from Year 1 of the Dark Energy Survey (DES Y1), which covers 1500 square degrees in four bands griz, with a median redshift of 0.59. We describe the shape measurement process implemented by the DES Y1 im3shape catalogue, which contains 21.9M high-quality r-band bulge/disc fits. In Chapter 3 a new suite of image simulations, referred to as hoopoe, are presented. The hoopoe dataset is tailored to DES Y1 and includes realistic blending, spatial masks and variation in the point spread function. We derive shear corrections, which we show are robust to changes in calibration method, galaxy binning and variance within the simulated dataset. Sources of systematic uncertainty in the simulation-based shear calibration are discussed, leading to a final estimate of the 1 sigma uncertainties in the residual multiplicative bias after calibration of 0.025. Chapter 4 describes an extension of the analysis on the hoopoe simulations into a detailed investigation of the impact of galaxy neighbours on shape measurement and shear cosmology. Four mechanisms by which neighbours can have a non-negligible influence on shear measurement are identified. These effects, if ignored, would contribute a net multiplicative bias of m ~ 0.03 - 0.09 in DES Y1, though the precise impact will depend on both the measurement code and the selection cuts applied. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude S8 = sigma_8 (Omega_m /0.3)^0.5 by 1.5 sigma towards low values. Finally, we use the hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the cosmological impact to be subdominant to statistical error at the current level of precision. Another major uncertainty in shear cosmology is the accuracy of our ensemble redshift distributions. Chapter 5 presents a numerical investigation into the combined constraining power of cosmic shear, galaxy clustering and their cross-correlation in DES Y1, and the potential for internal calibration of redshift errors. Introducing a moderate uniform bias into the redshift distributions used to model the weak lensing (WL) galaxies is shown to produce a > 2 sigma bias in S8. We demonstrate that this cosmological bias can be eliminated by marginalising over redshift error nuisance parameters. Strikingly, the cosmological constraint of the combined dataset is largely undiminished by the loss of prior information on the WL distributions. We demonstrate that this implicit self-calibration is the result of complementary degeneracy directions in the combined data. In Chapter 6 we present the preliminary results of an investigation into galaxy intrinsic alignments. Using the DES Y1 data, we show a clear dependence in alignment amplitude on galaxy type, in agreement with previous results. We subject these findings to a series of initial robustness tests. We conclude with a short overview of the work presented, and discuss prospects for the future