Physics of non-Gaussian fields and the cosmological genus statistic

We report a technique to calculate the impact of distinct physical processes inducing non-Gaussianity on the cosmological density field. A natural decomposition of the cosmic genus statistic into an orthogonal polynomial sequence allows complete expression of the scale-dependent evolution of the morphology of large-scale structure, in which effects including galaxy bias, nonlinear gravitational evolution and primordial non-Gaussianity may be delineated. The relationship of this decomposition to previous methods for analysing the genus statistic is briefly considered and the following applications are made: i) the expression of certain systematics affecting topological measurements; ii) the quantification of broad deformations from Gaussianity that appear in the genus statistic as measured in the Horizon Run simulation; iii) the study of the evolution of the genus curve for simulations with primordial non-Gaussianity. These advances improve the treatment of flux-limited galaxy catalogues for use with this measurement and further the use of the genus statistic as a tool for exploring non-Gaussianity.Comment: AASTeX preprint, 24 pages, 8 figures, includes several improvements suggested by anonymous reviewe

Expanding Space: the Root of all Evil?

While it remains the staple of virtually all cosmological teaching, the concept of expanding space in explaining the increasing separation of galaxies has recently come under fire as a dangerous idea whose application leads to the development of confusion and the establishment of misconceptions. In this paper, we develop a notion of expanding space that is completely valid as a framework for the description of the evolution of the universe and whose application allows an intuitive understanding of the influence of universal expansion. We also demonstrate how arguments against the concept in general have failed thus far, as they imbue expanding space with physical properties not consistent with the expectations of general relativity.Comment: 8 pages, accepted for publication in PAS

Spectral diversity of Type Ia Supernovae

We use published spectroscopic and photometric data for 8 Type Ia supernovae to construct a dispersion spectrum for this class of object, showing their diversity over the wavelength range 3700A to 7100A. We find that the B and V bands are the spectral regions with the least dispersion, while the U band below 4100A is more diverse. Some spectral features such as the Si line at 6150A are also highly diverse. We then construct two objective measures of 'peculiarity' by (i) using the deviation of individual objects from the average SN Ia spectrum compared to the typical dispersion and (ii) applying principle component analysis. We demonstrate these methods on several SNe Ia that have previously been classified as peculiar.Comment: 8 pages, 8 figures, uses mn2e.cls, accepted for publication by MNRA

The Adventures of the Rocketeer: Accelerated Motion Under the Influence of Expanding Space

It is well known that interstellar travel is bounded by the finite speed of light, but on very large scales any rocketeer would also need to consider the influence of cosmological expansion on their journey. This paper examines accelerated journeys within the framework of Friedmann- Lemaitre-Robertson-Walker universes, illustrating how the duration of a fixed acceleration sharply divides exploration over interstellar and intergalactic distances. Furthermore, we show how the universal expansion increases the difficulty of intergalactic navigation, with small uncertainties in cosmological parameters resulting in significantly large deviations. This paper also shows that, contrary to simplistic ideas, the motion of any rocketeer is indistinguishable from Newtonian gravity if the acceleration is kept small.Comment: 9 pages, 7 figures, accepted for publication in PAS

Cosmological Radar Ranging in an Expanding Universe

While modern cosmology, founded in the language of general relativity, is almost a century old, the meaning of the expansion of space is still being debated. In this paper, the question of radar ranging in an expanding universe is examined, focusing upon light travel times during the ranging; it has recently been claimed that this proves that space physically expands. We generalize the problem into considering the return journey of an accelerating rocketeer, showing that while this agrees with expectations of special relativity for an empty universe, distinct differences occur when the universe contains matter. We conclude that this does not require the expansion of space to be a physical phenomenon, rather that we cannot neglect the influence of matter, seen through the laws of general relativity, when considering motions on cosmic scales.Comment: 6 Pages. To appear in MNRA

Clipping the Cosmos: The Bias and Bispectrum of Large Scale Structure

A large fraction of the information collected by cosmological surveys is simply discarded to avoid lengthscales which are difficult to model theoretically. We introduce a new technique which enables the extraction of useful information from the bispectrum of galaxies well beyond the conventional limits of perturbation theory. Our results strongly suggest that this method increases the range of scales where the relation between the bispectrum and power spectrum in tree-level perturbation theory may be applied, from k_max ~ 0.1 h/Mpc to ~ 0.7 h/Mpc. This leads to correspondingly large improvements in the determination of galaxy bias. Since the clipped matter power spectrum closely follows the linear power spectrum, there is the potential to use this technique to probe the growth rate of linear perturbations and confront theories of modified gravity with observation.Comment: 5 pages, 2 figures. To appear in Physical Review Letter

Topology of non-linear structure in the 2dF Galaxy Redshift Survey

We study the evolution of non-linear structure as a function of scale in samples from the 2dF Galaxy Redshift Survey, constituting over 221 000 galaxies at a median redshift of z=0.11. The two flux-limited galaxy samples, located near the southern galactic pole and the galactic equator, are smoothed with Gaussian filters of width ranging from 5 to 8 Mpc/h to produce a continuous galaxy density field. The topological genus statistic is used to measure the relative abundance of overdense clusters to void regions at each scale; these results are compared to the predictions of analytic theory, in the form of the genus statistic for i) the linear regime case of a Gaussian random field; and ii) a first-order perturbative expansion of the weakly non-linear evolved field. The measurements demonstrate a statistically significant detection of an asymmetry in the genus statistic between regions corresponding to low- and high-density volumes of the universe. We attribute the asymmetry to the non-linear effects of gravitational evolution and biased galaxy formation, and demonstrate that these effects evolve as a function of scale. We find that neither analytic prescription satisfactorily reproduces the measurements, though the weakly non-linear theory yields substantially better results in some cases, and we discuss the potential explanations for this result.Comment: 13 pages, matching proof to be published in MNRAS; new version adds reference and corrects figure

Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because a) standard assumptions for machine-learned model selection procedures break down and b) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting (IW), co-training (CT), and active learning (AL). We argue that AL---where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up---is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and OGLE, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply active learning to classify variable stars in the ASAS survey, finding dramatic improvement in our agreement with the ACVS catalog, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.Comment: 43 pages, 11 figures, submitted to Ap

Constraints on the Generalized Chaplygin Gas Model from Gamma-Ray Bursts

We study the Generalized Chaplygin gas model (GCGM) using Gamma-ray bursts as cosmological probes. In order to avoid the so-called circularity problem we use cosmology-independent data set and Bayesian statistics to impose constraints on the model parameters. We observe that a negative value for the parameter $\alpha$ is favoured if we adopt a flat Universe and the estimated value of the parameter $H_{0}$ is lower than that found in literature.Comment: 10 pages, 29 figures, accepted for publication in Physics Letters