Adiabaticity and the Fate of Non-Gaussianities: The Trispectrum and Beyond

Extending the analysis of [1011.4934] beyond the bispectrum, we explore the superhorizon generation of local non-gaussianities and their subsequent approach to adiabaticity. Working with a class of two field models of inflation with potentials amenable to treatment with the delta N formalism we find that, as is the case for f_{NL}^{local}, the local trispectrum parameters tau_{NL} and g_{NL} are exponentially driven toward values which are slow roll suppressed if the fluctuations are driven into an adiabatic mode by a phase of effectively single field inflation. We argue that general considerations should ensure that a similar behavior will hold for the local forms of higher point correlations as well.Comment: v3: Updated to match published version, minor corrections throughout, 17 pages; v2: Corrected counting of higher order non-linearity parameters, added references, updated formatting, conclusions unchanged, 16 pages; v1: 16 page

Non-Gaussianities in Multifield Inflation: Superhorizon Evolution, Adiabaticity, and the Fate of fnl

We explore the superhorizon generation of large fnl of the local form in two field inflation. We calculate the two- and three-point observables in a general class of potentials which allow for an analytic treatment using the delta N formalism. Motivated by the conservation of the curvature perturbation outside the horizon in the adiabatic mode and also by the observed adiabaticity of the power spectrum, we follow the evolution of fnl^{local} until it is driven into the adibatic solution by passing through a phase of effectively single field inflation. We find that although large fnl^{local} may be generated during inflation, such non-gaussianities are transitory and will be exponentially damped as the cosmological fluctuations approach adiabaticity.Comment: v3: Typos corrected, minor changes to match published version, references added, 18 pages, 1 figure. v2: Changed sign of fnl to match WMAP convention, minor changes throughout, references added, 18 pages, 1 figure. v1: 17 pages, 1 figur

Machine Learning Classification of SDSS Transient Survey Images

We show that multiple machine learning algorithms can match human performance in classifying transient imaging data from the Sloan Digital Sky Survey (SDSS) supernova survey into real objects and artefacts. This is a first step in any transient science pipeline and is currently still done by humans, but future surveys such as the Large Synoptic Survey Telescope (LSST) will necessitate fully machine-enabled solutions. Using features trained from eigenimage analysis (principal component analysis, PCA) of single-epoch g, r and i-difference images, we can reach a completeness (recall) of 96 per cent, while only incorrectly classifying at most 18 per cent of artefacts as real objects, corresponding to a precision (purity) of 84 per cent. In general, random forests performed best, followed by the k-nearest neighbour and the SkyNet artificial neural net algorithms, compared to other methods such as na\"ive Bayes and kernel support vector machine. Our results show that PCA-based machine learning can match human success levels and can naturally be extended by including multiple epochs of data, transient colours and host galaxy information which should allow for significant further improvements, especially at low signal-to-noise.Comment: 14 pages, 8 figures. In this version extremely minor adjustments to the paper were made - e.g. Figure 5 is now easier to view in greyscal

First On-Sky High Contrast Imaging with an Apodizing Phase Plate

We present the first astronomical observations obtained with an Apodizing Phase Plate (APP). The plate is designed to suppress the stellar diffraction pattern by 5 magnitudes from 2-9 lambda/D over a 180 degree region. Stellar images were obtained in the M' band (4.85 microns) at the MMTO 6.5m telescope, with adaptive wavefront correction made with a deformable secondary mirror designed for low thermal background observations. The measured PSF shows a halo intensity of 0.1% of the stellar peak at 2 lambda/D (0.36 arcsec), tapering off as r^{-5/3} out to radius 9 lambda/D. Such a profile is consistent with residual errors predicted for servo lag in the AO system. We project a 5 sigma contrast limit, set by residual atmospheric fluctuations, of 10.2 magnitudes at 0.36 arcsec separation for a one hour exposure. This can be realised if static and quasi-static aberrations are removed by differential imaging, and is close to the sensitivity level set by thermal background photon noise for target stars with M'>3. The advantage of using the phase plate is the removal of speckle noise caused by the residuals in the diffraction pattern that remain after PSF subtraction. The APP gives higher sensitivity over the range 2-5 lambda/D compared to direct imaging techniques.Comment: 22 pages, 5 figures, 1 table, ApJ accepte