54 research outputs found
Extending BEAMS to incorporate correlated systematic uncertainties
New supernova surveys such as the Dark Energy Survey, Pan-STARRS and the LSST
will produce an unprecedented number of photometric supernova candidates, most
with no spectroscopic data. Avoiding biases in cosmological parameters due to
the resulting inevitable contamination from non-Ia supernovae can be achieved
with the BEAMS formalism, allowing for fully photometric supernova cosmology
studies. Here we extend BEAMS to deal with the case in which the supernovae are
correlated by systematic uncertainties. The analytical form of the full BEAMS
posterior requires evaluating 2^N terms, where N is the number of supernova
candidates. This `exponential catastrophe' is computationally unfeasible even
for N of order 100. We circumvent the exponential catastrophe by marginalising
numerically instead of analytically over the possible supernova types: we
augment the cosmological parameters with nuisance parameters describing the
covariance matrix and the types of all the supernovae, \tau_i, that we include
in our MCMC analysis. We show that this method deals well even with large,
unknown systematic uncertainties without a major increase in computational
time, whereas ignoring the correlations can lead to significant biases and
incorrect credible contours. We then compare the numerical marginalisation
technique with a perturbative expansion of the posterior based on the insight
that future surveys will have exquisite light curves and hence the probability
that a given candidate is a Type Ia will be close to unity or zero, for most
objects. Although this perturbative approach changes computation of the
posterior from a 2^N problem into an N^2 or N^3 one, we show that it leads to
biases in general through a small number of misclassifications, implying that
numerical marginalisation is superior.Comment: Resubmitted under married name Lochner (formally Knights). Version 3:
major changes, including a large scale analysis with thousands of MCMC
chains. Matches version published in JCAP. 23 pages, 8 figure
Towards the Future of Supernova Cosmology
For future surveys, spectroscopic follow-up for all supernovae will be
extremely difficult. However, one can use light curve fitters, to obtain the
probability that an object is a Type Ia. One may consider applying a
probability cut to the data, but we show that the resulting non-Ia
contamination can lead to biases in the estimation of cosmological parameters.
A different method, which allows the use of the full dataset and results in
unbiased cosmological parameter estimation, is Bayesian Estimation Applied to
Multiple Species (BEAMS). BEAMS is a Bayesian approach to the problem which
includes the uncertainty in the types in the evaluation of the posterior. Here
we outline the theory of BEAMS and demonstrate its effectiveness using both
simulated datasets and SDSS-II data. We also show that it is possible to use
BEAMS if the data are correlated, by introducing a numerical marginalisation
over the types of the objects. This is largely a pedagogical introduction to
BEAMS with references to the main BEAMS papers.Comment: Replaced under married name Lochner (formally Knights). 3 pages, 2
figures. To appear in the Proceedings of 13th Marcel Grossmann Meeting
(MG13), Stockholm, Sweden, 1-7 July 201
Bayesian estimation applied to multiple species
Observed data are often contaminated by undiscovered interlopers, leading to biased parameter estimation. Here we present BEAMS (Bayesian estimation applied to multiple species) which significantly improves on the standard maximum likelihood approach in the case where the probability for each data point being “pure” is known. We discuss the application of BEAMS to future type-Ia supernovae (SNIa) surveys, such as LSST, which are projected to deliver over a million supernovae light curves without spectra. The multiband light curves for each candidate will provide a probability of being Ia (pure) but the full sample will be significantly contaminated with other types of supernovae and transients. Given a sample of N supernovae with mean probability, ⟨P⟩, of being Ia, BEAMS delivers parameter constraints equal to N⟨P⟩ spectroscopically confirmed SNIa. In addition BEAMS can be simultaneously used to tease apart different families of data and to recover properties of the underlying distributions of those families (e.g. the type-Ibc and II distributions). Hence BEAMS provides a unified classification and parameter estimation methodology which may be useful in a diverse range of problems such as photometric redshift estimation or, indeed, any parameter estimation problem where contamination is an issue
Power-law Template for Infrared Point-source Clustering
We perform a combined fit to angular power spectra of unresolved infrared (IR) point sources from the Planck
satellite (at 217, 353, 545, and 857 GHz, over angular scales 100 ≾ ℓ ≾ 2200), the Balloon-borne Large-Aperture
Submillimeter Telescope (BLAST; 250, 350, and 500μm; 1000 ≾ ℓ ≾ 9000), and from correlating BLAST and Atacama Cosmology Telescope (ACT; 148 and 218 GHz) maps. We find that the clustered power over the range of angular scales and frequencies considered is well fitted by a simple power law of the form C^(clust)_ℓ ∝ ℓ^(-n) with n = 1.25 ± 0.06. While the IR sources are understood to lie at a range of redshifts, with a variety of dust properties, we find that the frequency dependence of the clustering power can be described by the square of a modified blackbody, ν^(β)B(ν, T_(eff)), with a single emissivity index β = 2.20 ± 0.07 and effective temperature T_(eff) = 9.7 K. Our predictions for the clustering amplitude are consistent with existing ACT and South Pole Telescope results at around 150 and 220 GHz, as is our prediction for the effective dust spectral index, which we find to be α_(150–220) = 3.68±0.07 between 150 and 220 GHz. Our constraints on the clustering shape and frequency dependence can be used to model the IR clustering as a contaminant in cosmic microwave background anisotropy measurements. The combined Planck and BLAST data also rule out a linear bias clustering model
The Atacama Cosmology Telescope: Cross Correlation with Planck maps
We present the temperature power spectrum of the Cosmic Microwave Background
obtained by cross-correlating maps from the Atacama Cosmology Telescope (ACT)
at 148 and 218 GHz with maps from the Planck satellite at 143 and 217 GHz, in
two overlapping regions covering 592 square degrees. We find excellent
agreement between the two datasets at both frequencies, quantified using the
variance of the residuals between the ACT power spectra and the ACTxPlanck
cross-spectra. We use these cross-correlations to calibrate the ACT data at 148
and 218 GHz, to 0.7% and 2% precision respectively. We find no evidence for
anisotropy in the calibration parameter. We compare the Planck 353 GHz power
spectrum with the measured amplitudes of dust and cosmic infrared background
(CIB) of ACT data at 148 and 218 GHz. We also compare planet and point source
measurements from the two experiments.Comment: 9 pages, 8 figure
Results from the Supernova Photometric Classification Challenge
We report results from the Supernova Photometric Classification Challenge
(SNPCC), a publicly released mix of simulated supernovae (SNe), with types (Ia,
Ibc, and II) selected in proportion to their expected rate. The simulation was
realized in the griz filters of the Dark Energy Survey (DES) with realistic
observing conditions (sky noise, point-spread function and atmospheric
transparency) based on years of recorded conditions at the DES site.
Simulations of non-Ia type SNe are based on spectroscopically confirmed light
curves that include unpublished non-Ia samples donated from the Carnegie
Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan
Digital Sky Survey-II (SDSS-II). A spectroscopically confirmed subset was
provided for training. We challenged scientists to run their classification
algorithms and report a type and photo-z for each SN. Participants from 10
groups contributed 13 entries for the sample that included a host-galaxy
photo-z for each SN, and 9 entries for the sample that had no redshift
information. Several different classification strategies resulted in similar
performance, and for all entries the performance was significantly better for
the training subset than for the unconfirmed sample. For the spectroscopically
unconfirmed subset, the entry with the highest average figure of merit for
classifying SNe~Ia has an efficiency of 0.96 and an SN~Ia purity of 0.79. As a
public resource for the future development of photometric SN classification and
photo-z estimators, we have released updated simulations with improvements
based on our experience from the SNPCC, added samples corresponding to the
Large Synoptic Survey Telescope (LSST) and the SDSS, and provided the answer
keys so that developers can evaluate their own analysis.Comment: accepted by PAS
Fisher Matrix Preloaded -- Fisher4Cast
The Fisher Matrix is the backbone of modern cosmological forecasting. We
describe the Fisher4Cast software: a general-purpose, easy-to-use, Fisher
Matrix framework. It is open source, rigorously designed and tested and
includes a Graphical User Interface (GUI) with automated LATEX file creation
capability and point-and-click Fisher ellipse generation. Fisher4Cast was
designed for ease of extension and, although written in Matlab, is easily
portable to open-source alternatives such as Octave and Scilab. Here we use
Fisher4Cast to present new 3-D and 4-D visualisations of the forecasting
landscape and to investigate the effects of growth and curvature on future
cosmological surveys. Early releases have been available at
http://www.cosmology.org.za since May 2008 with 750 downloads in the first
year. Version 2.2 is made public with this paper and includes a Quick Start
guide and the code used to produce the figures in this paper, in the hope that
it will be useful to the cosmology and wider scientific communities.Comment: 30 Pages, 15 figures. Minor revisions to match published version,
with some additional functionality described to match the current version
(2.2) of the code. Software available at http://www.cosmology.org.za. Usage,
structure and flow of the software, as well as tests performed are described
in the accompanying Users' Manua
Cosmological Parameters from Pre-Planck CMB Measurements
Recent data from the WMAP, ACT and SPT experiments provide precise
measurements of the cosmic microwave background temperature power spectrum over
a wide range of angular scales. The combination of these observations is well
fit by the standard, spatially flat LCDM cosmological model, constraining six
free parameters to within a few percent. The scalar spectral index, n_s =
0.9690 +/- 0.0089, is less than unity at the 3.6 sigma level, consistent with
simple models of inflation. The damping tail of the power spectrum at high
resolution, combined with the amplitude of gravitational lensing measured by
ACT and SPT, constrains the effective number of relativistic species to be
N_eff = 3.28 +/- 0.40, in agreement with the standard model's three species of
light neutrinos.Comment: 5 pages, 4 figure
The Atacama Cosmology Telescope: A Measurement of the Thermal Sunyaev-Zel'dovich Effect Using the Skewness of the CMB Temperature Distribution
We present a detection of the unnormalized skewness induced by the
thermal Sunyaev-Zel'dovich (tSZ) effect in filtered Atacama Cosmology Telescope
(ACT) 148 GHz cosmic microwave background temperature maps. Contamination due
to infrared and radio sources is minimized by template subtraction of resolved
sources and by constructing a mask using outlying values in the 218 GHz
(tSZ-null) ACT maps. We measure = -31 +- 6 \mu K^3 (measurement error
only) or +- 14 \mu K^3 (including cosmic variance error) in the filtered ACT
data, a 5-sigma detection. We show that the skewness is a sensitive probe of
sigma_8, and use analytic calculations and tSZ simulations to obtain
cosmological constraints from this measurement. From this signal alone we infer
a value of sigma_8= 0.79 +0.03 -0.03 (68 % C.L.) +0.06 -0.06 (95 % C.L.). Our
results demonstrate that measurements of non-Gaussianity can be a useful method
for characterizing the tSZ effect and extracting the underlying cosmological
information.Comment: 9 pages, 5 figures. Replaced with version accepted by Phys. Rev. D,
with improvements to the likelihood function and the IR source treatment;
only minor changes in the result
- …