Reliable inference of exoplanet light curve parameters using deterministic and stochastic systematics models

Time-series photometry and spectroscopy of transiting exoplanets allow us to study their atmospheres. Unfortunately, the required precision to extract atmospheric information surpasses the design specifications of most general purpose instrumentation, resulting in instrumental systematics in the light curves that are typically larger than the target precision. Systematics must therefore be modelled, leaving the inference of light curve parameters conditioned on the subjective choice of models and model selection criteria. This paper aims to test the reliability of the most commonly used systematics models and model selection criteria. As we are primarily interested in recovering light curve parameters rather than the favoured systematics model, marginalisation over systematics models is introduced as a more robust alternative than simple model selection. This can incorporate uncertainties in the choice of systematics model into the error budget as well as the model parameters. Its use is demonstrated using a series of simulated transit light curves. Stochastic models, specifically Gaussian processes, are also discussed in the context of marginalisation over systematics models, and are found to reliably recover the transit parameters for a wide range of systematics functions. None of the tested model selection criteria - including the BIC - routinely recovered the correct model. This means that commonly used methods that are based on simple model selection may underestimate the uncertainties when extracting transmission and eclipse spectra from real data, and low-significance claims using such techniques should be treated with caution. In general, no systematics modelling techniques are perfect; however, marginalisation over many systematics models helps to mitigate poor model selection, and stochastic processes provide an even more flexible approach to modelling instrumental systematics.Comment: 15 pages, 2 figures, published in MNRAS, typo in footnote eq correcte

Exploiting the full potential of photometric quasar surveys: Optimal power spectra through blind mitigation of systematics

We present optimal measurements of the angular power spectrum of the XDQSOz catalogue of photometric quasars from the Sloan Digital Sky Survey. These measurements rely on a quadratic maximum likelihood estimator that simultaneously measures the auto- and cross-power spectra of four redshift samples, and provides minimum-variance, unbiased estimates even at the largest angular scales. Since photometric quasars are known to be strongly affected by systematics such as spatially-varying depth and stellar contamination, we introduce a new framework of extended mode projection to robustly mitigate the impact of systematics on the power spectrum measurements. This technique involves constructing template maps of potential systematics, decorrelating them on the sky, and projecting out modes which are significantly correlated with the data. Our method is able to simultaneously process several thousands of nonlinearly-correlated systematics, and mode projection is performed in a blind fashion. Using our final power spectrum measurements, we find a good agreement with theoretical predictions, and no evidence for further contamination by systematics. Extended mode projection not only obviates the need for aggressive sky and quality cuts, but also provides control over the level of systematics in the measurements, enabling the search for small signals of new physics while avoiding confirmation bias.Comment: 13 pages, 8 figures. v2: version accepted by MNRAS. v3: systematics templates publicly available on www.earlyuniverse.org/code, no change to pape

Internal Robustness: systematic search for systematic bias in SN Ia data

A great deal of effort is currently being devoted to understanding, estimating and removing systematic errors in cosmological data. In the particular case of type Ia supernovae, systematics are starting to dominate the error budget. Here we propose a Bayesian tool for carrying out a systematic search for systematic contamination. This serves as an extension to the standard goodness-of-fit tests and allows not only to cross-check raw or processed data for the presence of systematics but also to pin-point the data that are most likely contaminated. We successfully test our tool with mock catalogues and conclude that the Union2.1 data do not possess a significant amount of systematics. Finally, we show that if one includes in Union2.1 the supernovae that originally failed the quality cuts, our tool signals the presence of systematics at over 3.8-sigma confidence level.Comment: 14 pages, 15 figures; matches version accepted for publication in MNRA

Systematics of 2+ states in semi-magic nuclei

We propose a simple systematics of low lying 2+ energy levels and electromagnetic transitions in semi-magic isotopic chains Z=28,50,82 and isotonic chains N=28,50,82,126. To this purpose we use a two-level pairing plus quadrupole Hamiltonian, within the spherical Quasiparticle Random Phase Approximation (QRPA). We derive a simple relation connecting the 2+ energy with the pairing gap and quadrupole-quadupole (QQ) interaction strength. It turns out that the systematics of energy levels and B(E2) values predicted by this simple model is fulfilled with a reasonable accuracy by all available experimental data. Both systematics suggest that not only active nucleons but also those filling closed shells play an important role

Spider Optimization: Probing the Systematics of a Large Scale B-Mode Experiment

Spider is a long-duration, balloon-borne polarimeter designed to measure large scale Cosmic Microwave Background (CMB) polarization with very high sensitivity and control of systematics. The instrument will map over half the sky with degree angular resolution in I, Q and U Stokes parameters, in four frequency bands from 96 to 275 GHz. Spider's ultimate goal is to detect the primordial gravity wave signal imprinted on the CMB B-mode polarization. One of the challenges in achieving this goal is the minimization of the contamination of B-modes by systematic effects. This paper explores a number of instrument systematics and observing strategies in order to optimize B-mode sensitivity. This is done by injecting realistic-amplitude, time-varying systematics in a set of simulated time-streams. Tests of the impact of detector noise characteristics, pointing jitter, payload pendulations, polarization angle offsets, beam systematics and receiver gain drifts are shown. Spider's default observing strategy is to spin continuously in azimuth, with polarization modulation achieved by either a rapidly spinning half-wave plate or a rapidly spinning gondola and a slowly stepped half-wave plate. Although the latter is more susceptible to systematics, results shown here indicate that either mode of operation can be used by Spider.Comment: 15 pages, 12 figs, version with full resolution figs available here http://www.astro.caltech.edu/~lgg/spider_front.ht

Probing the cosmic acceleration from combinations of different data sets

We examine in some detail the influence of the systematics in different data sets including type Ia supernova sample, baryon acoustic oscillation data and the cosmic microwave background information on the fitting results of the Chevallier-Polarski-Linder parametrization. We find that the systematics in the data sets does influence the fitting results and leads to different evolutional behavior of dark energy. To check the versatility of Chevallier-Polarski-Linder parametrization, we also perform the analysis on the Wetterich parametrization of dark energy. The results show that both the parametrization of dark energy and the systematics in data sets influence the evolutional behavior of dark energy.Comment: 15 pages, 5 figures and 1 table, major revision, delete bao a data, main results unchanged. jcap in press

Characterizing unknown systematics in large scale structure surveys

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data, we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.Comment: 24 pages, 6 figures; Expanded discussion of results, added figure 2; Version to be published in JCA