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Register a new userLensing and Supernovae: Quantifying The Bias on the Dark Energy Equation of State
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Devdeep Sarkar
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The gravitational magnification and demagnification of Type Ia supernovae (SNe) modify their positions on the Hubble diagram, shifting the distance estimates from the underlying luminosity-distance relation. This can introduce a systematic uncertainty in the dark energy equation of state (EOS) estimated from SNe, although this systematic is expected to average away for sufficiently large data sets. Using mock SN samples over the redshift range $0 < z leq 1.7$ we quantify the lensing bias. We find that the bias on the dark energy EOS is less than half a percent for large datasets ($gtrsim$ 2,000 SNe). However, if highly magnified events (SNe deviating by more than 2.5$sigma$) are systematically removed from the analysis, the bias increases to $sim$ 0.8%. Given that the EOS parameters measured from such a sample have a 1$sigma$ uncertainty of 10%, the systematic bias related to lensing in SN data out to $z sim 1.7$ can be safely ignored in future cosmological measurements.
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Observation of thousands of type Ia supernovae should offer the most direct approach to probe the dark energy content of the universe. This will be undertaken by future large ground-based surveys followed by a space mission (SNAP/JDEM). We address the problem of extracting the cosmological parameters from the future data in a model independent approach, with minimal assumptions on the prior knowledge of some parameters. We concentrate on the comparison between a fiducial model and the fitting function and adress in particular the effect of neglecting (or not) the time evolution of the equation of state. We present a quantitative analysis of the bias which can be introduced by the fitting procedure. Such bias cannot be ignored as soon as the statistical errors from present data are drastically improved.
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