AbstractSupernovae are important probes of cosmology. In 1999, Type Ia Supernovae (SNeIa) provided the first evidence for the accelerating expansion of the Universe (Riesset al., 1998, Perlmutter et al., 1999), and since then there have been many wide-field SN surveys with the scope of increasing the number of observed SNe, thus improving the constraints on cosmological parameters. Among these SN surveys,the Dark Energy Survey (DES) and the planned Large Synoptic Survey Telescope(LSST) will increase the number of available SNe Ia respectively to ' 3000 and ∼105 (possibly ∼ 106) in the coming decade. Weak gravitational lensing effects willthen become important for these new surveys.
Weak gravitational lensing have different effects on the distance modulus measurements of SNe. Firstly, it introduces a non-Gaussian scatter on the distance moduli of SNe Ia, and this effect increases as a function of redshift. The non-Gaussian weak lensing distribution can also introduce a bias on the cosmological parameter values recovered by fitting the Hubble diagram. Secondly, it introduces spatial correlations on the magnitudes of close SN pairs, with angular separation of the order of arcminutes. Weak lensing of SNe can also be used to probe the growth of structures along the line-of-sight, giving further constraints on cosmological parameters like σ8 and Ωm.
In Chapter 2, we present our results on the fit of the Hubble diagram from the
Jointed Light-curve Analysis sample (JLA, Betoule et al. 2014) including weak lensing and peculiar velocities, the latter introducing an extra dispersion on the distance modulus measurements of low redshift SNe. We give constraints on the cosmological parameters when fitting for the the first four moments of the weak lensing distribution together with the variance induced by peculiar velocities. We test our method via numerical simulations and we find Ωm=0.274±0.013 and σ8=0.44+0.63-0.44 when fitting the JLA sample. We also apply the Kernel Density Estimation technique to reduce the problem of biased estimates of the moments measured on sparse data sample, and a boot-strap re-sampling method when computing the covariance between the moments.
In Chapter 3 we propose to measure the two-point magnitude correlation function from SN data and compare such measurements to theoretical expectations. As available data sample appear to be insufficient to detect this weak correlation (we report a tentative detection with the JLA sample), we predict measurements with current (DES) and future (LSST) SN surveys, finding that the LSST should be able to detect such correlations at 6σ level of confidence (15,000 SNe over 70 deg2 and assuming an intrinsic scatter of 0.15 magnitudes). DES (deep field) is expected to detect a cross-correlation between the Hubble residuals and the foreground galaxies at 12σ (integrated up to 9 arcminutes of separation and assuming an intrinsic scatter of 0.15 magnitudes), taking advantage of the higher galaxy density on the sky, while LSST should detect the same cross-correlation with signal-to-noise ⪆ 100. We also give forecasts on cosmological parameters when fitting Ωm and σ8 from the twopoint magnitude auto-correlation function, i.e. we can achieve a 25% measurement of σ8 from LSST (assuming 0.15 magnitudes of intrinsic scatter and applying a Gaussian prior on the matter density parameter).
In Chapter 4, we investigate Type Ic Superluminous Supernovae (SLSNe Ic) as a new class of potential standard candles, which appear to be standardisable in their peak magnitudes with a scatter of only 0.2 – 0.3 magnitudes. Moreover, their exceptional peak magnitude (up to 100 times brighter than SNe Ia) allows them to be discovered to redshift ∼ 3, shedding new light on the deceleration epoch of the Universe. We give predictions for SLSN Ic redshift distribution within present (DES and SUDSS, which are expected to find 15 and 75 SLSNe respectively) and future surveys (LSST and Euclid, which should increase the available SLSNe to 10; 000 and 300 respectively, the latter up to redshift 4). We construct simulated Hubble diagrams for SLSNe Ic, spanning the likely values of intrinsic scatter for these sources ( 0:15 - 0:25 magnitudes), and fit the Hubble diagrams to infer cosmological constraints. We find that the addition of 75 SLSNe from SUDSS to the 3800 SNe Ia from DES can improve the constraints on w (the dark energy state parameter) and Ωm by 20% (assuming a flat wCDM universe). Moreover, the combination of DES SNe Ia and 10,000 LSST SLSNe can measure Ωm and w to 2% and 4% respectively. When considering temporal variations in w(a), we find possible uncertainties of 2%, 5% and 0.14 on Ωm, w0 and wa respectively, from the combination of DES SNe Ia, LSST SLSNe and Planck Cosmic Microwave Background temperature power spectrum. We find that SLSNe from Euclid can constrain the matter density parameter to 10%, and can help constraining the equation-of-state parameters w0 and wa. All these surveys will also improve the knowledge about SLSN astrophysics, their progenitors and possible classification into sub-classes.
|Date of Award||Feb 2017|
|Supervisor||Bob Nichol (Supervisor) & David Bacon (Supervisor)|