| dc.description.abstract | Cosmology asks questions about the large scale properties of the universe, e.g.: ”What is the universe
made of?”, and ”How are things distributed throughout the universe?”. To help answer these questions
we look at Intrinsic Alignment (IA), the correlation between galaxy shapes and nearby large-scale structures during galaxy formation, alongside gravitational lensing. IA is dependent on the method of shape
measurement, since different measurement methods are sensitive to different parts of galaxies, which align
differently. In this thesis we investigate the use of multiple shape measurements per galaxy to enhance
cosmological constraints.
In Part I, Intrinsic Alignment Amplitude (AIA) and difference in AIA between methods (∆AIA) are
measured using data from the Galaxy And Mass Assembly (GAMA) survey (for redshifts) and the KiloDegree Survey (KiDS) (for shapes). Galaxy shapes are determined using the moments-based DEIMOS
method. This method includes a weight function, which is varied so that a set of measurements is taken
that is sensitive to the outer regions of galaxies, a set that is sensitive to the inner regions of galaxies, and
one in between. A random catalog is employed to mitigate large-scale structure effects. Two subsamples,
”Reddest” and ”Brightest,” are selected based on colour and brightness. Common estimators are used
to measure galaxy position-galaxy position and galaxy position-galaxy shape correlations, with a modification for galaxy position-difference in galaxy shape correlation. This difference is between the shape
measured at the outer regions and the inner regions of galaxies. ∆AIA values of 0.55±0.40 (Brightest) and
0.86±0.74 (Reddest) are obtained, providing upper bounds and indicating potential underlying effects.
In Part II, the impact of multiple shape measurements is forecasted for the Large Synoptic Survey
Telescope (LSST). Five tomographic redshift bins and two shape measurement methods per galaxy are
considered, resulting in 55 angular shape-shape power spectra. The covariance matrix, accounting for
correlated noise, is modeled. Fisher forecasting is employed to predict the covariance matrix of cosmological parameters and assess uncertainties related to the parameter S8. Reductions in S8 uncertainty up to
35% (ideal scenario), 20% (’Brightest” like scenario), and 15% (”Reddest” like scenario) are forecasted.
In conclusion, this study demonstrates that utilizing multiple shape measurements per galaxy can
enhance cosmological constraints without requiring additional telescope time. | |
