2 resultados para Coalescence Times

em CaltechTHESIS


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Cosmic birefringence (CB)---a rotation of photon-polarization plane in vacuum---is a generic signature of new scalar fields that could provide dark energy. Previously, WMAP observations excluded a uniform CB-rotation angle larger than a degree.

In this thesis, we develop a minimum-variance--estimator formalism for reconstructing direction-dependent rotation from full-sky CMB maps, and forecast more than an order-of-magnitude improvement in sensitivity with incoming Planck data and future satellite missions. Next, we perform the first analysis of WMAP-7 data to look for rotation-angle anisotropies and report null detection of the rotation-angle power-spectrum multipoles below L=512, constraining quadrupole amplitude of a scale-invariant power to less than one degree. We further explore the use of a cross-correlation between CMB temperature and the rotation for detecting the CB signal, for different quintessence models. We find that it may improve sensitivity in case of marginal detection, and provide an empirical handle for distinguishing details of new physics indicated by CB.

We then consider other parity-violating physics beyond standard models---in particular, a chiral inflationary-gravitational-wave background. We show that WMAP has no constraining power, while a cosmic-variance--limited experiment would be capable of detecting only a large parity violation. In case of a strong detection of EB/TB correlations, CB can be readily distinguished from chiral gravity waves.

We next adopt our CB analysis to investigate patchy screening of the CMB, driven by inhomogeneities during the Epoch of Reionization (EoR). We constrain a toy model of reionization with WMAP-7 data, and show that data from Planck should start approaching interesting portions of the EoR parameter space and can be used to exclude reionization tomographies with large ionized bubbles.

In light of the upcoming data from low-frequency radio observations of the redshifted 21-cm line from the EoR, we examine probability-distribution functions (PDFs) and difference PDFs of the simulated 21-cm brightness temperature, and discuss the information that can be recovered using these statistics. We find that PDFs are insensitive to details of small-scale physics, but highly sensitive to the properties of the ionizing sources and the size of ionized bubbles.

Finally, we discuss prospects for related future investigations.

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The LIGO and Virgo gravitational-wave observatories are complex and extremely sensitive strain detectors that can be used to search for a wide variety of gravitational waves from astrophysical and cosmological sources. In this thesis, I motivate the search for the gravitational wave signals from coalescing black hole binary systems with total mass between 25 and 100 solar masses. The mechanisms for formation of such systems are not well-understood, and we do not have many observational constraints on the parameters that guide the formation scenarios. Detection of gravitational waves from such systems — or, in the absence of detection, the tightening of upper limits on the rate of such coalescences — will provide valuable information that can inform the astrophysics of the formation of these systems. I review the search for these systems and place upper limits on the rate of black hole binary coalescences with total mass between 25 and 100 solar masses. I then show how the sensitivity of this search can be improved by up to 40% by the the application of the multivariate statistical classifier known as a random forest of bagged decision trees to more effectively discriminate between signal and non-Gaussian instrumental noise. I also discuss the use of this classifier in the search for the ringdown signal from the merger of two black holes with total mass between 50 and 450 solar masses and present upper limits. I also apply multivariate statistical classifiers to the problem of quantifying the non-Gaussianity of LIGO data. Despite these improvements, no gravitational-wave signals have been detected in LIGO data so far. However, the use of multivariate statistical classification can significantly improve the sensitivity of the Advanced LIGO detectors to such signals.