Professor Pedro Ferreira

Abstract:

The detection of an electromagnetic counterpart (GRB 170817A) to the gravitational-wave signal (GW170817) from the merger of two neutron stars opens a completely new arena for testing theories of gravity. We show that this measurement allows us to place stringent constraints on general scalar-tensor and vector-tensor theories, while allowing us to place an independent bound on the graviton mass in bimetric theories of gravity. These constraints severely reduce the viable range of cosmological models that have been proposed as alternatives to general relativistic cosmology.

Abstract:

We construct a model for the angular power spectrum of the instrumental noise in interferometer networks mapping gravitational wave backgrounds (GWBs) as a function of detector noise properties, network configuration, and scan strategy. We use the model to calculate the noise power spectrum for current and future ground-based experiments, as well as for planned space missions. We present our results in a language similar to that used in cosmic microwave background and intensity mapping experiments, and connect the formalism with the sensitivity curves that are common lore in GWB analyses.

Abstract:

Context. Current and future large-scale structure surveys aim to constrain the neutrino mass and the equation of state of dark energy. To do this efficiently, rapid yet accurate evaluation of the matter power spectrum in the presence of these effects is essential. Aims. We aim to construct accurate and interpretable symbolic approximations of the linear and nonlinear matter power spectra as a function of cosmological parameters in extended ΛCDM models that contain massive neutrinos and nonconstant equations of state for dark energy. This constitutes an extension of the SYREN-HALOFIT emulators to incorporate these two effects, which we call SYREN-NEW (SYmbolic-Regression-ENhanced power spectrum emulator with NEutrinos and W0−wa). We also wish to obtain a simple approximation of the derived parameter, σ8, as a function of the cosmological parameters for these models. Methods. We utilizedd symbolic regression to efficiently search through candidate analytic expressions to approximate the various quantities of interest. Our results for the linear power spectrum are designed to emulate CLASS, whereas for the nonlinear case we aim to match the results of EUCLIDEMULATOR2. We compared our results to existing emulators and N-body simulations. Results. Our analytic emulators for σ8, and the linear and nonlinear power spectra achieve root mean squared errors of 0.1%, 0.3%, and 1.3%, respectively, across a wide range of cosmological parameters, redshifts and wavenumbers. The error on the nonlinear power spectrum is reduced by approximately a factor of 2 when considering observationally plausible dark energy models and neutrino masses. We verify that emulator-related discrepancies are subdominant compared to observational errors and other modeling uncertainties when computing shear power spectra for LSST-like surveys. Our expressions have similar accuracy to existing (numerical) emulators, but are at least an order of magnitude faster, both on a CPU and a GPU. Conclusions. Our work greatly improves the accuracy, speed, and applicability range of current symbolic approximations of the linear and nonlinear matter power spectra. These now cover the same range of cosmological models as many numerical emulators with similar accuracy, but are much faster and more interpretable. We provide publicly available code for all symbolic approximations found.