Professor Pedro Ferreira

Abstract:

Scalar fields around compact objects are of interest for scalar-tensor theories of gravity and dark matter models consisting of a massive scalar, e.g., axions. We study the behavior of a scalar field around a Kerr black hole with nontrivial asymptotic boundary conditions—both nonzero density and nonzero angular momentum. Starting from an initial radially homogeneous configuration, a scalar cloud is accreted, which asymptotes to known stationary configurations over time. We study the cloud growth for different parameters including black hole spin, scalar field mass, and the scalar field density and angular momentum far from the black hole. We characterize the transient growth of the mass and angular momentum in the cloud, and the spatial profile of the scalar around the black hole, and relate the results of fully nonlinear simulations to an analytic perturbative expansion. We also highlight the potential for these accreted clouds to create monochromatic gravitational wave signals—similar to the signals from superradiant clouds, although significantly weaker in amplitude.

Abstract:

The Novel Probes Project, an initiative to advance the field of astrophysical tests of the dark sector by creating a forum that connects observers and theorists, is introduced. This review focuses on tests of gravity and is intended to be of use primarily to observers, as well as theorists with an interest in the development of experimental tests. It is twinned with a separate upcoming review on dark matter self-interactions. The review focuses on astrophysical tests of gravity in the weak-field regime, ranging from stars to quasilinear cosmological scales. This regime is complementary to both strong-field tests of gravity and background and linear probes in cosmology. In particular, the nonlinear screening mechanisms that are an integral part of viable modified-gravity models lead to characteristic signatures, specifically on astrophysical scales. The potential of these probes is not limited by cosmic variance but comes with the challenge of building robust theoretical models of the nonlinear dynamics of stars, galaxies, and large-scale structure. The groundwork is laid for a thorough exploration of the weak-field, nonlinear regime, with an eye to using the current and next generation of observations for tests of gravity. The scene is set by showing how gravitational theories beyond general relativity are expected to behave, focusing primarily on screening mechanisms. Analytic and numerical techniques for exploring the relevant astrophysical regime are described, as are the pertinent observational signals. With these in hand a range of astrophysical tests of gravity are presented, and prospects for future measurements and theoretical developments are discussed.

Abstract:

Galileons are scalar field theories which obey the Galileon symmetry $\varphi \to \varphi + b + c_\mu x^\mu$ and are capable of self-acceleration if they have an inverted sign for the kinetic term. These theories violate the Strong Equivalence Principle, such that black holes (BHs) do not couple to the Galileon field, whereas non-relativistic objects experience a fifth force with strength $\Delta G / G_{\rm N}$ relative to gravity. For galaxies falling down a gradient in the Galileon field, this results in an offset between the centre of the galaxy and its host supermassive BH. We reconstruct the local gravitational and Galileon fields through a suite of constrained N-body simulations (which we dub CSiBORG) and develop a Monte Carlo-based forward model for these offsets on a galaxy-by-galaxy basis. Using the measured offset between the optical centre and active galactic nucleus of 1916 galaxies from the literature, propagating uncertainties in the input quantities and marginalising over an empirical noise model describing astrophysical and observational noise, we constrain the Galileon coupling to be $\Delta G / G_{\rm N} < 0.16$ at $1\sigma$ confidence for Galileons with crossover scale $r_{\rm C} \gtrsim H_0^{-1}$.

Abstract:

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-zs at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2pdbl-pdbl2.6 redshift range that the Euclid mission will probe. We designed a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data was divided into two samples: one calibration sample for which photometry and redshifts were provided to the participants; and the validation sample, containing only the photometry to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates the sources they consider unfit for use in cosmological analyses. The performance of each method was assessed through a set of informative metrics, using cross-matched spectroscopic and highly-accurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, that is to say sources for which the photo-z deviates by more than 0.15(1pdbl+pdblz) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. We find that no machine-learning method provides good results in the regions of galaxy color-space that are sparsely populated by spectroscopic-redshifts, for example zpdbl> pdbl1. However they generally perform better than template-fitting methods at low redshift (zpdbl< pdbl0.7), indicating that template-fitting methods do not use all of the information contained in the photometry. We introduce metrics that quantify both photo-z precision and completeness of the samples (post-rejection), since both contribute to the final figure of merit of the science goals of the survey (e.g., cosmic shear from Euclid). Template-fitting methods provide the best results in these metrics, but we show that a combination of template-fitting results and machine-learning results with rejection criteria can outperform any individual method. On this basis, we argue that further work in identifying how to best select between machine-learning and template-fitting approaches for each individual galaxy should be pursued as a priority.