A great deal of expertise in satellite precipitation estimation has been developed during the Tropical Rainfall Measuring Mission (TRMM) era (1998–2015). The quantification of errors associated with ...satellite precipitation products (SPPs) is crucial for a correct use of these datasets in hydrological applications, climate studies, and water resources management. This study presents a review of previous work that focused on validating SPPs for liquid precipitation during the TRMM era through comparisons with surface observations, both in terms of mean errors and detection capabilities across different regions of the world. Several SPPs have been considered: TMPA 3B42 (research and real-time products), CPC morphing technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP; both the near-real-time and the Motion Vector Kalman filter products), PERSIANN, and PERSIANN–Cloud Classification System (PERSIANN-CCS). Topography, seasonality, and climatology were shown to play a role in the SPP’s performance, especially in terms of detection probability and bias. Regions with complex terrain exhibited poor rain detection and magnitude-dependent mean errors; low probability of detection was reported in semiarid areas. Winter seasons, usually associated with lighter rain events, snow, and mixed-phase precipitation, showed larger biases.
Ultralight bosons with masses in the range 10−13 eV≤mb≤10−12 eV can induce a superradiant instability around spinning black holes (BHs) with masses of order 10−100 M⊙. This instability leads to ...the formation of a rotating "bosonic cloud" around the BH, which can emit gravitational waves (GWs) in the frequency band probed by ground-based detectors. The superposition of GWs from all such systems can generate a stochastic gravitational-wave background (SGWB). In this work, we develop a Bayesian data analysis framework to study the SGWB from bosonic clouds using data from Advanced LIGO and Advanced Virgo, building on previous work by Brito et al. Phys. Rev. D 96, 064050 (2017). We further improve this model by adding a BH population of binary merger remnants. To assess the performance of our pipeline, we quantify the range of boson masses that can be constrained by Advanced LIGO and Advanced Virgo measurements at design sensitivity. Furthermore, we explore our capability to distinguish an ultralight boson SGWB from a stochastic signal due to distant compact binary coalescences (CBC). Finally, we present results of a search for the SGWB from bosonic clouds using data from Advanced LIGO's first observing run. We find no evidence of such a signal. Due to degeneracies between the boson mass and unknown astrophysical quantities such as the distribution of isolated BH spins, our analysis cannot robustly exclude the presence of a bosonic field at any mass. Nevertheless, we show that under optimistic assumptions about the BH formation rate and spin distribution, boson masses in the range 2.0×10−13 eV≤mb≤3.8×10−13 eV are excluded at 95% credibility, although with less optimistic spin distributions, no masses can be excluded. The framework established here can be used to learn about the nature of fundamental bosonic fields with future gravitational wave observations.
The recent Advanced LIGO and Advanced Virgo joint observing runs have not claimed a stochastic gravitational-wave background detection, but one expects this to change as the sensitivity of the ...detectors improves. The challenge of claiming a true detection will be immediately succeeded by the difficulty of relating the signal to the sources that contribute to it. In this paper, we consider backgrounds that comprise compact binary coalescences and additional cosmological sources, and we set simultaneous upper limits on these backgrounds. We find that the Advanced LIGO/Advanced Virgo network, operating at design sensitivity, will not allow for separation of the sources we consider. Third-generation detectors, sensitive to most individual compact binary mergers, can reduce the astrophysical signal via subtraction of individual sources, and potentially reveal a cosmological background. Our Bayesian analysis shows that, assuming a detector network containing Cosmic Explorer and Einstein Telescope and reasonable levels of individual source subtraction, we can detect cosmological signals ΩCS (25 Hz) = 4.5 × 10−13 for cosmic strings, and ΩBPL (25 Hz) = 2.2 × 10−13 for a broken power-law model of an early Universe phase transition.
A detection of the stochastic gravitational-wave background (SGWB) from unresolved compact binary coalescences could be made by Advanced LIGO and Advanced Virgo at their design sensitivities. ...However, it is possible for magnetic noise that is correlated between spatially separated ground-based detectors to mimic a SGWB signal. In this paper we propose a new method for detecting correlated magnetic noise and separating it from a true SGWB signal. A commonly discussed method for addressing correlated magnetic noise is coherent subtraction in the raw data using Wiener filtering. The method proposed here uses a parametrized model of the magnetometer-to-strain coupling functions, along with measurements from local magnetometers, to estimate the contribution of correlated noise to the traditional SGWB detection statistic. We then use Bayesian model selection to distinguish between models that include correlated magnetic noise and those with a SGWB. Realistic simulations are used to show that this method prevents a false SGWB detection due to correlated magnetic noise. We also demonstrate that it can be used for a detection of a SGWB in the presence of strong correlated magnetic noise, albeit with reduced significance compared to the case with no correlated noise. Finally, we discuss the advantages of using a global three-detector network for both identifying and characterizing correlated magnetic noise.
The collection of individually resolvable gravitational wave (GW) events makes up a tiny fraction of all GW signals that reach our detectors, while most lie below the confusion limit and are ...undetected. Similarly to voices in a crowded room, the collection of unresolved signals gives rise to a background that is well-described via stochastic variables and, hence, referred to as the stochastic GW background (SGWB). In this review, we provide an overview of stochastic GW signals and characterise them based on features of interest such as generation processes and observational properties. We then review the current detection strategies for stochastic backgrounds, offering a ready-to-use manual for stochastic GW searches in real data. In the process, we distinguish between interferometric measurements of GWs, either by ground-based or space-based laser interferometers, and timing-residuals analyses with pulsar timing arrays (PTAs). These detection methods have been applied to real data both by large GW collaborations and smaller research groups, and the most recent and instructive results are reported here. We close this review with an outlook on future observations with third generation detectors, space-based interferometers, and potential noninterferometric detection methods proposed in the literature.
ABSTRACT
It is an open challenge to estimate systematically the physical parameters of neutron star interiors from pulsar timing data while separating spin wandering intrinsic to the pulsar ...(achromatic timing noise) from measurement noise and chromatic timing noise (due to propagation effects). In this paper, we formulate the classic two-component, crust-superfluid model of neutron star interiors as a noise-driven, linear dynamical system and use a state-space-based expectation–maximization method to estimate the system parameters using gravitational-wave and electromagnetic timing data. Monte Carlo simulations show that we can accurately estimate all six parameters of the two-component model provided that electromagnetic measurements of the crust angular velocity and gravitational-wave measurements of the core angular velocity are both available. When only electromagnetic data are available, we can recover the overall relaxation time-scale, the ensemble-averaged spin-down rate, and the strength of the white-noise torque on the crust. However, the estimates of the secular torques on the two components and white-noise torque on the superfluid are biased significantly.
ABSTRACT In the standard two-component crust-superfluid model of a neutron star, timing noise can arise when the two components are perturbed by stochastic torques. Here it is demonstrated how to ...analyse fluctuations in radio pulse times of arrival with a Kalman filter to measure physical properties of the two-component model, including the crust-superfluid coupling time-scale and the variances of the crust and superfluid torques. The analysis technique, validated previously on synthetic data, is applied to observations with the Molonglo Observatory Synthesis Telescope of the representative pulsar PSR J1359−6038. It is shown that the two-component model is preferred to a one-component model, with log Bayes factor 6.81 ± 0.02. The coupling time-scale and the torque variances on the crust and superfluid are measured with 90 per cent confidence to be $10^{7.1^{+0.8}_{-0.5}}$$\rm {s}$ and $10^{-24.0^{+0.4}_{-5.6}}$$\rm {rad^2~s^{-3}}$ and $10^{-21.7^{+3.5}_{-0.9}}$$\rm {rad^2~s^{-3}}$, respectively.
ABSTRACT
The classic, two-component, crust-superfluid model of a neutron star can be formulated as a noise-driven, linear dynamical system, in which the angular velocities of the crust and superfluid ...are tracked using a Kalman filter applied to electromagnetic pulse timing data and gravitational-wave data, when available. Here it is shown how to combine the marginal likelihood of the Kalman filter and nested sampling to estimate full posterior distributions of the six model parameters, extending previous analyses based on a maximum-likelihood approach. The method is tested across an astrophysically plausible parameter domain using Monte Carlo simulations. It recovers the injected parameters to ≲10 per cent for time series containing ∼103 samples, typical of long-term pulsar timing campaigns. It runs efficiently in $\mathcal {O}(1)$ CPU-hr for data sets of the above size. In a present-day observational scenario, when electromagnetic data are available only, the method accurately estimates three parameters: the relaxation time, the ensemble-averaged spin-down of the system, and the amplitude of the stochastic torques applied to the crust. In a future observational scenario, where gravitational-wave data are also available, the method also estimates the ratio between the moments of inertia of the crust and the superfluid, the amplitude of the stochastic torque applied to the superfluid, and the crust-superfluid lag. These empirical results are consistent with a formal identifiability analysis of the linear dynamical system.
Abstract The magnetic dipole moment μ of an accretion-powered pulsar in magnetocentrifugal equilibrium cannot be inferred uniquely from time-averaged pulse period and aperiodic X-ray flux data, ...because the radiative efficiency η 0 of the accretion is unknown, as are the mass, radius, and distance of the star. The degeneracy associated with the radiative efficiency is circumvented if fluctuations of the pulse period and aperiodic X-ray flux are tracked with a Kalman filter, whereupon μ can be measured uniquely up to the uncertainties in the mass, radius, and distance. Here, the Kalman filter analysis is demonstrated successfully in practice for the first time on Rossi X-ray Timing Explorer observations of the X-ray transient SXP 18.3 in the Small Magellanic Cloud (SMC), which is monitored regularly. The analysis yields μ = 8.0 − 1.2 + 1.3 × 10 30 G cm 3 and η 0 = 0.04 − 0.01 + 0.02 , compared to μ = 5.0 − 1.0 + 1.0 × 10 30 G cm 3 as inferred traditionally from time-averaged data assuming η 0 = 1. The analysis also yields time-resolved estimates of two hidden state variables, the mass accretion rate and the Maxwell stress at the disk–magnetosphere boundary. The success of the demonstration confirms that the Kalman filter analysis can be applied in the future to study the magnetic moments and disk–magnetosphere physics of accretion-powered pulsar populations in the SMC and elsewhere.
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