Superradiance can trigger the formation of an ultralight boson cloud around a spinning black hole. Once formed, the boson cloud is expected to emit a nearly periodic, long-duration, ...gravitational-wave signal. For boson masses in the range (10−13–10−11) eV, and stellar mass black holes, such signals are potentially detectable by gravitational-wave detectors, like Advanced LIGO and Virgo. In this Letter, we present full band upper limits for a generic all-sky search for periodic gravitational waves in LIGO O2 data, and use them to derive-for the first time-direct constraints on the ultralight scalar boson field mass.
While gravitational waves have been detected from mergers of binary black holes and binary neutron stars, signals from core collapse supernovae, the most energetic explosions in the modern Universe, ...have not been detected yet. Here we present a new method to analyse the data of the LIGO, Virgo, and KAGRA network to enhance the detection efficiency of this category of signals. The method takes advantage of a peculiarity of the gravitational wave signal emitted in the core collapse supernova and it is based on a classification procedure of the time-frequency images of the network data performed by a convolutional neural network trained to perform the task to recognize the signal. We validate the method using phenomenological waveforms injected in Gaussian noise whose spectral properties are those of the LIGO and Virgo advanced detectors and we conclude that this method can identify the signal better than the present algorithm devoted to select gravitational wave transient signal.
As a consequence of superradiant instability induced in Kerr black holes, ultralight boson clouds can be a source of persistent gravitational waves, potentially detectable by current and future ...gravitational-wave detectors. These signals have been predicted to be nearly monochromatic, with a small steady frequency increase (spin-up), but given the several assumptions and simplifications done at theoretical level, it is wise to consider, from the data analysis point of view, a broader class of gravitational signals in which the phase (or the frequency) slightly wander in time. Also other types of sources, e.g., neutron stars in which a torque balance equilibrium exists between matter accretion and emission of persistent gravitational waves, would fit in this category. In this paper we present a robust and computationally cheap analysis pipeline devoted to the search of such kind of signals. We provide a full characterization of the method, through both a theoretical sensitivity estimation and through the analysis of synthetic data in which simulated signals have been injected. The search setup for both all-sky searches and higher sensitivity directed searches is discussed.
A rapidly rotating neutron star (NS) with non-axisymmetric deformations is an interesting type of continuous gravitational-Wave (CW) source for the advanced LIGO-Virgo detectors. Within the ...sensitivity bands of these detectors, more than half of the known pulsars (i.e. 1200) in our galaxy are in binary systems. All CW signals are modulated by the doppler effect due to Earth's motion, while for sources in binary systems there is an extra modulation due to the source orbital motion, which further decreases the detectability of the signal, if not properly taken into account. In order to correct for these modulations, one would need to know at least the orbital parameters and source sky location with very high accuracy. For unknown parameters the correction implies an extensive computational burden. In this paper we investigate-for the first time-the application and robustness of binary time-domain corrections to directed narrowband searches through the stroboscopic resampling, which has already been applied in several CW searches for isolated NSs. We also present a 90% confidence-level sensitivity estimation for a Scorpius X-1 directed narrowband search on publicly available data from the second observing advanced LIGO-Virgo run.
A type of gravitational-wave signal in the LIGO-Virgo data is expected to be emitted by spinning asymmetric neutron stars, with rotational frequencies that could plausibly emit continuous ...gravitational radiation in the most sensitive band of the LIGO-Virgo detectors. The most important feature of such signals is in their phase evolution, which is stable over a long observation run. When using analysis based on matched filtering, the phase evolution of long-coherent signals is needed to define how to build a proper template grid in order to gain the best signal-to-noise ratio possible. This information is encoded in a matrix called a phase metric, which characterizes the geometry for the likelihood given by matched filtering. Most of the time, the metric for long-coherent signals cannot be computed analytically, and even its numerical computation is not possible due to the numerical precision needed. In this paper, we show a general phase decomposition technique that is able to make the template metric semianalytically computable. We also show how these variables can be employed to distinguish robustly between astrophysical signals and nonstationary noise artifacts that may affect analysis pipelines.
Abstract
In this work, simple semi-empirical correlations to describe the temperature and the pressure dependence of the dynamic viscosity of low GWP refrigerants, namely HydroFluoroOlefins (HFOs) ...and HydroChloroFluoroOlefins (HCFOs), in the liquid phase are presented. Firstly, the experimental liquid dynamic viscosity data available in scientific literature and databases were collected and statistically analyzed. From the data collected for low pressures, the Latini et al. (2002, 1990) correlation for the dynamic viscosity of liquid refrigerants in saturated conditions was re-fitted and constants expressly dedicated to the studied low GWP refrigerants were obtained. Then, the proposed temperature-dependent correlation was modified to represent liquid dynamic viscosity dependence on pressure. In addition, an artificial neural network was developed to predict the dependence of the liquid viscosity of the studied refrigerants on temperature and pressure. This model was trained, validated, and tested for the selected dataset. The results of the proposed correlations and the multi-layer perceptron neural network were compared with the liquid viscosity calculations provided by some of the most well-known literature correlations and REFPROP 10.0, proving the accuracy of the proposed models for engineering applications.
This work explores the relationship between two data-analysis methods used in the search for continuous gravitational waves in LIGO-Virgo-KAGRA data: the \(\mathcal{F}\)-statistic and the 5-vector ...method. We show that the 5-vector method can be derived from a maximum likelihood framework similar to the \(\mathcal{F}\)-statistic. Our analysis demonstrates that the two methods are statistically equivalent, providing the same detection probability for a given false alarm rate. We extend this comparison to multiple detectors, highlighting differences from the standard approach that simply combines 5-vectors from each detector. In our maximum likelihood approach, each 5-vector is weighted by the observation time and sensitivity of its respective detector, resulting in efficient estimators and analytical distributions for the detection statistic. Additionally, we present the analytical computation of sensitivity for different searches, expressed in terms of the minimum detectable amplitude.
The emission of continuous gravitational waves (CWs), with duration much longer than the typical data taking runs, is expected from several sources, notably spinning neutron stars, asymmetric with ...respect to their rotation axis and more exotic sources, like ultra-light scalar boson clouds formed around Kerr black holes and sub-solar mass primordial binary black holes. Unless the signal time evolution is well predicted and its relevant parameters accurately known, the search for CWs is typically based on semi-coherent methods, where the full data set is divided in shorter chunks of given duration, which are properly processed, and then incoherently combined. In this paper we present a semi-coherent method, in which the so-called \textit{5-vector} statistics is computed for the various data segments and then summed after the removal of the Earth Doppler modulation and signal intrinsic spin-down. The method can work with segment duration of several days, thanks to a double stage procedure in which an initial rough correction of the Doppler and spin-down is followed by a refined step in which the residual variations are removed. This method can be efficiently applied for directed searches, where the source position is known to a good level of accuracy, and in the candidate follow-up stage of wide-parameter space searches.
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