arXiv subjects

F. Muciaccia

Publications and source records attributed to F. Muciaccia.

5 recordsLinked to original sources

arXiv2024

Two sides of the same coin: the F-statistic and the 5-vector method

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.

gr-qc↗

arXiv2023

A semi-coherent generalization of the 5-vector method to search for continuous gravitational waves

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.

gr-qc↗

arXiv2018

A New Method to Observe Gravitational Waves emitted by Core Collapse Supernovae

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.

astro-ph.IM↗

arXiv2018

A semi-coherent analysis method to search for continuous gravitational waves emitted by ultra-light boson clouds around spinning black holes

As a consequence of superradiant instability induced in Kerr black holes, ultra-light 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 syntethic data in which simulated signals have been injected. The search setup for both all-sky searches and higher sensitivity directed searches is discussed.

gr-qc↗

arXiv2018

Phase decomposition of the template metric for continuous gravitational-wave searches

A type of gravitational-wave signals in the LIGO-Virgo sensitivity band are 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 kind of 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 \textit{phase metric}, which characterizes the geometry for the likelihood given by the matched filtering. Most of the times, the metric for long-coherent signals cannot be computed anlaytically and even its numerical computation is not possible due to numerical precision. In this paper we show a general phase decomposition technique able to make the template metric analytically computable. We will also show how this variables can be employed to distinguish in a robust way among astrophysical signals and non-stationary noise artifacts that may affect analysis pipelines.

gr-qc↗