Characterizing a supernova's Standing Accretion Shock Instability with neutrinos and gravitational waves

We perform a novel multi-messenger analysis for the identification and parameter estimation of the Standing Accretion Shock Instability (SASI) in a core collapse supernova with neutrino and gravitational wave (GW) signals. In the neutrino channel, this method performs a likelihood ratio test for the presence of SASI in the frequency domain. For gravitational wave signals we process an event with a modified constrained likelihood method. Using simulated supernova signals, the properties of the Hyper-Kamiokande neutrino detector, and O3 LIGO Interferometric data, we produce the two-dimensional probability density function (PDF) of the SASI activity indicator and calculate the probability of detection $P_\mathrm{D}$ as well as the false identification probability $P_\mathrm{FI}$. We discuss the probability to establish the presence of the SASI as a function of the source distance in each observational channel, as well as jointly. Compared to a single-messenger approach, the joint analysis results in $P_\mathrm{D}$ (at $P_\mathrm{FI}=0.1$) of SASI activities that is larger by up to $\approx~40\%$ for a distance to the supernova of 5 kpc. We also discuss how accurately the frequency and duration of the SASI activity can be estimated in each channel separately. Our methodology is suitable for implementation in a realistic data analysis and a multi-messenger setting.Comment: 24 pages, 15 figures, accepted by PR

Observing gravitational waves from core-collapse supernovae in the advanced detector era

The next galactic core-collapse supernova (CCSN) has already exploded, and its electromagnetic (EM) waves, neutrinos, and gravitational waves (GWs) may arrive at any moment. We present an extensive study on the potential sensitivity of prospective detection scenarios for GWs from CCSNe within 5 Mpc, using realistic noise at the predicted sensitivity of the Advanced LIGO and Advanced Virgo detectors for 2015, 2017, and 2019. We quantify the detectability of GWs from CCSNe within the Milky Way and Large Magellanic Cloud, for which there will be an observed neutrino burst. We also consider extreme GW emission scenarios for more distant CCSNe with an associated EM signature. We find that a three-detector network at design sensitivity will be able to detect neutrino-driven CCSN explosions out to ∼5.5  kpc, while rapidly rotating core collapse will be detectable out to the Large Magellanic Cloud at 50 kpc. Of the phenomenological models for extreme GW emission scenarios considered in this study, such as long-lived bar-mode instabilities and disk fragmentation instabilities, all models considered will be detectable out to M31 at 0.77 Mpc, while the most extreme models will be detectable out to M82 at 3.52 Mpc and beyond

Search for Transient Gravitational Waves in Coincidence With Short-Duration Radio Transients During 2007-2013

We present an archival search for transient gravitational-wave bursts in coincidence with 27 single pulse triggers from Green Bank Telescope pulsar surveys, using the LIGO, Virgo and GEO interferometer network. We also discuss a check for gravitational-wave signals in coincidence with Parkes Fast Radio Bursts using similar methods. Data analyzed in these searches were collected between 2007 and 2013. Possible sources of emission of both short-duration radio signals and transient gravitational-wave emission include starquakes on neutron stars, binary coalescence of neutron stars, and cosmic string cusps. While no evidence for gravitational-wave emission in coincidence with these radio transients was found, the current analysis serves as a prototype for similar future searches using more sensitive second-generation interferometers

A First Comparison Between LIGO and Virgo Inspiral Search Pipelines

This article reports on a project that is the first step the LIGO Scientific Collaboration and the Virgo Collaboration have taken to prepare for the mutual search for inspiral signals. The project involved comparing the analysis pipelines of the two collaborations on data sets prepared by both sides, containing simulated noise and injected events. The ability of the pipelines to detect the injected events was checked, and a first comparison of how the parameters of the events were recovered has been completed.Comment: GWDAW-9 proceeding

A first comparison of search methods for gravitational wave bursts using LIGO and Virgo simulated data

We present a comparative study of 6 search methods for gravitational wave bursts using simulated LIGO and Virgo noise data. The data's spectra were chosen to follow the design sensitivity of the two 4km LIGO interferometers and the 3km Virgo interferometer. The searches were applied on replicas of the data sets to which 8 different signals were injected. Three figures of merit were employed in this analysis: (a) Receiver Operator Characteristic curves, (b) necessary signal to noise ratios for the searches to achieve 50 percent and 90 percent efficiencies, and (c) variance and bias for the estimation of the arrival time of a gravitational wave burst.Comment: GWDAW9 proceeding

Using supervised learning algorithms as a follow-up method in the search of gravitational waves from core-collapse supernovae

We present a follow-up method based on supervised machine learning (ML) to improve the performance in the search of gravitational wave (GW) bursts from core-collapse supernovae (CCSNe) using the coherent WaveBurst (cWB) pipeline. The ML model discriminates noise from signal events by using a set of reconstruction parameters provided by cWB as features. Detected noise events are discarded yielding a reduction in the false alarm rate (FAR) and the false alarm probability thus enhancing the statistical significance. We tested the proposed method using strain data from the first half of the third observing run of advanced LIGO, and CCSNe GW signals extracted from 3D simulations. The ML model is tuned using a dataset of noise and signal events, and then used to identify and discard noise events in the cWB analyses. Noise and signal reduction levels were examined in single (L1 and H1) and two detector network (L1H1). The FAR was reduced by a factor of ∼10 to ∼100 resulting in an enhancement in the statistical significance of ∼1σ to ∼2σ, while not impacting the detection efficiencies

Using Supervised Learning Algorithms as a Follow-Up Method in the Search of Gravitational Waves from Core-Collapse Supernovae

We present a follow-up method based on supervised machine learning (ML) to improve the performance in the search of gravitational wave (GW) bursts from core-collapse supernovae (CCSNe) using the coherent WaveBurst (cWB) pipeline. The ML model discriminates noise from signal events by using a set of reconstruction parameters provided by cWB as features. Detected noise events are discarded yielding a reduction in the false alarm rate (FAR) and the false alarm probability thus enhancing the statistical significance. We tested the proposed method using strain data from the first half of the third observing run of advanced LIGO, and CCSNe GW signals extracted from 3D simulations. The ML model is tuned using a dataset of noise and signal events, and then used to identify and discard noise events in the cWB analyses. Noise and signal reduction levels were examined in single (L1 and H1) and two detector networks (L1H1). The FAR was reduced by a factor of ∼10 to ∼100 resulting in an enhancement in the statistical significance of ∼1σ to ∼2σ, while not impacting the detection efficiencies

Application of asymptotic expansions of maximum likelihood estimators errors to gravitational waves from binary mergers: the single interferometer case

In this paper we describe a new methodology to calculate analytically the error for a maximum likelihood estimate (MLE) for physical parameters from Gravitational wave signals. All the existing litterature focuses on the usage of the Cramer Rao Lower bounds (CRLB) as a mean to approximate the errors for large signal to noise ratios. We show here how the variance and the bias of a MLE estimate can be expressed instead in inverse powers of the signal to noise ratios where the first order in the variance expansion is the CRLB. As an application we compute the second order of the variance and bias for MLE of physical parameters from the inspiral phase of binary mergers and for noises of gravitational wave interferometers . We also compare the improved error estimate with existing numerical estimates. The value of the second order of the variance expansions allows to get error predictions closer to what is observed in numerical simulations. It also predicts correctly the necessary SNR to approximate the error with the CRLB and provides new insight on the relationship between waveform properties SNR and estimation errors. For example the timing match filtering becomes optimal only if the SNR is larger than the kurtosis of the gravitational wave spectrum

A comparison of methods for gravitational wave burst searches from LIGO and Virgo

The search procedure for burst gravitational waves has been studied using 24 hours of simulated data in a network of three interferometers (Hanford 4-km, Livingston 4-km and Virgo 3-km are the example interferometers). Several methods to detect burst events developed in the LIGO Scientific Collaboration (LSC) and Virgo collaboration have been studied and compared. We have performed coincidence analysis of the triggers obtained in the different interferometers with and without simulated signals added to the data. The benefits of having multiple interferometers of similar sensitivity are demonstrated by comparing the detection performance of the joint coincidence analysis with LSC and Virgo only burst searches. Adding Virgo to the LIGO detector network can increase by 50% the detection efficiency for this search. Another advantage of a joint LIGO-Virgo network is the ability to reconstruct the source sky position. The reconstruction accuracy depends on the timing measurement accuracy of the events in each interferometer, and is displayed in this paper with a fixed source position example.Comment: LIGO-Virgo working group submitted to PR

LOOC UP: Locating and observing optical counterparts to gravitational wave bursts

Gravitational wave (GW) bursts (short duration signals) are expected to be associated with highly energetic astrophysical processes. With such high energies present, it is likely these astrophysical events will have signatures in the EM spectrum as well as in gravitational radiation. We have initiated a program, "Locating and Observing Optical Counterparts to Unmodeled Pulses in Gravitational Waves" (LOOC UP) to promptly search for counterparts to GW burst candidates. The proposed method analyzes near real-time data from the LIGO-Virgo network, and then uses a telescope network to seek optical-transient counterparts to candidate GW signals. We carried out a pilot study using S5/VSR1 data from the LIGO-Virgo network to develop methods and software tools for such a search. We will present the method, with an emphasis on the potential for such a search to be carried out during the next science run of LIGO and Virgo, expected to begin in 2009.Comment: 11 pages, 2 figures; v2) added acknowledgments, additional references, and minor text changes v3) added 1 figure, additional references, and minor text changes. v4) Updated references and acknowledgments. To be published in the GWDAW 12 Conf. Proc. by Classical and Quantum Gravit