First targeted search for gravitational-wave bursts from core-collapse supernovae in data of first-generation laser interferometer detectors

We present results from a search for gravitational-wave bursts coincident with two core-collapse supernovae observed optically in 2007 and 2011. We employ data from the Laser Interferometer Gravitational-wave Observatory (LIGO), the Virgo gravitational-wave observatory, and the GEO 600 gravitational-wave observatory. The targeted core-collapse supernovae were selected on the basis of (1) proximity (within approximately 15 Mpc), (2) tightness of observational constraints on the time of core collapse that defines the gravitational-wave search window, and (3) coincident operation of at least two interferometers at the time of core collapse. We find no plausible gravitational-wave candidates. We present the probability of detecting signals from both astrophysically well-motivated and more speculative gravitational-wave emission mechanisms as a function of distance from Earth, and discuss the implications for the detection of gravitational waves from core-collapse supernovae by the upgraded Advanced LIGO and Virgo detectors.

Figure 1

On-source windows as defined for the four core-collapse supernovae considered in Sec. 2. The date given for each core-collapse supernova is the published date of discovery. Overplotted in color are the stretches of time covered with science-quality and Astrowatch-quality data of the various GW interferometers. The percentages given for each core-collapse supernova and interferometer are the fractional coverage of the on-source window with science or astrowatch data by that interferometer. See Table 1 and Secs. 2 and 3 for details.

Figure 2

Noise amplitude spectral densities of the GW interferometers whose data are analyzed for SNe 2007gr and 2011dh (see Sec. 3). The curves are the results of averaging $1/S(f)$ over the on-source windows of the SNe (see Table 1). We plot the G1 noise spectrum also for SN 2008ax to demonstrate the improvement in high-frequency sensitivity due to GEO-HF [131] for SN 2011dh.

Figure 3

False Alarm Probability [FAP, Equation (1)] distributions of the background events for SN 2007gr and the H1H2L1V1 detector network (cf. Section 3). The FAP indicates the probability that an event of a given “loudness” (significance) is consistent with background noise. The left panel shows the FAP distribution determined by the cWB pipeline as a function of its loudness measure, $\rho$, (see [136] for details). The right panel depicts the same for X-Pipeline as a function of its loudness measure, ${\mathrm{\Lambda }}_c$, (see [61, 135] for details). The shaded regions indicate $1-\sigma$ error estimates for the FAP.

Figure 4

SN 2007gr detection efficiency versus distance for the waveforms from multidimensional CCSN simulations (left) and the phenomenological waveforms (right) described in Tables 4 and 5. Simulated GW signals are added into detector data with a range of amplitudes corresponding to different source distances. A simulated signal is considered to be detected if cWB or X-Pipeline reports an event that survives the coherent tests and data quality cuts with a FAR value lower than that of the loudest event from the SN 2007gr and SN 2011dh on-source windows. These efficiencies are averaged over all detector network combinations for SN 2007gr. The efficiencies are limited to $\le 93\%$ at small distances due to the fact that this was the duty cycle for coincident observation over the SN 2007gr on-source window. The numbers in brackets for each model are the distances at which the efficiency equals 50% of the asymptotic value at small distances.

Figure 5

SN 2011dh detection efficiency vs distance for the phenomenological waveforms described in Table 5. Simulated GW signals are added into detector data with a range of amplitudes corresponding to different source distances. A simulated signal is considered to be detected if either cWB or X-Pipeline reports an event that survives the coherent tests and data quality cuts with a FAR value lower than that of the loudest event from the SN 2007gr and SN 2011dh on-source windows. The efficiencies are limited to $\le 37\%$ at small distances due to the fact that this was the duty cycle for coincident observation over the SN 2011dh on-source window; some simulations are also vetoed by data quality cuts. The numbers in the brackets are the distances at which the efficiency equals 50% of its maximum value for each model.

Figure 6

Expected model exclusion probabilities for example waveforms as a function of amplitude sensitivity rescaling, $A$, and supernova sample size rescaling, $p$, based on the SN 2007gr and SN 2011dh sample (e.g. $p=5$ corresponds to 10 supernovae). The naming convention is described in Table 5. Currently none of the emission models can be excluded, but for the advanced detectors with better sensitivity and more nearby CCSNe it is realistic to expect to rule out some of the extreme emission models.