GW070605: An Undisclosed Binary Neutron Star Hardware Injection in LIGO's Fifth Science Run

Abstract

The authors wished to document the sensitivity improvement that has been contributed to the GW detection rate by detection algorithm research and development efforts, and set about re-analyzing S5 and S6 to determine the sensitive time-volumes of a modern pipeline and compare them to that of analysis algorithms of the day. To our surprise, this effort led to the discovery of GW070605, what at first appeared to be a previously unreported high significance binary neutron star merger at a time when only the Livingston detector (L1) was operating -- data that could not have been analyzed and a signal that could not have been discovered previously because the algorithms of the day required coincidence between two or more detectors. GW070605's end time occurs in LIGO's L1 detector at 2007-06-05 18:37:02 UTC, and is estimated to be a merger with component masses of 1.82$M_\odot$ and 1.24$M_\odot$. The GstLAL detection algorithm estimates that noise processes produce false positives at least as significant as GW070605 at a rate of $8.6\times10^{-10}$ per year. Disappointingly, subsequent investigations revealed the presence of a previously undocumented hardware injection in the L1 detector's Y arm end test mass' excitation channel, whose time and properties match that of GW070605. The injection does not appear in the Gravitational Wave Open Science Center list of hardware injections. We determined that while there is no sensitivity improvement between GstLAL and previous algorithms at the null-result threshold, there is marked improvement at above null-result thresholds; specifically, an approximately 55-times detection rate increase from initial-era algorithms at a FAR threshold of 1 per 7000 years.

Figures (8)

• Figure 1: Template waveforms plotted in terms of their chirp mass $\mathcal{M}_c$ and effective spin $\chi_\mathrm{eff}$. The total mass of the templates is limited to $m_1+m_1 \le 25 \mathrm{M}_{\odot}$ to reduce the number of triggers rung up by high mass ratio templates due to non-stationary noise Abadie_2012. Colour denotes the template likelihood $P(t_k|\mathrm{signal},\rho)$ at $\rho=10$, and is approximated as a constant over each template bin. Each bin contains approximately 300 templates, which populate the bank via a stochastic placement algorithm Privitera_2014Harry_2009. The waveform approximant used is IMRPhenomD Khan_2016.
• Figure 2: Number of events that were recovered with $\ln\mathcal{L}$ ranking statistic values above the threshold. The dashed line represents the predicted number of background noise events (with the shaded regions indicating the Poisson-distributed random fluctuations in multiples of $\pm\sqrt{\langle N\rangle}$), while the solid black line denotes the observed number of events in the analysis. The highest significant event, GW070605, was found with a log likelihood ratio $\ln\mathcal{L}=14.13$. The vertical lines at $\ln\mathcal{L} = 4.54$ (Case 1) and $\ln\mathcal{L} = -2.51$ (Case 2) mark the thresholds for when the top ranked and top three ranked candidates are excluded, respectively. These cases are later used as the null-result $\ln\mathcal{L}$ thresholds in Sec. \ref{['sec:sensitivity']}.
• Figure 3: Q-transform spectrogram of L1 strain data around the time of the candidate event GW070605. The red curve denotes the representative waveform of GW070605, with its end time marked by the vertical dashed line. The Q-values used to create the spectrogram are Q$_\mathrm{min} = 4$ and Q$_\mathrm{max} = 64$.
• Figure 4: Q-transform spectrogram of the L1 ETMX (top) and ETMY (bottom) coil excitation channels. In both panels, the red curve denotes the representative waveform of GW070605, with its end time marked by the vertical dashed line.
• Figure 5: Q-transform spectrograms of the 2nd and 3rd top ranked candidates in Tab. \ref{['table:triggers']}. In both panels, the red curve denotes the template waveform that recovered the candidate, with its end time marked by the vertical dashed line.