1-OGC: The first open gravitational-wave catalog of binary mergers from analysis of public Advanced LIGO data

Introduction

The Advanced LIGO gravitational wave observatories (Abbott et al., 2016g) performed their first observing run (O1) from September 12, 2015 to January 19, 2016. This provided a total of 51.5 days of coincident observations from the two detectors located in Hanford, WA and Livingston, LA. The binary black hole mergers observed in this observing run have been reported by the LIGO and Virgo Collaborations (LVC) in Abbott et al. (2016e, d, a). These binary black hole detections have been independently studied by Green & Moffat (2018); Roulet & Zaldarriaga (2018); Antelis & Moreno (2018).

Since the publication of the results by Abbott et al. (2016a, i), improvements to the data-analysis methods used (Abbott et al., 2016c) have been implemented (Nitz et al., 2017; Nitz, 2018; Dal Canton & Harry, 2017). Using these improvements, we re-analyze the O1 data and provide—for the first time—a full catalog of candidate events from a matched filter search for compact binary coalescences using the O1 data, which we call 1-OGC. This catalog provides estimates of the significance of previously known events and a ranked list of sub-threshold candidates. Although not significant by themselves, these sub-threshold candidates can be correlated with archival data or transient events found by other astronomical observatories to provide constraints on the population of compact-object mergers (Ashton et al., 2018; Burns et al., 2018).

Our catalog is based entirely on public, open data and software. We use the LIGO data available from the Gravitational Wave Open Science Center (Vallisneri et al., 2015), and analyze the data using the open source PyCBC toolkit (Usman et al., 2016; Dal Canton et al., 2014; Nitz et al., 2018c).This toolkit was also used by one of the two analyses described in Abbott et al. (2016c). The lowest mass sources targeted in our search are neutron star binaries with total mass $m_{1}+m_{2}=2\,M_{\odot}$. The search space extends to binary black hole systems that produce gravitational waveforms longer than $0.15$ s from $20$ Hz. This corresponds to a total mass up to $500M_{\odot}$ for sources with high mass ratios and spins where the component aligned with the orbital angular momentum is positive and large. For binaries with negligible spin, this corresponds to total mass $\lesssim 200M_{\odot}$. The search space also includes neutron star–black hole binaries. After applying cuts for data quality (Abbott et al., 2016b, 2018), a total of 48.1 days of coincident data are searched for signals.

The three most significant signals in the catalog correspond to GW150914 (Abbott et al., 2016e), LVT151012 (Abbott et al., 2016e, a), and GW151226 (Abbott et al., 2016d), respectively. No other astrophysically significant signals are observed. In the analysis of Abbott et al. (2016a), LVT151012 was the third-most significant event, but it was not sufficiently significant to be labeled as an unambiguous detection. With the improved methods employed here, the false alarm rate of this candidate improves by an order of magnitude and it should be considered a true astrophysical event. The analyses of Abbott et al. (2016a, i) restricted the astrophysical search space to binaries with a total mass less that $100\,M_{\odot}$. Our analysis extends this target space to higher mass signals. No additional signals are detected in this region of parameter space, consistent with the results of Abbott et al. (2017g).

A second observing run (O2) of the Advanced LIGO detectors took place from November 30, 2016 to August 25, 2017 (Abbott et al., 2016f). The Virgo gravitational wave detector also collected data for part of this period, starting from August 1, 2017. The detections reported in this second observing run thus far include three additional binary black hole coalescence events (Abbott et al., 2017b, d, e), and a binary neutron star merger (Abbott et al., 2017a). However, the full O2 data set has not yet been released. The catalog presented here is therefore restricted to the first observing run, O1.

Our paper is organized as follows: In Sec. 2 and Sec. 3, we summarize our analysis methods, including the parameter space searched, the detection statistic used for ranking candidate events, and our method for calculating the statistical significance of events. The search results are summarized in Sec. 4. Our full catalog and released data are described in Sec. 5 and are available online as supplementary materials (www.github.com/gwastro/1-ogc). In this paper, we focus on the detection of compact objects. Since no new astrophysical events have been observed, we do not consider measurement of the signals’ parameters and refer to Abbott et al. (2016a); Biwer et al. (2018) for discussion of the detected events’ source-frame properties. Consequently, we quote binary mass parameters in the detector frame in this work.

Search Methodology

To search for gravitational waves from compact-object mergers, we use matched filtering (Allen et al., 2012) implemented in the open-source PyCBC library (Usman et al., 2016; Dal Canton et al., 2014; Nitz et al., 2018c). Our methods improve on the analyses of Abbott et al. (2016a, i, c) by imposing a phase, amplitude and time delay consistency on candidate signals, an improved background model, and a larger search parameter space (Nitz et al., 2017; Nitz, 2018; Dal Canton & Harry, 2017).

A discrete bank of gravitational-wave template waveforms (Owen, 1996; Owen & Sathyaprakash, 1999; Brown et al., 2012) is used to target binary neutron star, neutron star–black hole, and binary black hole mergers with total mass from $2-500M_{\odot}$ (Dal Canton & Harry, 2017). The templates are parameterized by their component masses $m_{1,2}$ and their dimensionless spins $\vec{\chi}_{1,2}=c\vec{S}_{1,2}/Gm_{1,2}^{2}$, where $\vec{S}_{1,2}$ are the spin vectors of each compact object. For compact objects with component masses greater than $2M_{\odot}$, the template bank covers a wide range of spins, with $\chi_{(1,2)z}\in[\pm 0.998]$, where $\chi_{(1,2)z}$ are the components aligned with the orbital angular momentum. For compact objects with masses less than $2M_{\odot}$, the spin is restricted to $\chi_{(1,2)z}\in[\pm 0.05]$ (Brown et al., 2012). Templates that correspond to sources with a signal duration less than 0.15 seconds (starting from $20\,$Hz) are excluded due to the difficulty in separating candidates arising from these templates from populations of instrumental glitches (Dal Canton & Harry, 2017). Consequently, the total mass boundary of the search depends strongly on the “effective spin” (Racine, 2008; Ajith et al., 2011),

This dependence is visible in the distribution of the approximately $400,000$ templates required to cover the space shown in Fig. 1. A dotted line in Fig. 1 denotes the upper boundary of the O1 analysis performed in Abbott et al. (2016a). For binaries with total mass greater than $4\,M_{\odot}$, we use the spinning effective-one-body model (SEOBNRv4) (Taracchini et al., 2014; Bohé et al., 2016) as template gravitational waveforms. For sources with total masses less than $4M_{\odot}$ we use TaylorF2 post-Newtonian waveforms with phasing accurate to 3.5 post-Newtonian order and the dominant amplitude evolution (Sathyaprakash & Dhurandhar, 1991; Droz et al., 1999; Blanchet, 2002; Faye et al., 2012). Our choice of template bank discretization causes less than a $10\%$ loss in detection rate for any source within the boundaries of the template bank. Our search assumes that the source can be adequately described by only the dominant gravitational-wave mode, two component masses, non-precessing spins, and negligible eccentricity.

2 Creation and Ranking of Candidate Events

For each template and each detector, we calculate the matched filter signal-to-noise ratio (SNR) as a function of time $\rho(t)$ (Allen et al., 2012). The template bank is divided into 15 equal sized sub-banks based on the chirp mass $\mathcal{M}=(m_{1}m_{2})^{3/5}/(m_{1}+m_{2})^{1/5}$ of each template. A single-detector “trigger” is a peak in the SNR time series that is greater than 4 and larger than any other peaks within 1s. For each sub-bank, the loudest 100 triggers (by $\rho$) are recorded in $\sim 1$s fixed time windows. This method has been shown to improve search sensitivity, while making the rate of single-detector triggers manageable (Nitz et al., 2018b). We have found this choice of sub-banks to be an effective method to ensure the analysis can concurrently record triggers from separate regions of parameter space that respond differently to instrumental noise. Other choices are possible.

We use the data-quality segments provided by the Gravitational-Wave Open Science Center to exclude triggers that occur in times when there are problems with the detectors’ data quality (Abbott et al., 2016b, 2018). In addition, very loud transient glitches, corresponding to $>100\sigma$ deviations from Gaussian noise, are excised from the strain data according to the procedure of Usman et al. (2016) before calculation of the SNR time series. However, there remain many types of transient non-Gaussian noise in the LIGO data which produce triggers with large values of SNR (Nuttall et al., 2015; Abbott et al., 2016b, 2018).

For every trigger with $\rho>5.5$ we calculate the signal consistency test, $\chi^{2}_{r}$, introduced in Allen (2005). The statistic $\chi^{2}_{r}$ divides the matched filter into frequency bands and checks that the contribution from each band is consistent with the expected signal. The statistic takes values close to unity when the data contains either Gaussian noise or the expected signal and larger values for many types of transient glitches. We impose the SNR limit as the $\chi^{2}_{r}$ test is generally non-informative when $\rho<5.5$. The $\chi^{2}_{r}$ value is used to re-weight the SNR $\rho$ as (Babak et al., 2013)

For single-detector triggers from templates with total mass greater than 40$M_{\odot}$ we apply an additional test, $\chi^{2}_{r,sg}$, that determines if the detector output contains power at higher frequencies than the maximum expected frequency content of the gravitational-wave signal (Nitz, 2018). This test is only applied for higher mass systems, since these templates are shorter in duration and more difficult to separate from instrumental noise. For other systems, we set $\chi^{2}_{r,sg}=1$. Using this statistic, we apply a further re-weighting as

3 Statistical Significance

The statistical significance of candidate events is estimated by measuring empirically the rate of false alarms (FAR). To measure the noise background rate, we generate additional analyses by time shifting the data from one instrument with respect to the other by multiples of 100 ms. Since this time shift is greater than the maximum astrophysical time of flight between observatories, any candidates produced in these analyses are false alarms. This time shift is much greater than the auto-correlation length of our template waveforms of $\mathcal{O}$(1ms). The time-slid analyses are produced following the same procedure as the search; This is a key requirement for our analysis to produce valid statistical results (Abbott et al., 2016c). The equivalent of more than 50,000 years of observing time can be generated from 5 days of data.

Evaluating Candidates based on the Astrophysical Population

We find two candidate events with FAR $<1$ per $50\,000$ years, corresponding to GW150914 and GW151226. Although FAR does not give the probability that an event is an astrophysical signal, we can be confident that these events were not caused by chance coincidence between the detectors. It is possible that these events were caused by a correlated source between the detectors. However, detailed followup studies of GW150914 and GW151226 found no correlated noise sources between the detectors that could be mistaken for a gravitational wave (Abbott et al., 2016b, d).

Results

The results presented here are generated using the data from the first observing run of Advanced LIGO which ran from September 12, 2015 to January 19, 2016. We divide the 16 kHz LIGO open data into 9 consecutive periods of time and search each time period independently so that each analysis contains roughly five days of observing time. This time interval is set by the disk and memory requirements of the search pipeline, but it is sufficient to estimate the FAR of candidate events to better than 1 in 50,000 years. It is possible to combine these time intervals during the analysis to improve this limit, but we have not done so here. Our analysis is restricted to times marked as observable by the metadata provided by the Gravitational-Wave Open Science Center. After accounting for times which are marked as not analyzable, there remain $\sim 48.1$ days of data when both the Hanford and Livingston LIGO instruments were operating.

2 Revisiting LVT151012

LVT151012 was first announced in Abbott et al. (2016c), with a FAR of 1 per 2.3 years. Our improved methods yield a false alarm rate for LVT151012 of 1 per 24 years. Restricting attention to our selected BBH region, which is consistent with the other observed binary black hole mergers, gives a FAR for LVT151012 in this region alone of 1 per 446 years. We combine this FAR with our conservative estimate of the rate of detections to estimate that 99.92% of binary black hole merger candidates at least as significant as LVT151012 are astrophysical in origin. We also estimate the probability that specifically LVT151012 is astrophysical in origin to be 97.59$\%$.

Data Release

Discussion

We present a full catalog of gravitational-wave events and candidates from a PyCBC-based, templated, matched-filter search of the LIGO O1 open data. Our analysis represents an improvement over that of Abbott et al. (2016a, i) by using improved ranking of candidates by considering phase, amplitude and time delay consistency, an improved background model and a template bank targeting a wider range of sources (Nitz et al., 2017; Nitz, 2018; Dal Canton & Harry, 2017). We independently verify the discovery of GW150914 and GW151226 and report an improved significance of the candidate event LVT151012, which we claim should be viewed as a confident detection. Apart from these three signals, none of the other candidate events are individually significant in our analysis. All of these candidates are listed in our catalog available at www.github.com/gwastro/1-ogc, along with tools for exploring and using it. Complete gravitational-wave event catalogs of this nature will become important tools in multi-messenger astronomy.

A larger data set from the second observing run of LIGO and Virgo already exists. Individual detections have been published, and short periods of data around the detections are available publicly. However, the bulk of this data has not yet been released publicly. It will be possible to create a similar open catalog with the most up-to-date analysis tools when these data are released.

References