1 Draft version May 21, 2020 2 Typeset using LATEX twocolumn style in AASTeX63

3 GW190814: Gravitational Waves from the Coalescence of a 23 M Black Hole 4 with a 2.6 M Compact Object

5 LIGO Scientific Collaboration and Virgo Collaboration

6

7 (Dated: May 21, 2020)

8 ABSTRACT

9 We report the observation of a compact binary coalescence involving a 22.2 – 24.3 M black hole and 10 a compact object with a mass of 2.50 – 2.67 M (all measurements quoted at the 90% credible level). 11 The gravitational-wave signal, GW190814, was observed during LIGO’s and Virgo’s third observing 12 run on August 14, 2019 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector 2 +41 13 network. The source was localized to 18.5 deg at a distance of 241−45 Mpc; no electromagnetic 14 counterpart has been confirmed to date. The source has the most unequal mass ratio yet measured +0.008 15 with gravitational waves, 0.112−0.009, and its secondary component is either the lightest black hole 16 or the heaviest neutron star ever discovered in a double compact-object system. The dimensionless 17 spin of the primary black hole is tightly constrained to 0.07. Tests of general relativity reveal no ≤ 18 measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at −3 −1 19 high confidence. We estimate a merger rate density of 1–23 Gpc yr for the new class of binary 20 coalescence sources that GW190814 represents. Astrophysical models predict that binaries with mass 21 ratios similar to this event can form through several channels, but are unlikely to have formed in 22 globular clusters. However, the combination of mass ratio, component masses, and the inferred merger 23 rate for this event challenges all current models for the formation and mass distribution of compact- 24 object binaries.

25 1. INTRODUCTION 48 The first six months of the third observing run (O3) 49 were completed between April 1 and September 30, 26 The first two observing runs (O1 and O2) with 50 2019. The LVC recently reported on the discovery of 27 Advanced LIGO (Aasi et al. 2015) and Advanced 51 GW190425, the coalescence signal of what is most likely 28 Virgo (Acernese et al. 2015) opened up the field of 52 a BNS with unusually large chirp mass and total mass 29 gravitational-wave astrophysics with the detection of 53 compared to the Galactic BNSs known from radio pul- 30 the first binary black hole (BBH) coalescence signal, 54 sar observations (Abbott et al. 2020a). Another dis- 31 GW150914 (Abbott et al. 2016a). Another nine such 55 covery from O3 is that of GW190412, the first BBH 32 events (Abbott et al. 2016b, 2019a) were discovered by 56 33 coalescence with an unequivocally unequal mass ratio the LIGO Scientific and Virgo Collaborations (LVC) +0.12 57 q = m2/m1 of 0.28 (all measurements are reported 34 during this period, and additional events were reported −0.06 58 as symmetric 90% credible intervals around the median 35 by independent groups (Zackay et al. 2019a,b; Venumad- 59 of the marginalized posterior distribution, unless other- 36 hav et al. 2019; Nitz et al. 2020). The first binary neu- 60 wise specified). It is also the first event for which higher- 37 tron star (BNS) coalescence signal, GW170817, was dis- 61 multipole gravitational radiation was detected with high 38 covered during the second of these observing campaigns 62 significance (Abbott et al. 2020d). 39 (Abbott et al. 2017a, 2019b). It proved to be a multi- 63 Here we report on another O3 detection, GW190814, 40 messenger source with emission across the electromag- 64 the signal of a compact binary coalescence with the 41 netic spectrum (Abbott et al. 2017b), with implications 65 42 most unequal mass ratio yet measured with gravitational for the origin of short gamma-ray bursts (Abbott et al. +0.008 66 waves: q = 0.112 . The signal was first identified 43 2017c), the formation of heavy elements (Chornock et al. −0.009 67 in data from two detectors, LIGO Livingston and Virgo, 44 2017; Tanvir et al. 2017; Abbott et al. 2017d; Rosswog 68 on 2019 August 14, 21:11:00 UTC. Subsequent analysis 45 et al. 2018; Kasliwal et al. 2019; Watson et al. 2019), 69 of data from the full three-detector network revealed a 46 cosmology (Abbott et al. 2017e, 2019c) and fundamen- 70 merger signal with signal-to-noise ratio (SNR) of 25. 47 tal physics (Abbott et al. 2017c, 2019d). ' 2

71 The primary component of GW190814 is conclusively +1.1 Normalized energy 72 a black hole (BH) with mass m1 = 23.2 M . Its di- −1.0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 73 mensionless spin magnitude is constrained to χ1 0.07. +0.08 ≤ 74 The nature of the 2.59−0.09 M secondary component is 75 unclear. The lack of measurable tidal deformations and 76 the absence of an electromagnetic counterpart are con- LIGO Hanford 77 sistent with either a neutron star (NS) or a BH given the +41 100 78 event’s asymmetric masses and distance of 241−45 Mpc. 79 However, we show here that comparisons with the maxi- 80 mum NS mass predicted by studies of GW170817’s rem- 81 nant, by current knowledge of the NS equation of state, 82 and by electromagnetic observations of NSs in binary 10 83 systems indicate that the secondary is likely too heavy 84 to be a NS. Either way, this is an unprecedented source LIGO Livingston 85 because the secondary’s well-constrained mass of 2.50– 100 86 2.67 M makes it either the lightest BH or the heaviest 87 NS ever observed in a double compact-object system. 88 As in the case of GW190412, we are able to measure Frequency (Hz) 89 the presence of higher multipoles in the gravitational ra- 90 diation, and a set of tests of general relativity with the 10 91 signal reveal no deviations from the theory. Treating 92 this event as a new class of compact binary coalescences, Virgo −3 −1 93 we estimate a merger rate density of 1–23 Gpc yr for 100 94 GW190814-like events. Forming coalescing compact bi- 95 naries with this unusual combination of masses at such a 96 rate challenges our current understanding of astrophys- 97 ical models. 98 We report on the status of the detector network and 10 10 8 6 4 2 0 99 the specifics of the detection in Sections 2 and 3. In − − − − − 100 Section 4, we estimate physical source properties with Time (seconds) from 2019-08-14 21:10:39 UTC 101 a set of waveform models, and we assess statistical and 102 systematic uncertainties. Tests of general relativity are Figure 1. Time–frequency representations (Chatterji et al. 103 described in Section 5. In Section 6, we calculate the 2004) of data containing GW190814, observed by LIGO Han- 104 merger rate density and discuss implications for the na- ford (top), LIGO Livingston (middle), and Virgo (bottom). Times are shown relative to 2019 August 14, 21:10:39 UTC. 105 ture of the secondary component, compact binary for- Each detector’s data are whitened by their respective noise 106 mation and cosmology. Section 7 summarizes our find- amplitude spectral density and a Q-transform is calculated. 107 ings. The colorbar displays the normalized energy reported by the Q-transform at each frequency. These plots are not used in

108 2. DETECTOR NETWORK our detection procedure and are for visualization purposes only. 109 At the time of GW190814, LIGO Hanford, LIGO Liv- 110 ingston and Virgo were operating with typical O3 sen- 122 of analyzed frequencies. A time–frequency representa- 111 sitivities (Abbott et al. 2020a). Although LIGO Han- 123 tion (Chatterji et al. 2004) of the data from all three 112 ford was in a stable operating configuration at the time 124 detectors around the time of the signal is shown in Fig- 113 of GW190814, the detector was not in observing mode 125 ure1. 114 due to a routine procedure to minimize angular noise 126 We used validation procedures similar to those used 115 coupling to the strain measurement (Kasprzack & Yu 127 to vet previous gravitational-wave events (Abbott et al. 116 2017). This same procedure took place at LIGO Han- 128 2016c, 2019a). Overall we found no evidence that instru- 117 ford around the time of GW170608; we refer the reader 129 mental or environmental disturbances (Effler et al. 2015) 118 to Abbott et al.(2017f) for details of this procedure. 130 could account for GW190814. However, we did identify 119 Within a 5 min window around GW190814, this pro- 131 low-frequency transient noise due to scattered light at 120 cedure was not taking place, therefore LIGO Hanford 132 LIGO Livingston, a common source of noise in all three 121 data for GW190814 are usable in the nominal range 3

133 interferometers (Nuttall 2018). Scattered light features 184 ization computed using the rapid Bayesian algorithm 134 in the strain data are produced when a small fraction 185 BAYESTAR (Singer & Price 2016) that is shown in 135 of the main laser beam reflects off a moving surface and 186 Figure2. The event was initially classified as “Mass- 136 is phase modulated before recombining with the main 187 Gap” (Kapadia et al. 2020; LIGO Scientific Collabora- 137 beam. This recombination can result in excess noise 188 tion, Virgo Collaboration 2019b), implying that at least 138 with the morphology of arches in the time–frequency 189 one of the binary merger components was found to have 139 plane; the frequency of this noise is determined by the 190 a mass between 3–5 M in the low-latency analyses. 140 velocity of the moving surface (Accadia et al. 2010). 191 Other low-latency searches, including the matched- 141 Thunderstorms near LIGO Livingston around the time 192 filtering based MBTA (Adams et al. 2016) and Py- 142 of GW190814 resulted in acoustic noise coupling to the 193 CBC (Usman et al. 2016; Nitz et al. 2017, 2018, 2019) 143 detector and caused features in the strain data asso- 194 pipelines, could not detect the event at the time as its 144 ciated with scattered light (Abbott et al. 2019a). In 195 SNR in Virgo data was below their single-detector detec- 145 this instance, this form of noise affects frequencies up 196 tion thresholds, although a test version of MBTA with 146 to 30 Hz from roughly 22 s to 8 s before and 0.2 s to 197 a lower SNR threshold did identify the event. 147 1.5 s after the detected time of GW190814, as seen in the 198 Shortly thereafter, reanalyses including LIGO Han- 148 middle panel of Figure1. Since this noise could bias the 199 ford data were performed using GstLAL and PyCBC. 149 estimation of GW190814’s source parameters, we used a 200 A coincident gravitational-wave signal was identified in 150 starting frequency of 30 Hz to analyse LIGO Livingston 201 all three detectors by both searches, with SNR 21.6 in 151 data. Virgo was operating nominally and there are no 202 LIGO Livingston, 10.6 in LIGO Hanford, and 4.5 in 152 quality issues in the Virgo data. 203 Virgo data (as measured by GstLAL, consistent with 153 The LIGO and Virgo detectors are calibrated by pho- 204 SNRs reported by PyCBC). Results of these 3-detector 154 ton pressure from modulated auxiliary lasers inducing 205 analyses were reported in a GCN Circular within 2.3 155 test-mass motion (Karki et al. 2016; Viets et al. 2018; 206 hours of the time of the event (LIGO Scientific Col- 156 Acernese et al. 2018). Over the frequency range 20– 207 laboration, Virgo Collaboration 2019c,d), providing a 157 2048 Hz, the maximum 1σ calibration uncertainties for 208 3-detector localization (Singer & Price 2016) constrain- 158 strain data used in the analysis of GW190814 were 6% in 209 ing the distance to 220–330 Mpc and the sky area to 2 159 amplitude and 4 deg in phase for LIGO data, and 5% in 210 38 deg at the 90% credible level. Another GCN Cir- 160 amplitude and 7 deg in phase for Virgo data. These cali- 211 cular (LIGO Scientific Collaboration, Virgo Collabora- 161 bration uncertainties are propagated into the parameter 212 tion 2019e) sent 13.5 hours after the event updated the 162 estimation reported in Section4 via marginalization. 213 source localization to a distance of 215–320 Mpc, the 2 214 sky area to 23 deg , and the source classification to 163 3. DETECTION 215 “NSBH” (Kapadia et al. 2020; LIGO Scientific Collabo- 216 ration, Virgo Collaboration 2019b), indicating that the 164 3.1. Low-latency Identification of a Candidate Event 217 secondary had a mass below 3 M . These updated sky 165 GW190814 was first identified on 2019 August 14, 218 localizations are also shown in Figure2. The two dis- 166 21:11:00 UTC as a loud two-detector event in LIGO 219 joint sky localizations arise because the low SNR in the 167 Livingston and Virgo data (SNR 21.4 and 4.3) by the 220 Virgo detector (4.5) means that the data are consistent 168 low-latency GstLAL matched-filtering search pipeline 221 with two different signal arrival times in that detector. 169 for coalescing binaries (Cannon et al. 2012; Privitera 170 et al. 2014; Messick et al. 2017; Hanna et al. 2020; 222 3.2. Multi-messenger Follow-up 171 Sachdev et al. 2019). Matched-filtering searches use 172 banks (Sathyaprakash & Dhurandhar 1991; Blanchet 223 Several external groups performed multi-messenger 173 et al. 1995; Owen 1996; Owen & Sathyaprakash 1999; 224 follow-up of the source with observations across the elec- 174 Damour et al. 2001; Blanchet et al. 2005; Cokelaer 225 tromagnetic spectrum (e.g., Lipunov et al. 2019; Gomez 175 2007; Harry et al. 2009; Brown et al. 2013; Ajith et al. 226 et al. 2019; Antier et al. 2020; Andreoni et al. 2020; 176 2014; Harry et al. 2014; Capano et al. 2016b; Indik 227 Dobie et al. 2019; Watson et al. 2020; Ackley et al. 177 et al. 2018; Roy et al. 2017, 2019) of modeled gravi- 228 2020; Vieira et al. 2020) and with neutrino observa- 178 tational waveforms (Arun et al. 2009; Blanchet 2014; 229 tions (e.g., Ageron et al. 2019; The IceCube Collabo- 179 Buonanno & Damour 1999; Boh´eet al. 2017; P¨urrer 230 ration 2019). No counterpart candidates were reported. 180 2016) as filter templates. A Notice was issued through 231 The non-detection is consistent with the source’s highly 181 NASA’s Gamma-ray Coordinates Network (GCN) 20 232 unequal mass ratio and low primary spin (LIGO Scien- 182 min later (LIGO Scientific Collaboration, Virgo Col- 233 tific Collaboration, Virgo Collaboration 2019d,e). Ten- 183 laboration 2019a) with a two-detector source local- 234 tative constraints placed by multi-messenger studies on 4

5° 235 the properties of the system, such as the ejecta mass and 60◦ 236 maximum primary spin (Andreoni et al. 2020; Ackley 237 et al. 2020; Kawaguchi et al. 2020; Coughlin et al. 2020) 30 238 or the circum-merger density (Dobie et al. 2019) assum- ◦ N 239 ing a neutron-star–black-hole (NSBH) source, may need E 240 to be revisited in light of the updated source parameters 0◦ 241 we present in Sec. 4.1. 4h 0h 20h BAYESTAR LV 242 3.3. Significance BAYESTAR HLV 30◦ 30◦ − − Latest Circular 243 The significance of GW190814 was estimated by Combined PHM 244 follow-up searches using improved calibration and re- 60◦ − 245 fined data-quality information that are not available in Figure 2. Posterior distributions for the sky location of 246 low latency. They also used longer stretches of data for GW190814. The contours show the 90% credible interval for 247 better precision (Abbott et al. 2016b,c). With LIGO a LIGO Livingston–Virgo (blue) and LIGO Hanford–LIGO 248 Hanford data being usable but not in nominal observing Livingston–Virgo (orange) detector network based on the 249 mode at the time of GW190814, we used only data from rapid localization algorithm BAYESTAR (Singer & Price 250 the LIGO Livingston and Virgo detectors for significance 2016). The sky localization circulated 13.5 hours after the 251 estimation. GW190814 was identified as a confident de- event, based on a LIGO Hanford–LIGO Livingston–Virgo 252 tection in analyses of detector data collected over the analysis with the LALInference stochastic sampling soft- 253 period from August 7 to August 15, 2019 by the two in- ware (Veitch et al. 2015), is shown in green. The purple contour indicates the final sky localization as presented in 254 dependent matched-filtering searches GstLAL and Py- this paper, which constrains the source to within 18.5 deg2 255 CBC, with SNR values consistent with the low-latency at 90% probability. 256 analyses. The production version of PyCBC for O3 es- 257 timates significance only for events that are coincident 286 GW190814 by PyCBC were indeed confirmed to be co- 258 in the LIGO Hanford and LIGO Livingston detectors, 287 incidences of the candidate event itself in LIGO Liv- 259 and therefore an extended version (Davies et al. 2020) 288 ingston with random noise events in Virgo. The stated 260 was used for GW190814 in order to enable the use of 289 background estimates are therefore conservative (Ca- 261 Virgo data in significance estimation. 290 pano et al. 2016a). We also estimate the background 262 GstLAL and PyCBC use different techniques for es- 291 excluding the candidate from the calculation, a proce- 263 timating the noise background and methods of ranking 292 dure that yields a mean-unbiased estimation of the dis- 264 gravitational-wave candidates. Both use results from 293 tribution of noise events (Capano et al. 2016a; Abbott 265 searches over non time-coincident data to improve their 294 et al. 2016d). In this case, with GstLAL we found a 266 noise background estimation (Privitera et al. 2014; Mes- 5 295 FAR of < 1 in 10 yr while with PyCBC we found a 267 sick et al. 2017; Usman et al. 2016). Using data from 4 296 FAR of < 1 in 4.2 10 yr. With both pipelines iden- 268 the first six months of O3 and including all events dur- × 297 tifying GW190814 as more significant than any event in 269 ing this period in the estimation of noise background, 298 the background, the FARs assigned are upper bounds. 270 GstLAL estimated a false-alarm rate (FAR) of 1 in 3 299 When data from LIGO Hanford were included, 271 1.3 10 yr for GW190814. Using data from the 8-day × 300 GW190814 was also identified by the unmodelled co- 272 period surrounding GW190814 and including this and 301 herent Wave Burst (cWB) search that targets generic 273 all quieter events during this period in noise background 302 gravitational-wave transients with increasing frequency 274 estimation, the extended PyCBC pipeline (Davies et al. 303 over time without relying on waveform models (Kli- 275 2020) estimated a FAR for the event of 1 in 8.1 yr. 304 menko et al. 2008, 2016; Abbott et al. 2016e). We found 276 The higher FAR estimate from PyCBC can be at- 3 305 a FAR of < 1 in 10 yr of observing time against the 277 tributed to the event being identified by the pipeline 306 noise background from LIGO Hanford and LIGO Liv- 278 as being quieter than multiple noise events in Virgo 307 ingston data, consistent with the other searches. 279 data. As PyCBC estimates background statistics using 280 non-coincident data from both detectors, these louder 308 4. PROPERTIES OF GW190814 281 noise events in Virgo data can form chance coincidences 282 with the signal in LIGO Livingston data and elevate 309 We infer the physical properties of GW190814 using a 283 the noise background estimate for coincident events, es- 310 coherent Bayesian analysis of the data from LIGO Liv- 284 pecially when considering shorter data periods. All esti- 311 ingston, LIGO Hanford and Virgo following the method- 285 mated background events that were ranked higher than 312 ology described in Appendix B of Abbott et al.(2019a). 5

EOBNR PHM Phenom PHM Combined +1.0 +1.3 +1.1 Primary mass m1/M 23.2−0.9 23.2−1.1 23.2−1.0 +0.08 +0.09 +0.08 Secondary mass m2/M 2.59−0.08 2.58−0.10 2.59−0.09 +0.008 +0.009 +0.008 Mass ratio q 0.112−0.008 0.111−0.010 0.112−0.009 +0.06 +0.06 +0.06 Chirp mass /M 6.10−0.05 6.08−0.05 6.09−0.06 M +0.9 +1.2 +1.0 Total mass M/M 25.8−0.8 25.8−1.0 25.8−0.9 +1.0 +1.2 +1.1 Final mass Mf /M 25.6−0.8 25.5−1.0 25.6−0.9

Upper bound on primary spin magnitude χ1 0.06 0.08 0.07 +0.059 +0.061 +0.060 Effective inspiral spin parameter χeff 0.001 0.005 0.002 −0.056 − −0.065 − −0.061 Upper bound on effective precession parameter χp 0.07 0.07 0.07 +0.02 +0.02 +0.02 Final spin χf 0.28−0.02 0.28−0.03 0.28−0.02

+40 +39 +41 Luminosity distance DL/Mpc 235−45 249−43 241−45 +0.008 +0.008 +0.009 Source redshift z 0.051−0.009 0.054−0.009 0.053−0.010 +0.3 +0.2 +0.3 Inclination angle Θ/rad 0.9−0.2 0.8−0.2 0.8−0.2

+0.1 +0.1 +0.1 Signal to noise ratio in LIGO Hanford ρH 10.6−0.1 10.7−0.2 10.7−0.2 +0.09 +0.09 +0.10 Signal to noise ratio in LIGO Livingston ρL 22.21−0.15 22.16−0.17 22.18−0.17 +0.2 +0.2 +0.2 Signal to noise ratio in Virgo ρV 4.3−0.5 4.1−0.6 4.2−0.6 +0.1 +0.1 +0.1 Network Signal to noise ratio ρHLV 25.0−0.2 24.9−0.2 25.0−0.2 Table 1. Source properties of GW190814: We report the median values along with the symmetric 90% credible intervals for the SEOBNRv4PHM (EOBNR PHM) and IMRPhenomPv3HM (Phenom PHM) waveform models. The primary spin magnitude and the effective precession is given as the 90% upper limit. The inclination angle is folded to [0, π/2]. The last column is the result of combining the posteriors of each model with equal weight. The sky location of GW190814 is shown in Figure2.

313 Results presented here are obtained using 16 s of data 337 For the NSBH analyses, we use BBH wave- 314 around the time of detection. We use a low-frequency 338 form models augmented with tidal effects (Matas 315 cutoff of 20 Hz for LIGO Hanford and Virgo and 30 Hz 339 et al. 2020; Thompson et al. 2020). When 316 for LIGO Livingston for the likelihood evaluations, and 340 sampling the parameter space with the SEOB- 317 we choose uninformative and wide priors, as defined in 341 NRv4 ROM NRTidalv2 NSBH (Matas et al. 2020) 318 Appendix B.1 of Abbott et al.(2019a). The LALInfer- 342 and IMRPhenomNSBH (Thompson et al. 2020) wave- 319 ence stochastic sampling software (Veitch et al. 2015) is 343 form models, we obtained posterior distributions for 320 the primary tool used to sample the posterior distribu- 344 the secondary component’s tidal deformability Λ2 that 321 tion. A parallelized version of the parameter estimation 345 are uninformative relative to a uniform prior in Λ2 ∈ 322 software bilby (pbilby; Smith & Ashton 2019; Ashton 346 [0, 3000]. The absence of a measurable tidal signature is 323 et al. 2019) is used for computationally expensive signal 347 consistent with the highly unequal mass ratio (Foucart 324 models. The power spectral density used in the likeli- 348 et al. 2013; Kumar et al. 2017) and with the relatively 325 hood calculations is a fair draw estimate calculated with 349 large secondary mass (Flanagan & Hinderer 2008). The 326 BayesWave (Cornish & Littenberg 2015; Littenberg & 350 large asymmetry in the masses implies that the binary 327 Cornish 2015a). 351 will merge before the neutron star is tidally disrupted for 328 This signal is analyzed under two different assump- 352 any expected NS equation of state (Foucart et al. 2013). 329 tions: that it represents a BBH, or that it represents a 353 Given that the signal carries no discernible information 330 NSBH. For the BBH analyses, two different waveform 354 about matter effects, here we present quantitative re- 331 families are used, one based on the effective-one-body 355 sults only from BBH waveform models. 332 approach (EOBNR; Boh´eet al. 2017; Babak et al. 2017; 356 Our primary analyses include the effect of subdom- 333 Cotesta et al. 2018; Ossokine et al. 2020) and the other 357 inant multipole moments in precessing waveform tem- 334 on a phenomenological approach (Phenom; Khan et al. 358 plate models (PHM): IMRPhenomPv3HM (Phenom 335 2016; Husa et al. 2016; London et al. 2018; Khan et al. 359 PHM; Khan et al. 2019; Khan et al. 2020) from the phe- 336 2019; Khan et al. 2020). 360 nomenological family and SEOBNRv4PHM (EOBNR 6

361 PHM; Babak et al. 2017; Ossokine et al. 2020) from the 1 362 EOBNR family. Analyses that assume the spins are 363 aligned with the orbital angular momentum were also 364 performed, either including (Phenom/EOBNR HM) or 365 excluding (Phenom/EOBNR) the effect of subdominant 366 multipole moments. 2.8

367 4.1. Properties 2.7

368 From the 300 observed cycles above 20 Hz, we 2.6 ∼ 369

are able to tightly constrain the source properties of ] 2.5

370 GW190814. Our analysis shows that GW190814’s M [

371 source is a binary with an unequal mass ratio q = 2 2.4

+0.008 m Combined PHM 372 0.112−0.009, with individual source masses m1 = +1.1 +0.08 2.3 EOBNR PHM 373 23.2−1.0 M and m2 = 2.59−0.09 M , as shown in Phenom PHM 374 Figure3. A summary of the inferred source prop- 2.2 Abbott+ 2018 Mmax 375 erties is given in Table1. We assume a standard 2.1 Farr+Chatziioannou 2020 Mmax 376 flat ΛCDM cosmology with Hubble constant H0 = −1 −1 2.0 377 67.9 km s Mpc (Ade et al. 2016). 20 21 22 23 24 25 26 27 378 We report detailed results obtained from the two pre- m1[M ]

379 cessing BBH signal models including subdominant mul- 380 tipole moments: Phenom PHM and EOBNR PHM. In Figure 3. The posterior distribution of the primary and sec- 381 order to compare the template models, we compute their ondary source masses for two waveform models that include 382 Bayes factor (log10 ). We find no significant evidence precession and subdominant multipole moments. The pos- B 383 that one waveform family is preferred over the other as terior distribution resulting from combining their samples 384 the Bayes factor between Phenom PHM and EOBNR is also shown. Each contour, as well as the colored hori- zontal and vertical lines, shows the 90% credible intervals. 385 PHM is log10 1.0. As a result, we combine the B' The right panel compares m2 to predictions for the maxi- 386 posterior samples with equal weight, in effect marginal- mum NS mass, Mmax (see Section6). The posterior distri- 387 izing over a discrete set of signal models with a uniform bution for Mmax from the spectral equation of state analysis 388 probability. This is shown in the last column of Table1, of GW170817 (Abbott et al. 2018) is shown in orange, and 389 and we refer to these values throughout the paper unless the empirical Mmax distribution from the population model 390 stated otherwise. of Farr & Chatziioannou(2020) is shown in green. The grey 391 We find that the secondary mass lies in the dashed line and shading represent the measured mass of the 392 range 2.50– 2.67 M . This inferred secondary mass heaviest pulsar in the Galaxy (median and 68% confidence in- terval; Cromartie et al. 2019). The solid grey band at 2.3 M 393 exceeds the bounds of the primary component in is the upper bound on Mmax from studies of GW170817’s 394 GW190425 (1.61–2.52 M ; Abbott et al. 2020a) and the +0.10 merger remnant. 395 most massive known pulsar in the Galaxy: 2.14−0.09 M 396 at 68.3% credible interval (Cromartie et al. 2019). Fur- +0.06 407 chirp mass is well constrained to 6.09−0.06 M . The in- 397 thermore, the secondary is more massive than bounds +0.008 408 ferred mass ratio q = 0.112 makes GW190814 only 398 on the maximum NS mass from studies of the rem- −0.009 409 the second gravitational-wave observation with a signif- 399 nant of GW170817, and from theoretical (Abbott et al. 410 icantly unequal mass ratio (Abbott et al. 2019a, 2020d). 400 2018) and observational estimates (Farr & Chatziioan- 411 Given that this system is in a region of the parame- 401 nou 2020). The inferred secondary mass is comparable 412 ter space that has not been explored via gravitational- 402 to the putative BH remnant mass of GW170817 (Abbott 413 wave emission previously, we test possible waveform sys- 403 et al. 2019b). 414 tematics by comparing the Phenom and EOB waveform 404 The primary object is identified as a BH based on its +1.1 415 families. Differences in the inferred secondary mass are 405 measured mass of 23.2−1.0 M . Due to accurately ob- 416 shown in Figure4. The results indicate that the inferred 406 serving the frequency evolution over a long inspiral, the 417 secondary mass is robust to possible waveform system- 418 atics, with good agreement between the Phenom PHM 1 In the co-precessing frame the EOBNR model in-419 and EOBNR PHM signal models. Signal models that cludes the (l, m) = (2, ±2), (2, ±1), (3, ±3), (4, ±4) and 420 exclude higher multipoles or precession do not constrain (5, ±5) multipoles, and the Phenom model includes the (2, ±2), (2, ±1), (3, ±3), (3, ±2), (4, ±4) and (4, ±3) multipoles. 421 the secondary mass as well. 7

10.0 452 and the first gravitational-wave measurement which con- EOBNR PHM 453 clusively measures near-zero precession (Abbott et al. EOBNR HM 7.5 454 2019a, 2020a,d). EOBNR 455 By computing the Bayes factor between a precessing Phenom PHM 456 and non-precessing signal model (log10 0.5 in favor 5.0 Phenom HM B ∼ 457 of precession), we find inconclusive evidence for in-plane Phenom 458 spin. This is consistent with the inferred power from 2.5 459 precession SNR ρp (Fairhurst et al. 2019a,b), whose re-

Probability Density 460 covered distribution resembles that expected in the ab- 0.0 461 sence of any precession in the signal; see Figure5. The 2.3 2.5 2.7 2.9 3.1 462 ρp calculation assumes a signal dominated by the ` = 2 m2[M ] 463 mode; however, we have verified that the contribution of

464 higher harmonics to the measurement of spin precession Figure 4. The marginalized posterior distribution for the 465 is subdominant by a factor of 5. The data are therefore secondary mass obtained using a suite of waveform mod- 466 consistent with the signal from a non-precessing system. els. The vertical lines indicate the 90% credible bounds 467 Figure4 shows that signal models including spin- for each waveform model. The labels Phenom/EOBNR 468 precession effects give tighter constraints on the sec- PHM (generic spin directions + higher multipoles), Phe- nom/EOBNR HM (aligned-spin + higher multipoles) and 469 ondary mass compared to their non-precessing equiva- Phenom/EOBNR (aligned-spin, quadrupole only) indicate 470 lents. Signal models that include spin-precession effects the different physical content in each of the waveform mod- 471 can constrain χp, whereas non-precessing signal mod- els. 472 els cannot provide information on in-plane spin com- 473 ponents. In all analyses, we assume a prior equivalent

422 The time delay of a signal across a network of gravi- 474 to spin orientations being isotropically distributed. We 423 tational wave detectors, together with the relative am- 475 find that the data are inconsistent with large χp and 424 plitude and phase at each detector, allows us to mea- 476 consistent with any secondary spin. Therefore, for pre- 425 sure the location of the GW source on the sky (Abbott 477 cessing signal models the allowed q–χeff parameter space 426 et al. 2020b). We localize GW190814’s source to within 478 is restricted, which helps to break the degeneracy (Pois- 2 427 18.5 deg at 90% probability, as shown in Figure2. This 479 son & Will 1995; Baird et al. 2013; Farr et al. 2016; 428 is comparable to the localization of GW170817 (Abbott 480 Baird et al. 2013; Ng et al. 2018). Consequently, the 429 et al. 2017a, 2019a). 481 extra information from constraining χp to small values 430 Spins are a fundamental property of BHs. Their mag- 482 enables a more precise measurement of the secondary 431 nitude and orientation carry information regarding the 483 mass. 432 evolution history of the binary. The effective inspiral 484 The asymmetry in the masses of GW190814 means 433 spin parameter χeff (Damour 2001; Racine 2008; Ajith 485 that the spin of the more massive object dominates con- 434 et al. 2011; Santamar´ıaet al. 2010) contains informa- 486 tributions to χeff and χp. As both χeff and χp are tightly 435 tion about the spin components that are perpendicular 487 constrained, we are able to bound the primary spin of +0.060 436 to the orbital plane. We infer that χeff = 0.002 . 488 GW190814 to be χ1 0.07, as shown in Figure6. This − −0.061 ≤ 437 The tight constraints are consistent with being able to 489 is the strongest constraint on the primary spin for any 438 measure the phase evolution from the long inspiral. 490 gravitational-wave event to date (Abbott et al. 2019a, 439 Orbital precession occurs when there is a significant 491 2020a,d). 440 spin component in the orbital plane of the binary (Apos- 492 The joint posterior probability of the magnitude and 441 tolatos et al. 1994). We parameterize precession by the 493 orientation of χ1 and χ2 are shown in Figure6. De- 442 effective precession spin parameter 0 χp 1 (Schmidt 494 viations from uniform shading indicate a spin property ≤ ≤ 443 et al. 2015). This effect is difficult to measure for face-on 495 measurement. The primary spin is tightly constrained 444 and face-off systems (Apostolatos et al. 1994; Buonanno 496 to small magnitudes, but its orientation is indistinguish- 445 et al. 2003; Vitale et al. 2014, 2017; Fairhurst et al. 497 able from the prior distribution. The spin of the less 446 2019a,b). GW190814 constrains the inclination of the 498 massive object, χ2, remains unconstrained; the poste- +0.3 447 binary to be Θ = 0.8−0.2 rad. Since the system is nei- 499 rior distribution is broadly consistent with the prior. 448 ther face-on nor face-off, we are able to put strong con- 500 The final mass Mf and final dimensionless spin χf of +0.04 449 straints on the precession of the system: χp = 0.04−0.03. 501 the merger remnant are estimated under the assump- 450 This is both the strongest constraint on the amount of 502 tion that the secondary is a BH. By averaging several 451 precession for any gravitational-wave detection to date, 503 fits calibrated to numerical relativity (Hofmann et al. 8

0.8 Precession 33-mode 0◦ 0◦ 0.6 Noise distribution 30 30◦ ◦ tilt 0.8 0.4 60 ◦ 0.6 60 ◦ 0.4 0.2

Probabilty Density 0.2 magnitude

90 ◦

0.0 0.0 ◦ 0 2 4 6 8 10 90

ρ

120

◦

Figure 5. Posterior distributions for the precessing SNR, ◦ 120

ρp (green) and the optimal SNR in the (3,3) sub-dominant

150 multipole moment, ρ (orange). The grey dotted line shows ◦

◦

the expected distribution for Gaussian noise. 150

◦ ◦ 180 180

504 2016; Johnson-McDaniel et al. 2016; Healy & Lousto 505 2017; Jim´enez-Forteza et al. 2017), we infer the final +1.1 506 mass and spin of the remnant BH to be 25.6−0.9 M and +0.02 507 0.28−0.02, respectively. The final spin is lower than for Figure 6. Two-dimensional posterior probability for the 508 previous mergers (Abbott et al. 2019a, 2020d), as ex- tilt-angle and spin-magnitude for the primary object (left) 509 pected from the low primary spin and smaller orbital and secondary object (right) based on the Combined sam- ples. The tilt angles are 0◦ for spins aligned and 180◦ for 510 contribution due to the asymmetric masses. spins anti-aligned with the orbital angular momentum. The 511 4.2. Evidence for Higher-order Multipoles tiles are constructed linearly in spin magnitude and the co- sine of the tilt angles such that each tile contains identical 512 The relative importance of a subdominant multipole prior probability. The color indicates the posterior proba- 513 moment increases with mass ratio. Each subdominant bility per pixel. The probabilities are marginalized over the 514 multipole moment has a different angular dependence azimuthal angles. 515 on the emission direction. With significant evidence 516 for multipoles other than the dominant (`, m) = (2, 2) 538 The orthogonal optimal SNR of a subdominant mul- 517 quadrupole, we gain an independent measurement of the 539 tipole is calculated by decomposing each multipole into 518 inclination of the source. This allows for the distance- 540 components parallel and perpendicular to the domi- 519 inclination degeneracy to be broken (Cutler & Flanagan 541 nant harmonic (Mills & Fairhurst 2020; Abbott et al. 520 1994; Abbott et al. 2016f; Usman et al. 2019; Kalaghatgi 542 2020d). We infer that the orthogonal optimal SNR of 521 et al. 2019). Measuring higher-order multipoles there- +1.3 543 the (`, m) = (3, 3) multipole is 6.6−1.4, as shown in Fig- 522 fore gives more precise measurements of source parame- 544 ure5. This is the strongest evidence for measuring a 523 ters (Van Den Broeck & Sengupta 2007a,b; Kidder 2008; 545 subdominant multipole to date (Payne et al. 2019; Ku- 524 Blanchet et al. 2008; Mishra et al. 2016; Kumar et al. 546 mar et al. 2019; Abbott et al. 2020d). 525 2019). 547 Finally, we perform two complementary analyses in- 526 GW190412 was the first event where there was sig- 548 volving time–frequency tracks in the data to provide fur- 527 nificant evidence for higher-order multipoles (Payne 549 ther evidence for the presence of higher multipoles in the 528 et al. 2019; Kumar et al. 2019; Abbott et al. 2020d). 550 signal. In the first approach (also outlined in Abbott 529 GW190814 exhibits stronger evidence for higher-order 551 et al. 2020d, Section 4) we predict the time–frequency 530 multipoles, with log 9.6 in favor of a higher- 10 B' 552 track of the dominant (2, 2) multipole in the LIGO Liv- 531 multipole vs. a pure quadrupole model. The (`, m) = 553 ingston detector (as seen in Figure1, middle panel) from 532 (3, 3) is the strongest subdominant multipole, with 554 an EOBNR HM parameter estimation analysis. This 533 log 9.1 in favor of a signal model including 10 B' 555 analysis collects energies along a time–frequency track 534 both the (`, m) = (2, 2) and (3, 3) multipole moments. 556 which is α f22(t), the (2, 2) multipole’s instantaneous 535 GW190814’s stronger evidence for higher multipoles is × 557 frequency, where α is a dimensionless parameter (Roy 536 expected given its more asymmetric masses and the 558 et al. 2019; Abbott et al. 2020d). We find prominent 537 larger network SNR. 9

On-source Y (α) (modelled approach) 581 investigate if the description of the underlying signal is 8 Off-source Y (α) (modelled approach) 582 incomplete if we do not include contributions from the 6 583 m = 3 multipole in our waveform model. We compute a ) 584

α test statistic, the squared sum of the coherent residuals 4 585 estimated over selected time–frequency tracks parame- Y( 586 terized in terms of the same α parameter defined in the 2 587 previous analysis (Roy et al. 2019; Abbott et al. 2020d). 0 588 Each time–frequency track centered on α includes fre- 100 589 quencies within [α 0.1, α + 0.1] f22(t), and times On-source p-value − × (waveform-agnostic approach) 590 within [tmerger 0.5 s, tmerger 0.03 s], where f22(t) and − − 591 tmerger correspond to the maximum likelihood template

1 592 from the EOBNR parameter estimation analysis. We 10− 593 further compute a background distribution using simu-

p-value 594 lated signals in off-source data (Prodi et al. 2020), and 595 compute p-values for the on-source results as a func- 2 10− 596 tion of α (Figure7, bottom panel). We find a minimum −3 0.5 1.0 1.5 2.0 2.5 597 p–value of 6.8 10 at α = 1.5, providing strong ev- × α 598 idence that the disagreement between the actual event 599 and the EOBNR prediction is because of the absence Figure 7. Top panel: Variation of Y (α), i.e, the energy in 600 of the m = 3 multipoles in the waveform model. The the pixels along the α-th track defined by fα(t) = αf22(t), 601 local minimum near α = 2 is not an indication of the using the modelled approach. The peaks at α = 1 and 1.5 602 m = 4 multipoles, but rather a statistical fluctuation indicate the energies in the m = 2 and m = 3 multipoles, respectively. The grey band indicates the 68% confidence 603 which is consistent with similar behaviour seen for stud- interval on the off-source measurements of Y (α). Bottom 604 ies with simulated signals described in detail in Prodi panel: The variation of p-value of the on-source results, as 605 et al.(2020). a function of α, using the waveform-agnostic approach. The 606 Although the two time–frequency analyses are simi- dip at α = 1.5 is strong evidence of the presence of the 607 lar in motivation, the latter differs from the former in m = 3 mode in the underlying signal. The red dashed line 608 that it is not restricted to data from just one detector, in both panels corresponds to general relativity’s prediction 609 but rather uses the coherent signal energy across the of α = 1.5 for the m = 3 mode. 610 three-detector network. Both analyses point to strong 611 evidence for the presence of higher multipoles in the sig- 559 peaks in Y (α), the energy in the pixels along the α-th 612 nal. 560 track defined in Abbott et al.(2020d), at α = 1 and 1.5, 561 as can be seen from the on-source curve in the top panel 613 562 of Figure7. These peaks correspond to the m = 2 and 5. TESTS OF GENERAL RELATIVITY

563 m = 3 multipole predictions in the data containing the 614 GW190814 is the gravitational-wave event with the 564 signal (on-source data). We also compute a detection 615 most unequal mass ratio to date, and can therefore be 565 statistic β (Roy et al. 2019) of 11.18 for the presence of 616 used to test general relativity (GR) in a region of pa- −4 566 the m = 3 multipole with a p-value of < 2.5 10 , 617 rameter space previously unexplored with strong-field × 567 compared to a background distribution estimated over 618 tests of GR (Abbott et al. 2016g, 2019e,d). The asym- 568 18 hours of data adjacent to the event (off-source data), 619 metric nature of a system excites the higher multipole 569 where the largest background β is 6.88. The signifi- 620 moments of the gravitational signal, which allows us to 570 cant difference between on- and off-source values pro- 621 test the multipolar structure of gravity (Kastha et al. 571 vides much stronger evidence for the presence of higher 622 2018, 2019; Dhanpal et al. 2019; Islam et al. 2020). The 572 multipoles than what is reported for GW190412 (Abbott 623 addition of information from the higher harmonics of a 573 et al. 2020d). 624 signal also breaks certain degeneracies in the description 574 The second analysis uses waveform-agnostic methods 625 of the source, and could potentially enable us to place 575 to reconstruct the signal. It then compares the ob- 626 stronger constraints on certain deviations from GR (Van 576 served coherent signal energy in the LIGO Hanford– 627 Den Broeck & Sengupta 2007b,a). We perform sev- 577 LIGO Livingston–Virgo network of detectors, as iden- 628 eral null tests of GR using GW190814. These tests as- 578 tified by the cWB detection pipeline (Klimenko et al. 629 sume GW190814 is a (quasi-circular) BBH merger as de- 579 2016), with the predictions of a waveform model with- 630 scribed in GR, and look for inconsistencies between the 580 out higher multipoles (EOBNR; Prodi et al. 2020) to 631 observed signal and predictions of the theory. An incon- 10

632 sistency might arise from an incomplete understanding 684 is 1 for a BBH in GR. The posteriors on κs are rela- 633 of the underlying signal (or noise), and could indicate a 685 tively uninformative, and nearly span the prior range 634 non-BBH nature of the signal or a potential departure 686 of [0, 500], with increased support at κs = 0 relative to 635 from GR. 687 the prior. The upper bound of the prior was chosen to 636 First, as a consistency test of the signal reconstruc- 688 accommodate all the objects listed above. The result 637 tion, we subtract from the data the maximum like- 689 shows that GW190814 is consistent with having a BBH 638 lihood compact binary coalescence waveforms, Phe- 690 source described by GR. However, the broad posterior 639 nom (Khan et al. 2016), Phenom HM (Kalaghatgi 691 means that we cannot exclude the possibility that one 640 et al. 2019), Phenom PHM (Khan et al. 2020), and 692 or both components of the source is not a BH. We can 641 EOBNR PHM (Ossokine et al. 2020) and analyze 4 s 693 attempt to understand this result in terms of the spin 642 of the resulting residual data centered around the time 694 measurements for the binary. The measurements of κs 643 of merger with the morphology-independent transient 695 and a non-zero χeff are highly correlated (Krishnendu 644 analysis BayesWave (Cornish & Littenberg 2015; Lit- 696 et al. 2019), and for a system with small χeff the bounds 645 tenberg & Cornish 2015a). We measure the 90% credible 697 on the measured value of κs are weak. 646 upper limit on the coherent SNR, ρ90, and compare it 698 Finally, we investigate the source dynamics of the N 647 to the SNR, ρ90, recovered by analyzing 175 randomly 699 binary through a parameterized test of gravitational 648 selected data segments in surrounding time (off–source 700 waveform generation, where we allow for the coeffi- 649 data) with the same configuration settings. If the resid- 701 cients describing the post-Newtonian inspiral of a BBH 650 ual data are consistent with the noise, we expect ρ90 702 coalescence to deviate away from their predictions in N 651 to be consistent with ρ90. We compute the p-value 703 GR (Arun et al. 2006a,b; Yunes & Pretorius 2009; N 652 by comparing the distribution of ρ90 to ρ90 through 704 Mishra et al. 2010; Cornish et al. 2011; Li et al. 2012; N 653 p = P (ρ90 < ρ90). We obtain p-values of 0.59, 0.82, 705 Meidam et al. 2018). We use an aligned-spin EOB wave- 654 0.82, and 0.75 for Phenom, Phenom HM, Phenom PHM, 706 form without higher modes (EOBNR), and find no de- 655 and EOBNR PHM, respectively. Hence, we find no evi- 707 viations in the post-Newtonian coefficients from their 656 dence for deviations in the behavior of the residual data 708 nominal values in GR. In summary, none of our tests of 657 stream. 709 GR indicate any departure from the predictions of the 658 We also look for deviations in the spin-induced 710 theory, and GW190814 is consistent with the description 659 quadrupole moments of the binary components. Accord- 711 of a compact binary merger in GR. 660 ing to the no-hair conjecture (Carter 1971; Hansen 1974) 661 the multipole moments of a Kerr BH are completely 712 6. ASTROPHYSICAL IMPLICATIONS 662 described by its mass and spin angular momentum. +0.008 713 The highly unequal mass ratio of 0.112−0.009 and un- 663 At leading order in spin, the spin-induced quadrupole +0.08 714 usual secondary mass of 2.59−0.09 M make the source 664 moment scalar is (Hartle 1967; Pappas & Apostolatos 2 3 715 of GW190814 unlike any other compact binary coales- 665 2012), Q = κa m , where (m, a) are the mass and − 716 cence observed so far. The average mass ratio for BBH 666 dimensionless spin of the compact object, and κ is a 717 coalescences detected by the LVC during O1 and O2 is 667 dimensionless deformation parameter characterizing de- 718 0.9 (Roulet & Zaldarriaga 2019), and an inference 668 viations in the spin-induced quadrupole moment. Kerr ' 719 of the underlying population predicted that 99% of de- 669 BHs have κ = 1 (Thorne 1980), while κ 2–14 for NSs ∼ 720 tectable BBHs have mass ratios q 0.5 (Fishbach & 670 (depending on the equation of state) and κ 10–150 ≥ ∼ 721 Holz 2020). However, the paucity of events from O1 671 for spinning boson stars with large self-interaction (Ryan 722 and O2 means that this picture is limited. Indeed, the 672 1997). The deformation parameter can even be negative 723 discovery of GW190412 has already changed the picture 673 for (slowly-rotating, thin-shelled) gravastars (Uchikata 724 substantially (Abbott et al. 2020d). 674 et al. 2016). Hence, an accurate measurement of κ 725 GW190814’s secondary mass lies in the hypothesized 675 sheds light onto the nature of the compact object. For 726 lower mass gap of 2.5–5 M (Bailyn et al. 1998; Ozel¨ 676 compact binaries, the spin-induced quadrupole moment 727 et al. 2010; Farr et al. 2011; Ozel¨ et al. 2012) between 677 terms appear at second post-Newtonian order (Poisson 728 known NSs and BHs. It is heavier than the most mas- 678 1998). For Kerr BHs in GR, κ1 = κ2 = 1, where 729 sive pulsar in the Galaxy (Cromartie et al. 2019), and al- 679 κ1, κ2 are the individual deformation parameters of the 730 most certainly exceeds the mass of the 1.61–2.52 M pri- 680 primary and secondary compact objects in the binary. 731 mary component of GW190425, which is itself an out- 681 Since κ1 and κ2 are strongly degenerate in the gravita- 732 lier relative to the Galactic population of BNSs (Abbott 682 tional waveform, we instead measure a linear symmetric 733 et al. 2020a). On the other hand, it is comparable in 683 combination of these quantities, κs = (κ1 +κ2)/2, which 734 mass to two BH candidates: the 2.7 M merger rem- ' 11

735 nant of GW170817 (Abbott et al. 2019b) and the 2.6– 783 40 M (following our updated knowledge of the BH mass 736 6.1 M compact object (95% confidence interval) dis- 784 distribution); the NS mass range was 1–3 M , and com- 2 737 covered by Thompson et al.(2019). It is also compara- 785 ponent spins are < 0.95. As GW190814 occurred when 738 ble to the millisecond pulsar PSR J1748 2021B (Freire 786 LIGO Hanford was not in nominal observing mode, it is − +0.21 739 et al. 2008), whose mass is claimed as 2.74−0.21M at 787 not included in the production PyCBC results, and we 740 68% confidence. However, this estimate, obtained via 788 use GstLAL results to calculate the merger rate. 741 measurement of the periastron advance, could be inac- 789 We assume a Poisson likelihood over the astrophysical −1/2 742 curate if the system inclination is low or the pulsar’s 790 rate with a single count and we apply a Jeffreys R 743 companion is rapidly rotating (Freire et al. 2008). In 791 prior to obtain rate posteriors. The analysis was done 744 sum, it is not clear if GW190814’s secondary is a BH or 792 using samples from the Phenom PHM posterior and sep- 745 a NS. 793 arately from the EOBNR PHM posterior, producing the 746 GW190814 poses a challenge for our understanding of 794 same result in both cases. We find the merger rate den- +16 −3 −1 747 the population of merging compact binaries. In what 795 sity of GW190814-like systems to be 7−6 Gpc yr . 748 follows, we estimate the merger rate density of the com- 796 As a consistency check, we used the PyCBC search 749 pact binary subpopulation represented by this source, 797 results to calculate an upper limit. Repeating the rate 750 investigate the nature of its secondary component and 798 calculation with a PyCBC-based VT calibration and h i 751 possible implications for the NS equation of state, dis- 799 zero event count, we obtain an upper limit consistent 752 cuss how the system may have formed, and study its 800 (to within 10%) with the upper limit of the merger rate 753 implications for cosmology. 801 estimated using GstLAL search results. We conclude 802 that the uncertainty in our estimate of the rate density 754 6.1. Merger Rate Density 803 for the class of mergers represented by GW190814 is 755 Given the unprecedented combination of component 804 primarily dominated by Poisson statistics. 756 masses found in GW190814, we take the system to rep- 757 resent a new class of compact binary mergers, and use 805 6.2. Nature of the Secondary Component 758 our analysis of its source properties to estimate a merger +1.1 806 The primary mass measurement of 23.2−1.0 M se- 759 rate density for GW190814-like events. Following a 807 curely identifies the heavier component of GW190814 as 760 method described in Kim et al.(2003), we calculate +0.08 808 a BH, but the secondary mass of 2.59−0.09 M may be 761 a simple, single-event rate density estimate accord- R 809 compatible with either a NS or a BH depending on the 762 ing to our sensitivity to a population of systems drawn 810 maximum mass supported by the unknown NS equa- 763 from the parameter-estimation posteriors. As in Ab- 811 tion of state (EOS). The source’s asymmetric masses, 764 bott et al.(2020a), we calculate our surveyed space- 812 the non-detection of an electromagnetic counterpart and 765 time volume VT semi-analytically, imposing single- h i 813 the lack of a clear signature of tides or spin-induced 766 detector and network SNR thresholds of 5 and 10, re- 814 quadrupole effects in the waveform do not allow us to 767 spectively (Tiwari 2018). The semi-analytic VT for h i 815 distinguish between a BBH or a NSBH. Instead, we rely 768 GW190814 is then multiplied by a calibration factor to 816 on comparisons between m2 and different estimates of 769 match results from the search pipelines assuming a once- 817 the maximum NS mass, Mmax, to indicate the source 770 per-century FAR threshold. The sensitivity of a search 818 classification preferred by data: if m2 > Mmax, then the 771 pipeline is estimated using a set of simulated signals. 819 NSBH scenario is untenable. 772 For computational efficiency, this was done using pre- 820 While some candidate EOSs from nuclear theory can 773 existing search pipeline simulations and the mass prop- 821 support nonrotating NSs with masses of up to 3 M 774 erties were not highly optimized. However, given that ∼ 822 (e.g., M¨uller& Serot 1996), such large values of Mmax 775 we are estimating a rate based on a single source, the cal- 823 are disfavored by the relatively small tidal deforma- 776 ibration errors are much smaller than the statistical er- 824 bilities measured in GW170817 (Abbott et al. 2017a, 777 rors associated with the estimate. The simulated sources 825 2019b), which correlate with smaller internal pressure 778 were uniformly distributed in comoving volume, compo- 826 gradients as a function of density and hence a lower 779 nent masses, and component spins aligned with the or- 827 threshold for gravitational collapse. By adopting a phe- 780 bital angular momentum. For O1 and O2, the simulated 828 nomenological model for the EOS, conditioning it on 781 BH mass range was 5–100 M , but for the first part of 829 GW170817, and extrapolating the constraints to the 782 O3 we are analyzing here, the injected range was 2.5– 830 high densities relevant for the maximum mass, Lim & 831 Holt(2019) and Essick et al.(2020) place Mmax . 2 See van den Heuvel & Tauris(2020) and Thompson et al.(2020) 832 2.3 M . Similarly, the EOS inference reported in Abbott for discussion about the interpretation of this observation. 833 et al.(2018), based on an analysis of GW170817 with 12

834 a spectral parameterization (Lindblom 2010; Lindblom 886 postmerger gravitational waves were observed (Abbott 835 & Indik 2012, 2014) for the EOS, implies a 90% credi- 887 et al. 2017g, 2019f), modeling of the associated kilonova 836 ble upper bound of Mmax 2.43 M , with tenuous but 888 (Abbott et al. 2017b; Kasen et al. 2017; Villar et al. 2017; ≤ 837 non-zero posterior support beyond 2.6 M . We calculate 889 Cowperthwaite et al. 2017; Abbott et al. 2017d) sug- 838 the corresponding Mmax posterior distribution, shown 890 gests that the merger remnant collapsed to a BH after 839 in the right panel of Figure3, from the GW170817- 891 a brief supramassive or hypermassive NS phase during 840 informed spectral EOS samples used in Abbott et al. 892 which it was stabilized by uniform or differential rota- 841 (2018) by reconstructing each EOS from its parameters 893 tion. Assuming this ultimate fate for the merger rem- 842 and computing its maximum mass. Comparison with 894 nant immediately implies that no NS can be stable above 843 the m2 posterior suggests that the secondary component 895 2.7 M , but it places a more stringent constraint on ∼ 844 of GW190814 is probably more massive than this predic- 896 NSs that are not rotationally supported. The precise 845 tion for Mmax: the posterior probability of m2 Mmax, 897 mapping from the collapse threshold mass of the rem- ≤ 846 marginalized over the uncertainty in m2 and Mmax, is 898 nant to Mmax depends on the EOS, but by developing 847 only 3%. Nevertheless, the maximum mass predictions 899 approximate prescriptions based on sequences of rapidly 848 from these kinds of EOS inferences come with impor- 900 rotating stars for a range of candidate EOSs, Mmax has 849 tant caveats: their extrapolations are sensitive to the 901 been bounded below approximately 2.2–2.3 M (Mar- 850 phenomenological model assumed for the EOS; they use 902 galit & Metzger 2017; Rezzolla et al. 2018; Ruiz et al. 851 hard Mmax thresholds on the EOS prior to account for 903 2018; Shibata et al. 2019; Abbott et al. 2020c). Although 852 the existence of the heaviest Galactic pulsars, which is 904 the degree of EOS uncertainty in these results is difficult 853 known to bias the inferred maximum mass distribution 905 to quantify precisely, if we take the more conservative 854 towards the threshold (Miller et al. 2020); and they pre- 906 2.3 M bound at face value, then m2 is almost certainly 855 date the NICER observatory’s recent simultaneous mass 907 not a NS: the m2 posterior distribution has negligible 856 and radius measurement for J0030+0451, which may in- 908 support below 2.3 M . 857 crease the Mmax estimates by a few percent (Landry 909 Overall, these considerations suggest that GW190814 858 et al. 2020) because it favors slightly stiffer EOSs than 910 is probably not the product of a NSBH coalescence, de- 859 GW170817 (Raaijmakers et al. 2019; Riley et al. 2019; 911 spite its preliminary classification as such. Nonetheless, 860 Miller et al. 2019; Jiang et al. 2020). 912 the possibility that the secondary component is a NS 861 NS mass measurements also inform bounds on Mmax 913 cannot be completely discounted due to the current un- 862 independently of EOS assumptions. Fitting the known 914 certainty in Mmax. 863 population of NSs in binaries to a double-Gaussian mass 915 There are two further caveats to this assessment. 864 distribution with a high-mass cutoff, Alsing et al.(2018) 916 First, because the secondary’s spin is unconstrained, it 865 obtained an empirical constraint of Mmax 2.6 M 917 could conceivably be rotating rapidly enough for m2 ≤ 866 (one-sided 90% confidence interval). Farr & Chatzi- 918 to exceed Mmax without triggering gravitational col- 867 ioannou(2020) recently updated this analysis to in- 919 lapse: rapid uniform rotation can stabilize a star up 868 clude PSR J0740+6620 (Cromartie et al. 2019), which 920 to 20% more massive than the nonrotating maximum ∼ 869 had not been discovered at the time of the original 921 mass (Cook et al. 1994), in which case only the absolute 870 study. Based on samples from the Farr & Chatzi- 922 upper bound of 2.7 M is relevant. However, it is very ∼ 871 ioannou(2020) maximum-mass posterior distribution, 923 unlikely that a NSBH system could merge before dissi- 872 which is plotted in the right panel of Figure3, we 924 pating such extreme natal NS spin angular momentum. +0.81 873 find Mmax = 2.25−0.26 M . In this case, the posterior 925 Second, our discussion has thus far neglected the pos- 874 probability of m2 Mmax is 29%, again favoring the 926 sibility that the secondary component is an exotic com- ≤ 875 m2 > Mmax scenario, albeit less strongly because of the 927 pact object, such as a boson star (Kaup 1968) or a 876 distribution’s long tail up to 3 M . However, the em- 928 gravastar (Mazur & Mottola 2004), instead of a NS or a ∼ 877 pirical Mmax prediction is sensitive to selection effects 929 BH. Depending on the model, some exotic compact ob- 878 that could potentially bias it (Alsing et al. 2018). In 930 jects can potentially support masses up to and beyond 879 particular, masses are only measurable for binary pul- 931 2.6 M (Cardoso & Pani 2019). Our analysis does not 880 sars, and the mass distribution of isolated NSs could be 932 exclude this hypothesis for the secondary. 881 different. Additionally, the discovery of GW190425 (Ab- 933 Since the NSBH scenario cannot be definitively ruled 882 bott et al. 2020a) should also be taken into account in 934 out, we examine GW190814’s potential implications for 883 the population when predicting Mmax. 935 the NS EOS, assuming that the secondary proves to be 884 Finally, the NS maximum mass is constrained by stud- 936 a NS. This would require Mmax to be no less than m2, 885 ies of the merger remnant of GW170817. Although no 937 a condition that severely constrains the distribution of 13

965 From a theoretical point of view, accurately calculat- 966 ing the masses of compact remnants at formation is chal- 967 lenging, because it depends on the complex physics of 968 the supernova explosion and the details of stellar evolu- 969 tion, especially for the late evolutionary stages of mas- 970 sive stars (Janka 2012; M¨uller 2016; Burrows et al. 2018; 971 Burrows et al. 2019). Whether the models favor the 972 presence of a gap or a smooth transition between NSs 973 and BHs is still unclear, and in fact some models have 974 been developed with the purpose of reproducing this 975 lower mass gap (Ugliano et al. 2012; Fryer et al. 2012; 976 Kochanek 2014; Sukhbold & Woosley 2014; Ertl et al. 977 2016). Therefore, our robust discovery of an object with Figure 8. Constraints on the NS EOS assuming GW190814 978 a well-constrained mass in this regime may provide cru- was produced by a BBH (blue) or a NSBH (orange) coales- 979 cial constraints on compact-object formation models. In cence. The 90% and 50% credible contours of the posterior 980 fact, GW190814 demonstrates the need to adjust rem- in the pressure-density plane are shown. The constraints 981 nant mass prescriptions previously designed to produce are calculated by assuming a spectral decomposition for the EOS, following Abbott et al.(2018). The BBH constraints 982 a perceived mass gap. The combination of mass ratio are identical to those from the analysis of GW170817, while 983 and component masses challenges most results obtained for the NSBH case the posterior is reweighted by the prob- 984 from population synthesis simulations for isolated bina- ability that each EOS’s maximum mass is at least m2. The 985 ries (Dominik et al. 2012, 2015; Marchant et al. 2017; dashed lines indicate the 90% credible region of the prior. 986 Giacobbo & Mapelli 2018; Mapelli & Giacobbo 2018; 987 Kruckow et al. 2018; Neijssel et al. 2019; Mapelli et al.

938 EOSs compatible with existing astrophysical data. The 988 2019; Spera et al. 2019; Olejak et al. 2020). 939 combined constraints on the EOS from GW170817 and 989 Population synthesis models distinguish between NSs 940 this hypothetical maximum mass information are shown 990 and BHs using only a mass threshold, which is gen- 941 in Figure8. Specifically, we have taken the spectral 991 erally in the range 2–3 M . Thus, depending on the 942 EOS distribution conditioned on GW170817 from Ab- 992 adopted threshold and on the adopted supernova explo- 943 bott et al.(2018) and reweighted each EOS by the prob- 993 sion model, a GW190814-like event may be labeled as 944 ability that its maximum mass is at least as large as m2. 994 either a NSBH merger or a BBH merger. Most BBH 945 The updated posterior favors stiffer EOSs, which trans- 995 mergers have q > 0.5, while the distributions of merging 946 lates to larger radii for NSs of a given mass. The cor- 996 NSBH binaries suggest that systems with q . 0.1 may 3 947 responding constraints on the radius and tidal deforma- 997 be up to 10 times less common than more symmet- +0.8 ∼ 948 bility of a canonical 1.4 M NS are R1.4 = 12.9−0.7 km 998 ric ones (q > 0.1) and that the mass-ratio distribution +273 949 and Λ = 616 . 999 peaks at q 0.2. Furthermore, models tend to favor 1.4 −158 ≈ 1000 mergers of massive (& 1.3 M ) NSs with relatively small 1001 BHs (. 15 M ) in environments with sub-solar metal- 1002 licity (Z 0.5 Z ). The tendency to disfavor mergers 950 6.3. Origins of GW190814-like Systems . 1003 with highly asymmetric masses in isolated binaries may 951 The source of GW190814 represents a previously un- 1004 be the consequence of mass transfer (e.g., Postnov & 952 detected class of coalescences that has the potential to 1005 Yungelson 2014) and common envelope episodes (e.g., 953 shed light on the formation of merging compact-object 1006 Ivanova et al. 2013) that cause systems with initially 954 binaries with highly asymmetric masses. 1007 asymmetric masses to evolve towards more symmetric 955 Electromagnetic observations of Galactic NSs and 1008 configurations. Overall, producing mergers with such 956 stellar-mass BHs suggest a dearth of compact objects in 1009 unequal masses, with a secondary in the perceived mass 957 the 2.5 M to 5 M range (Bailyn et al. 1998; Ozel¨ ∼ 1010 gap, and at the rate implied by this discovery is a chal- 958 et al. 2010; Farr et al. 2011; Ozel¨ et al. 2012). Observa- 1011 lenge for current models. 959 tions of a few candidates with masses in this range seem 1012 Nevertheless, particular choices of poorly constrained 960 to disfavor the existence of a gap (Freire et al. 2008; 1013 assumptions within rapid population synthesis models 961 Neustroev et al. 2014; Giesers et al. 2018; Wyrzykowski 1014 may increase the number of mergers with q . 0.1 so 962 & Mandel 2020; Thompson et al. 2019), but whether the 1015 that the latter may be only a few times less common 963 mass gap is physical or caused by selection biases is still 1016 than (or even comparable to) systems with q 0.2 (e.g., 964 a matter of debate (e.g., Kreidberg et al. 2012). ' 14

1017 Eldridge & Stanway 2016; Eldridge et al. 2017; Giacobbo 1069 Petrovich & Antonini 2017; Hoang et al. 2018; Fragione 1018 & Mapelli 2018). 1070 et al. 2019). Specifically, Safarzadeh et al.(2020) ex- 1019 Another possibility is that GW190814 is of dynami- 1071 plore the possibility that a second-generation remnant 1020 cal origin. Dynamical exchanges in dense stellar envi- 1072 with mass 3 M may merge with a 30 M BH, cat- 1021 ronments tend to pair up massive compact objects with 1073 alyzed by a 50 M -BH perturber. The mass-ratio dis- 1022 similar masses (e.g., Sigurdsson & Hernquist 1993). This 1074 tributions of BBH and NSBH mergers from hierarchical 1023 process is effective for globular clusters, where compact- 1075 systems are similar to those of field binaries and it is 1024 object binaries may undergo tens of exchanges before 1076 unclear whether hierarchies may enhance the formation 1025 they get ejected from the cluster (Portegies Zwart & 1077 of merging compact-object binaries with highly asym- 1026 McMillan 2000; Rodriguez et al. 2016; Park et al. 2017; 1078 metric masses (e.g., Silsbee & Tremaine 2017). 1027 Askar et al. 2017; Rodriguez et al. 2019). For such envi- 1079 Disks of gas around supermassive BHs in active galac- 1028 ronments, models predict that most merging BBHs have 1080 tic nuclei may be promising environments for the forma- 1029 q 1 (e.g., Rodriguez et al. 2016), and the formation 1081 tion of GW190814-like systems. For such environments, ' 1030 of NSBH binaries is highly suppressed because BHs dy- 1082 theoretical models show that merging compact-object 1031 namically dominate the cores over the complete lifetime 1083 binaries with asymmetric masses are likely, but cannot 1032 of the clusters, preventing the interactions between BHs 1084 necessarily accommodate masses as low as the secondary 1033 and NSs, with the consequence that the merger rate of 1085 mass of GW190814 (e.g., Yang et al. 2019). However, 1034 NSBH binaries in globular clusters in the local Universe 1086 McKernan et al.(2020) show that the median mass ratio −2 −1 −3 −1 1035 is 10 –10 Gpc yr (Clausen et al. 2013; Ye et al. 1087 of NSBH mergers in active galactic nucleus disks may be ∼ 1036 2020; Arca Sedda 2020). The rate for GW190814-like 1088 as low as 0.07. ∼ 1037 events, with a secondary in the perceived mass gap, is 1089 We conclude that the combination of masses, mass 1038 likely even lower. In contrast, the NSBH merger rate 1090 ratio and inferred rate of GW190814 is challenging to 1039 may be significantly higher in young star clusters (e.g., 1091 explain, but potentially consistent with multiple forma- 1040 Ziosi et al. 2014) and the latter can effectively increase 1092 tion scenarios. However, it is not possible to assess the 1041 the number of progenitors leading to merging compact- 1093 validity of models that produce the right properties but 1042 object binaries with q . 0.15 (Di Carlo et al. 2019; 1094 do not make quantitative predictions about formation 1043 Rastello et al. 2020). Thus, young star clusters may 1095 rates, even at some order-of-magnitude level. 1044 be promising hosts for GW190814-like events, but the 1096 Young star clusters and active galactic nucleus disks 1045 parameter space relevant for GW190814 is mostly unex- 1097 seem to be more promising hosts for GW190814-like 1046 plored in the context of star clusters. 1098 mergers, since both these environments may enhance 1047 In dense stellar environments, GW190814-like sys- 1099 the formation of either progenitors of or directly merg- 1048 tems may also form from a low-mass merger remnant 1100 ing compact-object binaries with more asymmetric 1049 that acquires a BH companion via dynamical interac- 1101 masses to relevant rates. In contrast, globular-cluster 1050 tions (Gupta et al. 2019). Gupta et al.(2019) pre- 1102 models provide more robust predictions, showing that 1051 dicts a population of second-generation BHs in the 2.2– 1103 GW190814-like mergers with such asymmetric masses 1052 3.8 M range, with a peak in the distribution at 2.6 M , 1104 are outliers in the population predictions, even though a 1053 assuming a double-Gaussian mass distribution for the 1105 revision of the remnant-mass prescription is still needed. 1054 NSs. However, recent dynamical simulations of globular 1106 Isolated binaries binaries could prove possible progeni- 1055 clusters (e.g., Ye et al. 2020) find the subsequent merger 1107 tors provided similar revisions are implemented. The 1056 of such a second-generation BH with a larger stellar- 1108 importance of field multiples remains to be fully ex- 1057 mass BH to be exceedingly rare. A high component spin 1109 plored. Future gravitational-wave observations will pro- 1058 could be a distinguishing feature of a second-generation 1110 vide further insights into the dominance of different 1059 compact object, but the uninformative spin posterior 1111 channels. 1060 for the lighter component of GW190814 provides no ev- 1061 idence for or against this hypothesis. 1112 6.4. Cosmological Implications 1062 A GW190814-like merger may also have originated 1113 Luminosity distances inferred directly from observed 1063 from a hierarchical triple in the field (e.g., Silsbee & 1114 gravitational-wave events can be used with measure- 1064 Tremaine 2017; Fragione & Loeb 2019; Antonini et al. 1115 ments of source redshifts in the electromagnetic spec- 1065 2017), from a wide hierarchical quadruple system (Sa- 1116 trum to constrain cosmological parameters (Schutz 1066 farzadeh et al. 2020), or from hierarchical triples in 1117 1986). Redshifts can be either obtained directly from 1067 galactic centers, where the tertiary body is a supermas- 1118 counterparts to the gravitational-wave source (Holz & 1068 sive BH (Antonini & Perets 2012; Stephan et al. 2019; 1119 Hughes 2005), as was the case for GW170817 (Ab- 15

1120 bott et al. 2017a,b,e), by cross-correlation of the 1172 redshift measurements of the Hubble constant (Verde 1121 gravitational-wave localization posterior with catalogs 1173 et al. 2019), but these constraints will continue to im- 1122 of galaxy redshifts (Del Pozzo 2012; Nair et al. 2018; 1174 prove as further gravitational-wave observations are in- 1123 Chen et al. 2018; Fishbach et al. 2019; Gray et al. 1175 cluded (e.g., projections in Chen et al. 2018; Vitale & 1124 2019; Soares-Santos et al. 2019; Abbott et al. 2019c), 1176 Chen 2018; Gray et al. 2019; Feeney et al. 2019). 1125 by exploiting information in the neutron star equation 1126 of state (Messenger & Read 2012), or by using the red- 1127 shifted masses inferred from the gravitational wave ob- 1177 7. CONCLUSIONS 1128 servation and assumptions about the mass distribution 1178 During their third observing run, on 2019 August 14, 1129 of the sources (Chernoff & Finn 1993; Taylor et al. 1179 21:10:39 UTC, the LIGO and Virgo detectors observed 1130 2012; Taylor & Gair 2012; Farr et al. 2019). At cur- 1180 GW190814, a novel source unlike any other known com- 1131 rent sensitivities, the cosmological parameter to which 1181 pact binary coalescence. Thanks in part to the obser- 1132 LIGO–Virgo observations are most sensitive is the Hub- 1182 vation of significant power in subdominant multipoles 1133 ble constant, H0. The gravitational-wave observation 1183 of the gravitational radiation, and the conclusive mea- 1134 of GW170817 provided a posterior on H0 with mode 1184 surement of little to no spin precession, we obtain pre- 1135 and 68.3% highest posterior density interval of H0 = +22 −1 −1 1185 cise measurements of its physical source properties that 1136 69−8 km s Mpc (Abbott et al. 2017e, 2019b,c), 1186 clearly set it apart from other compact binaries. 1137 assuming a flat prior on H0. +0.008 1187 In particular, (a) its mass ratio of q = 0.112−0.009 1138 GW190814 is the best localized dark siren, i.e., 1188 is the most unequal ever observed with gravitational 1139 gravitational-wave source without an electromagnetic 1189 waves, (b) the bound χ1 0.07 on the spin of the 1140 counterpart, observed to date, and so it is a good candi- +1.1 ≤ 1190 23.2−1.0 M BH is the strongest constraint on a primary 1141 date for the statistical cross-correlation method. For a 1191 spin for any gravitational-wave source to date, and (c) 1142 fixed reference cosmology (Ade et al. 2016), the GLADE +0.08 1192 the secondary mass measurement of 2.59−0.09 M makes 1143 galaxy catalog (D´alya et al. 2018) is approximately 1193 it the lightest BH or the heaviest NS discovered in a dou- 1144 40% complete at the distance of GW190814 and con- 1194 ble compact-object system. We find no evidence of mea- 1145 tains 472 galaxies within the 90% posterior credible vol- 1195 surable tidal effects in the signal, and no electromagnetic 1146 ume of GW190814. To obtain a constrain on H0, we 1196 counterpart to the gravitational waves has been identi- 1147 use the methodology described in Abbott et al.(2019c) 1197 fied. 1148 and the GLADE catalog. We take a flat prior for H0 −1 −1 ∈ 1198 Comparisons between the secondary mass and sev- 1149 [20, 140] km s Mpc and assign a probability to each 1199 eral current estimates of the maximum NS mass sug- 1150 galaxy that it is the true host of the event that is pro- 1200 gest that GW190814 is unlikely to originate in a NSBH 1151 portional to its B-band luminosity. Using the posterior 1201 coalescence. Nevertheless, the Mmax estimates are un- 1152 distribution on the distance obtained from the combined +59 −1 −1 1202 certain enough that improved knowledge of the NS EOS 1153 PHM samples, we obtain H0 = 75−13 km s Mpc us- 1203 or further observations of the astrophysical population 1154 ing GW190814 alone (mode and 68.3% highest posterior 1204 of compact objects could alter this assessment. For this 1155 density interval; the median and 90% symmetric credi- +55 −1 −1 1205 reason, we cannot firmly exclude the possibility that the 1156 ble interval is H0 = 83−53 km s Mpc ), which can be +40 −1 −1 1206 secondary is a NS, nor can we be certain that it is a BH. 1157 compared to H0 = 75−32 km s Mpc (Soares-Santos 1207 Regardless, this event sheds new light on the compact- 1158 et al. 2019) obtained using the dark siren GW170814 1208 object mass distribution at the interface between known 1159 alone. The GW190814 result is the most precise mea- 1209 NSs and BHs. 1160 surement from a single dark siren observation to date, 1210 The unique combination of masses and inferred merger 1161 albeit comparable to the GW170814 result, which is 1211 rate for this event is difficult to produce in population 1162 expected given GW190814’s small localization volume 3 1212 synthesis models of multi-component systems in galactic 1163 ( 39000 Mpc ). The result is not very constraining, ∼ 1213 fields or dense stellar environments. The discovery of 1164 with the 68.3% highest posterior density interval com- 1214 GW190814 may therefore reshape our understanding of 1165 prising 60% of the prior range. Combining the result for 1215 the processes by which the lightest BHs or the most 1166 GW190814 with the result obtained from GW170817, we 1216 massive NSs form. Based on our rate density estimate, 1167 see an improvement over the GW170817-only result, to +17 −1 −1 1217 we may reasonably expect to detect more systems of this 1168 H0 = 70−8 km s Mpc (the median and 90% sym- +33 −1 −1 1218 kind after a year at design sensitivity. This discovery 1169 metric credible interval is H0 = 77−23 km s Mpc ). 1219 may prove to be the first hint of a larger population 1170 This result is not yet sufficiently constraining to pro- 1220 that could change our perspective on the formation and 1171 vide further insight into current tensions in low and high 1221 mass spectrum of compact objects. 16

1222 Segments of data containing the signal from all three 1270 Hungary (NKFIH), the National Research Foundation 1223 interferometers, and samples from the posterior dis- 1271 of Korea, Industry Canada and the Province of On- 1224 tributions for the source parameters, are available 1272 tario through the Ministry of Economic Development 1225 from the Gravitational Wave Open Science Center 1273 and Innovation, the Natural Science and Engineering 1226 (https://doi.org/10.7935/zzw5-ak90). The software 1274 Research Council Canada, the Canadian Institute for 1227 packages used in our analysis are open source. 1275 Advanced Research, the Brazilian Ministry of Science, 1228 1276 Technology, Innovations, and Communications, the In- 1229 The authors gratefully acknowledge the support of the 1277 ternational Center for Theoretical Physics South Ameri- 1230 United States National Science Foundation (NSF) for 1278 can Institute for Fundamental Research (ICTP-SAIFR), 1231 the construction and operation of the LIGO Laboratory 1279 the Research Grants Council of Hong Kong, the Na- 1232 and Advanced LIGO as well as the Science and Tech- 1280 tional Natural Science Foundation of China (NSFC), 1233 nology Facilities Council (STFC) of the United King- 1281 the Leverhulme Trust, the Research Corporation, the 1234 dom, the Max-Planck-Society (MPS), and the State of 1282 Ministry of Science and Technology (MOST), Taiwan 1235 Niedersachsen/Germany for support of the construction 1283 and the Kavli Foundation. The authors gratefully ac- 1236 of Advanced LIGO and construction and operation of 1284 knowledge the support of the NSF, STFC, INFN and 1237 the GEO600 detector. Additional support for Advanced 1285 CNRS for provision of computational resources. Some 1238 LIGO was provided by the Australian Research Council. 1286 of the parameter estimation analyses presented in this 1239 The authors gratefully acknowledge the Italian Istituto 1287 paper were performed using the supercomputer cluster 1240 Nazionale di Fisica Nucleare (INFN), the French Centre 1288 at the Swinburne University of Technology (OzSTAR 1241 National de la Recherche Scientifique (CNRS) and the 1289 and SSTAR). 1242 Netherlands Organization for Scientific Research, for the 1290 We would like to thank all of the essential workers who 1243 construction and operation of the Virgo detector and the 1291 put their health at risk during the COVID-19 pandemic, 1244 creation and support of the EGO consortium. 1292 without whom we would not have been able to complete 1245 The authors also gratefully acknowledge research sup- 1293 this work. 1246 port from these agencies as well as by the Council of Sci- 1294 Software: The detection of the signal and subse- 1247 entific and Industrial Research of India, the Department 1295 quent significance evaluation were performed with the 1248 of Science and Technology, India, the Science & Engi- 1296 GstLAL-based inspiral software pipeline (Cannon et al. 1249 neering Research Board (SERB), India, the Ministry 1297 2012; Privitera et al. 2014; Messick et al. 2017; Sachdev 1250 of Human Resource Development, India, the Spanish 1298 et al. 2019; Hanna et al. 2020), built on the LALSuite 1251 Agencia Estatal de Investigaci´on,the Vicepresid`encia 1299 software library (LIGO Scientific Collaboration 2018), 1252 i Conselleria d’Innovaci´o, Recerca i Turisme and the 1300 and with the PyCBC (Nitz et al. 2018, 2019; Usman 1253 Conselleria d’Educaci´oi Universitat del Govern de les 1301 et al. 2016) and MBTAOnline (Adams et al. 2016) 1254 Illes Balears, the Conselleria d’Innovaci´o,Universitats, 1302 packages. Parameter estimation was performed with the 1255 Ci`enciai Societat Digital de la Generalitat Valenciana 1303 LALInference (Veitch et al. 2015) and LALSimula- 1256 and the CERCA Programme Generalitat de Catalunya, 1304 tion libraries within LALSuite (LIGO Scientific Col- 1257 Spain, the National Science Centre of Poland, the Swiss 1305 laboration 2018), as well as the Bilby and pBilby 1258 National Science Foundation (SNSF), the Russian Foun- 1306 Libraries (Ashton et al. 2019; Smith & Ashton 2019) 1259 dation for Basic Research, the Russian Science Foun- 1307 and the dynesty nested sampling package (Speagle 1260 dation, the European Commission, the European Re- 1308 2020). Estimates of the noise spectra were obtained us- 1261 gional Development Funds (ERDF), the Royal Society, 1309 ing BayesWave (Cornish & Littenberg 2015; Littenberg 1262 the Scottish Funding Council, the Scottish Universi- 1310 & Cornish 2015b). Plots were prepared with Matplotlib 1263 ties Physics Alliance, the Hungarian Scientific Research 1311 (Hunter 2007). The sky map plot also used Astropy 1264 Fund (OTKA), the French Lyon Institute of Origins 1312 (http://www.astropy.org) a community-developed core 1265 (LIO), the Belgian Fonds de la Recherche Scientifique 1313 Python package for Astronomy (Astropy Collaboration 1266 (FRS-FNRS), Actions de Recherche Concert´ees(ARC) 1314 et al. 2013; Price-Whelan et al. 2018) and ligo.skymap 1267 and Fonds Wetenschappelijk Onderzoek – Vlaanderen 1315 (https://lscsoft.docs.ligo.org/ligo.skymap). 1268 (FWO), Belgium, the Paris ˆIle-de-France Region, the 1269 National Research, Development and Innovation Office

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55 96 55 24 149 118 2020 G. Mo, K. Mogushi, S. R. P. Mohapatra, S. R. Mohite, M. Molina-Ruiz, M. Mondin, 72, 73 13 50 63 50 92 181 2021 M. Montani, C. J. Moore, D. Moraru, F. Morawski, G. Moreno, S. Morisaki, B. Mours, 13 130 82, 36 54 132 2022 C. M. Mow-Lowry, S. Mozzon, F. Muciaccia, Arunava Mukherjee, D. Mukherjee, 16 120 9, 10 7 64 45 2023 S. Mukherjee, Subroto Mukherjee, N. Mukund, A. Mullavey, J. Munch, E. A. Muniz,˜ 54 98, 139, 182 95, 35 82, 36 183 75 2024 P. G. Murray, A. Nagar, I. Nardecchia, L. Naticchioni, R. K. Nayak, B. F. Neil, 125, 77 184, 40 7 9, 10 147 55 64 2025 J. Neilson, G. Nelemans, T. J. N. Nelson, M. Nery, A. Neunzert, K. Y. Ng, S. Ng, 28 80 144, 40 2 144, 40 31 55 2026 C. Nguyen, P. Nguyen, D. Nichols, S. A. Nichols, S. Nissanke, F. Nocera, M. Noh, 114 185 130 50 32 17, 18 2027 C. North, D. Nothard, L. K. Nuttall, J. Oberling, B. D. O’Brien, G. Oganesyan, 186 159 159 9, 10 92 15 111 2028 G. H. Ogin, J. J. Oh, S. H. Oh, F. Ohme, H. Ohta, M. A. Okada, M. 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37 34 72, 73 72, 73 203 13 2082 D. Verkindt, D. Veske, F. Vetrano, A. Vicere,´ A. D. Viets, S. Vinciguerra, 69 74 55 6 45 43, 44 2083 D. J. Vine, J.-Y. Vinet, S. Vitale, Francisco Hernandez Vivanco, T. Vo, H. Vocca, 50 68 8 185 185 40 29 2084 C. Vorvick, S. P. Vyatchanin, A. R. Wade, L. E. Wade, M. Wade, R. Walet, M. Walker, 25 1 24 147 21 16 8 2085 G. S. Wallace, L. Wallace, S. Walsh, J. Z. Wang, S. Wang, W. H. Wang, R. L. Ward, 38 50 37 112 50 9, 10 9, 10 2086 Z. A. Warden, J. Warner, M. Was, J. Watchi, B. Weaver, L.-W. Wei, M. Weinert, 1 55 9, 10 75 9, 10 38 2087 A. J. Weinstein, R. Weiss, F. Wellmann, L. Wen, P. Weßels, J. W. Westhouse, 8 70 32 55 9, 10 54 2088 K. Wette, J. T. Whelan, B. F. Whiting, C. Whittle, D. M. Wilken, D. Williams, 1 10, 9 9, 10 1 9, 10 54 9, 10 2089 J. L. Willis, B. Willke, W. Winkler, C. C. Wipf, H. Wittel, G. Woan, J. Woehler, 70 104 54 9, 10 70 1 1 2090 J. K. Wofford, C. Wong, J. L. Wright, D. S. Wu, D. M. Wysocki, L. Xiao, H. Yamamoto, 133 32 47 8 32 114 55 2091 L. Yang, Y. Yang, Z. Yang, M. J. Yap, M. Yazback, D. W. Yeeles, Hang Yu, 55 104 16 162 38 31 2092 Haocun Yu, S. H. R. Yuen, A. K. Zadrozny,˙ A. Zadrozny,˙ M. Zanolin, T. Zelenova, 61 14 75 1 54 75 112 14 2093 J.-P. Zendri, M. Zevin, J. Zhang, L. Zhang, T. Zhang, C. Zhao, G. Zhao, M. Zhou, 14 6 177 55, 1 1 2094 Z. Zhou, X. J. Zhu, A. B. Zimmerman, M. E. Zucker And J. Zweizig

2095 LIGO Scientific Collaboration and Virgo Collaboration

2096

1 2097 LIGO, California Institute of Technology, Pasadena, CA 91125, USA 2 2098 Louisiana State University, Baton Rouge, LA 70803, USA 3 2099 Inter-University Centre for Astronomy and Astrophysics, Pune 411007, India 4 2100 Dipartimento di Farmacia, Universit`adi Salerno, I-84084 Fisciano, Salerno, Italy 5 2101 INFN, Sezione di Napoli, Complesso Universitario di Monte S.Angelo, I-80126 Napoli, Italy 6 2102 OzGrav, School of Physics & Astronomy, Monash University, Clayton 3800, Victoria, Australia 7 2103 LIGO Livingston Observatory, Livingston, LA 70754, USA 8 2104 OzGrav, Australian National University, Canberra, Australian Capital Territory 0200, Australia 9 2105 Max Planck Institute for Gravitational Physics (Albert Einstein Institute), D-30167 Hannover, Germany 10 2106 Leibniz Universit¨atHannover, D-30167 Hannover, Germany 11 2107 Theoretisch-Physikalisches Institut, Friedrich-Schiller-Universit¨atJena, D-07743 Jena, Germany 12 2108 University of Cambridge, Cambridge CB2 1TN, UK 13 2109 University of Birmingham, Birmingham B15 2TT, UK 14 2110 Center for Interdisciplinary Exploration & Research in Astrophysics (CIERA), Northwestern University, Evanston, IL 60208, USA 15 2111 Instituto Nacional de Pesquisas Espaciais, 12227-010 S˜aoJos´edos Campos, S˜aoPaulo, Brazil 16 2112 The University of Texas Rio Grande Valley, Brownsville, TX 78520, USA 17 2113 Gran Sasso Science Institute (GSSI), I-67100 L’Aquila, Italy 18 2114 INFN, Laboratori Nazionali del Gran Sasso, I-67100 Assergi, Italy 19 2115 International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Bengaluru 560089, India 20 2116 University College Dublin, Dublin 4, Ireland 21 2117 NCSA, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA 22 2118 INFN, Sezione di Pisa, I-56127 Pisa, Italy 23 2119 Laboratoire des Mat´eriauxAvanc´es(LMA), IP2I - UMR 5822, CNRS, Universit´ede Lyon, F-69622 Villeurbanne, France 24 2120 University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA 25 2121 SUPA, University of Strathclyde, Glasgow G1 1XQ, UK 26 2122 Dipartimento di Matematica e Informatica, Universit`adi Udine, I-33100 Udine, Italy 27 2123 INFN, Sezione di Trieste, I-34127 Trieste, Italy 28 2124 APC, AstroParticule et Cosmologie, Universit´eParis Diderot, CNRS/IN2P3, CEA/Irfu, Observatoire de Paris, Sorbonne Paris Cit´e, 2125 F-75205 Paris Cedex 13, France 29 2126 California State University Fullerton, Fullerton, CA 92831, USA 30 2127 LAL, Univ. Paris-Sud, CNRS/IN2P3, Universit´eParis-Saclay, F-91898 Orsay, France 31 2128 European Gravitational Observatory (EGO), I-56021 Cascina, Pisa, Italy 32 2129 University of Florida, Gainesville, FL 32611, USA 33 2130 Chennai Mathematical Institute, Chennai 603103, India 34 2131 Columbia University, New York, NY 10027, USA 35 2132 INFN, Sezione di Roma Tor Vergata, I-00133 Roma, Italy 36 2133 INFN, Sezione di Roma, I-00185 Roma, Italy 37 2134 Laboratoire d’Annecy de Physique des Particules (LAPP), Univ. Grenoble Alpes, Universit´eSavoie Mont Blanc, CNRS/IN2P3, 2135 F-74941 Annecy, France 38 2136 Embry-Riddle Aeronautical University, Prescott, AZ 86301, USA 39 2137 Montclair State University, Montclair, NJ 07043, USA 40 2138 Nikhef, Science Park 105, 1098 XG Amsterdam, The Netherlands 27

41 2139 Korea Institute of Science and Technology Information, Daejeon 34141, South Korea 42 2140 Christopher Newport University, Newport News, VA 23606, USA 43 2141 Universit`adi Perugia, I-06123 Perugia, Italy 44 2142 INFN, Sezione di Perugia, I-06123 Perugia, Italy 45 2143 Syracuse University, Syracuse, NY 13244, USA 46 2144 Universit´ede Li`ege, B-4000 Li`ege,Belgium 47 2145 University of Minnesota, Minneapolis, MN 55455, USA 48 2146 Universit`adegli Studi di Milano-Bicocca, I-20126 Milano, Italy 49 2147 INFN, Sezione di Milano-Bicocca, I-20126 Milano, Italy 50 2148 LIGO Hanford Observatory, Richland, WA 99352, USA 51 2149 Caltech CaRT, Pasadena, CA 91125, USA 52 2150 Departament de F´ısica Qu`antica i Astrof´ısica, Institut de Ci`enciesdel Cosmos (ICCUB), Universitat de Barcelona (IEEC-UB), 2151 E-08028 Barcelona, Spain 53 2152 Dipartimento di Medicina, Chirurgia e Odontoiatria “Scuola Medica Salernitana,” Universit`adi Salerno, I-84081 Baronissi, Salerno, 2153 Italy 54 2154 SUPA, University of Glasgow, Glasgow G12 8QQ, UK 55 2155 LIGO, Massachusetts Institute of Technology, Cambridge, MA 02139, USA 56 2156 Wigner RCP, RMKI, H-1121 Budapest, Konkoly Thege Mikl´os´ut29-33, Hungary 57 2157 Stanford University, Stanford, CA 94305, USA 58 2158 Universit`adi Pisa, I-56127 Pisa, Italy 59 2159 Universit`adi Camerino, Dipartimento di Fisica, I-62032 Camerino, Italy 60 2160 Universit`adi Padova, Dipartimento di Fisica e Astronomia, I-35131 Padova, Italy 61 2161 INFN, Sezione di Padova, I-35131 Padova, Italy 62 2162 Montana State University, Bozeman, MT 59717, USA 63 2163 Nicolaus Copernicus Astronomical Center, Polish Academy of Sciences, 00-716, Warsaw, Poland 64 2164 OzGrav, University of Adelaide, Adelaide, South Australia 5005, Australia 65 2165 Max Planck Institute for Gravitational Physics (Albert Einstein Institute), D-14476 Potsdam-Golm, Germany 66 2166 INFN, Sezione di Genova, I-16146 Genova, Italy 67 2167 RRCAT, Indore, Madhya Pradesh 452013, India 68 2168 Faculty of Physics, Lomonosov Moscow State University, Moscow 119991, Russia 69 2169 SUPA, University of the West of Scotland, Paisley PA1 2BE, UK 70 2170 Rochester Institute of Technology, Rochester, NY 14623, USA 71 2171 Bar-Ilan University, Ramat Gan 5290002, Israel 72 2172 Universit`adegli Studi di Urbino “Carlo Bo,” I-61029 Urbino, Italy 73 2173 INFN, Sezione di Firenze, I-50019 Sesto Fiorentino, Firenze, Italy 74 2174 Artemis, Universit´eCˆoted’Azur, Observatoire Cˆoted’Azur, CNRS, CS 34229, F-06304 Nice Cedex 4, France 75 2175 OzGrav, University of Western Australia, Crawley, Western Australia 6009, Australia 76 2176 Dipartimento di Fisica “E.R. Caianiello,” Universit`adi Salerno, I-84084 Fisciano, Salerno, Italy 77 2177 INFN, Sezione di Napoli, Gruppo Collegato di Salerno, Complesso Universitario di Monte S. Angelo, I-80126 Napoli, Italy 78 2178 Physik-Institut, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland 79 2179 Univ Rennes, CNRS, Institut FOTON - UMR6082, F-3500 Rennes, France 80 2180 University of Oregon, Eugene, OR 97403, USA 81 2181 Laboratoire Kastler Brossel, Sorbonne Universit´e,CNRS, ENS-Universit´ePSL, Coll`egede France, F-75005 Paris, France 82 2182 Universit`adi Roma “La Sapienza,” I-00185 Roma, Italy 83 2183 Universit´ecatholique de Louvain, B-1348 Louvain-la-Neuve, Belgium 84 2184 Astronomical Observatory Warsaw University, 00-478 Warsaw, Poland 85 2185 VU University Amsterdam, 1081 HV Amsterdam, The Netherlands 86 2186 University of Maryland, College Park, MD 20742, USA 87 2187 School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA 88 2188 Universit´ede Lyon, Universit´eClaude Bernard Lyon 1, CNRS, Institut Lumi`ere Mati`ere, F-69622 Villeurbanne, France 89 2189 Universit`adi Napoli “Federico II,” Complesso Universitario di Monte S.Angelo, I-80126 Napoli, Italy 90 2190 NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA 91 2191 Dipartimento di Fisica, Universit`adegli Studi di Genova, I-16146 Genova, Italy 92 2192 RESCEU, University of Tokyo, Tokyo, 113-0033, Japan. 93 2193 Tsinghua University, Beijing 100084, China 94 2194 Texas Tech University, Lubbock, TX 79409, USA 95 2195 Universit`adi Roma Tor Vergata, I-00133 Roma, Italy 28

96 2196 Missouri University of Science and Technology, Rolla, MO 65409, USA 97 2197 Departamento de Astronom´ıay Astrof´ısica, Universitat de Val`encia,E-46100 Burjassot, Val`encia,Spain 98 2198 Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi,” I-00184 Roma, Italy 99 2199 National Tsing Hua University, Hsinchu City, 30013 Taiwan, Republic of China 100 2200 Charles Sturt University, Wagga Wagga, New South Wales 2678, Australia 101 2201 Physics and Astronomy Department, Stony Brook University, Stony Brook, NY 11794, USA 102 2202 Center for Computational Astrophysics, Flatiron Institute, 162 5th Ave, New York, NY 10010, USA 103 2203 University of Chicago, Chicago, IL 60637, USA 104 2204 The Chinese University of Hong Kong, Shatin, NT, Hong Kong 105 2205 Dipartimento di Ingegneria Industriale (DIIN), Universit`adi Salerno, I-84084 Fisciano, Salerno, Italy 106 2206 Institut de Physique des 2 Infinis de Lyon (IP2I) - UMR 5822, Universit´ede Lyon, Universit´eClaude Bernard, CNRS, F-69622 2207 Villeurbanne, France 107 2208 Seoul National University, Seoul 08826, South Korea 108 2209 Pusan National University, Busan 46241, South Korea 109 2210 INAF, Osservatorio Astronomico di Padova, I-35122 Padova, Italy 110 2211 OzGrav, University of Melbourne, Parkville, Victoria 3010, Australia 111 2212 Universitat de les Illes Balears, IAC3—IEEC, E-07122 Palma de Mallorca, Spain 112 2213 Universit´eLibre de Bruxelles, Brussels 1050, Belgium 113 2214 Departamento de Matem´aticas, Universitat de Val`encia, E-46100 Burjassot, Val`encia,Spain 114 2215 Cardiff University, Cardiff CF24 3AA, UK 115 2216 University of Rhode Island, Kingston, RI 02881, USA 116 2217 Bellevue College, Bellevue, WA 98007, USA 117 2218 MTA-ELTE Astrophysics Research Group, Institute of Physics, E¨otv¨osUniversity, Budapest 1117, Hungary 118 2219 California State University, Los Angeles, 5151 State University Dr, Los Angeles, CA 90032, USA 119 2220 Universit¨atHamburg, D-22761 Hamburg, Germany 120 2221 Institute for Plasma Research, Bhat, Gandhinagar 382428, India 121 2222 IGFAE, Campus Sur, Universidade de Santiago de Compostela, 15782 Spain 122 2223 The University of Sheffield, Sheffield S10 2TN, UK 123 2224 Dipartimento di Scienze Matematiche, Fisiche e Informatiche, Universit`adi Parma, I-43124 Parma, Italy 124 2225 INFN, Sezione di Milano Bicocca, Gruppo Collegato di Parma, I-43124 Parma, Italy 125 2226 Dipartimento di Ingegneria, Universit`adel Sannio, I-82100 Benevento, Italy 126 2227 Universit`adi Trento, Dipartimento di Fisica, I-38123 Povo, Trento, Italy 127 2228 INFN, Trento Institute for Fundamental Physics and Applications, I-38123 Povo, Trento, Italy 128 2229 Universit`adegli Studi di Sassari, I-07100 Sassari, Italy 129 2230 INFN, Laboratori Nazionali del Sud, I-95125 Catania, Italy 130 2231 University of Portsmouth, Portsmouth, PO1 3FX, UK 131 2232 West Virginia University, Morgantown, WV 26506, USA 132 2233 The Pennsylvania State University, University Park, PA 16802, USA 133 2234 Colorado State University, Fort Collins, CO 80523, USA 134 2235 Institute for Nuclear Research (Atomki), Hungarian Academy of Sciences, Bem t´er18/c, H-4026 Debrecen, Hungary 135 2236 CNR-SPIN, c/o Universit`adi Salerno, I-84084 Fisciano, Salerno, Italy 136 2237 Scuola di Ingegneria, Universit`adella Basilicata, I-85100 Potenza, Italy 137 2238 National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan 138 2239 Observatori Astron`omic,Universitat de Val`encia,E-46980 Paterna, Val`encia, Spain 139 2240 INFN Sezione di Torino, I-10125 Torino, Italy 140 2241 Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India 141 2242 University of Szeged, D´omt´er9, Szeged 6720, Hungary 142 2243 Delta Institute for Theoretical Physics, Science Park 904, 1090 GL Amsterdam, The Netherlands 143 2244 Lorentz Institute, Leiden University, PO Box 9506, Leiden 2300 RA, The Netherlands 144 2245 GRAPPA, Anton Pannekoek Institute for Astronomy and Institute for High-Energy Physics, University of Amsterdam, Science Park 2246 904, 1098 XH Amsterdam, The Netherlands 145 2247 Tata Institute of Fundamental Research, Mumbai 400005, India 146 2248 INAF, Osservatorio Astronomico di Capodimonte, I-80131 Napoli, Italy 147 2249 University of Michigan, Ann Arbor, MI 48109, USA 148 2250 American University, Washington, D.C. 20016, USA 149 2251 University of California, Berkeley, CA 94720, USA 150 2252 Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands 29

151 2253 Directorate of Construction, Services & Estate Management, Mumbai 400094 India 152 2254 University of Bialystok, 15-424 Bia lystok, Poland 153 2255 King’s College London, University of London, London WC2R 2LS, UK 154 2256 University of Southampton, Southampton SO17 1BJ, UK 155 2257 University of Washington Bothell, Bothell, WA 98011, USA 156 2258 Institute of Applied Physics, Nizhny Novgorod, 603950, Russia 157 2259 Ewha Womans University, Seoul 03760, South Korea 158 2260 Inje University Gimhae, South Gyeongsang 50834, South Korea 159 2261 National Institute for Mathematical Sciences, Daejeon 34047, South Korea 160 2262 Ulsan National Institute of Science and Technology, Ulsan 44919, South Korea 161 2263 Bard College, 30 Campus Rd, Annandale-On-Hudson, NY 12504, USA 162 2264 NCBJ, 05-400 Swierk-Otwock,´ Poland 163 2265 Institute of Mathematics, Polish Academy of Sciences, 00656 Warsaw, Poland 164 2266 Cornell University, Ithaca, NY 14850, USA 165 2267 Universit´ede Montr´eal/Polytechnique, Montreal, Quebec H3T 1J4, Canada 166 2268 Lagrange, Universit´eCˆoted’Azur, Observatoire Cˆoted’Azur, CNRS, CS 34229, F-06304 Nice Cedex 4, France 167 2269 Hillsdale College, Hillsdale, MI 49242, USA 168 2270 Korea Astronomy and Space Science Institute, Daejeon 34055, South Korea 169 2271 Institute for High-Energy Physics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands 170 2272 NASA Marshall Space Flight Center, Huntsville, AL 35811, USA 171 2273 University of Washington, Seattle, WA 98195, USA 172 2274 Dipartimento di Matematica e Fisica, Universit`adegli Studi Roma Tre, I-00146 Roma, Italy 173 2275 INFN, Sezione di Roma Tre, I-00146 Roma, Italy 174 2276 ESPCI, CNRS, F-75005 Paris, France 175 2277 Center for Phononics and Thermal Energy Science, School of Physics Science and Engineering, Tongji University, 200092 Shanghai, 2278 People’s Republic of China 176 2279 Southern University and A&M College, Baton Rouge, LA 70813, USA 177 2280 Department of Physics, University of Texas, Austin, TX 78712, USA 178 2281 Dipartimento di Fisica, Universit`adi Trieste, I-34127 Trieste, Italy 179 2282 Centre Scientifique de Monaco, 8 quai Antoine Ier, MC-98000, Monaco 180 2283 Indian Institute of Technology Madras, Chennai 600036, India 181 2284 Universit´ede Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, France 182 2285 Institut des Hautes Etudes Scientifiques, F-91440 Bures-sur-Yvette, France 183 2286 IISER-Kolkata, Mohanpur, West Bengal 741252, India 184 2287 Department of Astrophysics/IMAPP, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands 185 2288 Kenyon College, Gambier, OH 43022, USA 186 2289 Whitman College, 345 Boyer Avenue, Walla Walla, WA 99362 USA 187 2290 Hobart and William Smith Colleges, Geneva, NY 14456, USA 188 2291 Department of Physics, Lancaster University, Lancaster, LA1 4YB, UK 189 2292 OzGrav, Swinburne University of Technology, Hawthorn VIC 3122, Australia 190 2293 Trinity University, San Antonio, TX 78212, USA 191 2294 Dipartimento di Fisica, Universit`adegli Studi di Torino, I-10125 Torino, Italy 192 2295 Indian Institute of Technology, Gandhinagar Ahmedabad Gujarat 382424, India 193 2296 INAF, Osservatorio Astronomico di Brera sede di Merate, I-23807 Merate, Lecco, Italy 194 2297 Centro de Astrof´ısica e Gravita¸c˜ao(CENTRA), Departamento de F´ısica, Instituto Superior T´ecnico, Universidade de Lisboa, 2298 1049-001 Lisboa, Portugal 195 2299 Marquette University, 11420 W. Clybourn St., Milwaukee, WI 53233, USA 196 2300 Indian Institute of Technology Hyderabad, Sangareddy, Khandi, Telangana 502285, India 197 2301 INAF, Osservatorio di Astrofisica e Scienza dello Spazio, I-40129 Bologna, Italy 198 2302 International Institute of Physics, Universidade Federal do Rio Grande do Norte, Natal RN 59078-970, Brazil 199 2303 Villanova University, 800 Lancaster Ave, Villanova, PA 19085, USA 200 2304 Andrews University, Berrien Springs, MI 49104, USA 201 2305 Carleton College, Northfield, MN 55057, USA 202 2306 Department of Physics, Utrecht University, 3584CC Utrecht, The Netherlands 203 2307 Concordia University Wisconsin, 2800 N Lake Shore Dr, Mequon, WI 53097, USA