W1. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.024^{+0.024}_{-0.024}$ -- $5.019$
$m_2~(\mathrm{M}_\odot)$ $1.4172^{+0.0053}_{-0.0053}$ -- $1.4184$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237163^{+0.000031}_{-0.000029}$ -- $2.237157$
$q$ $3.545^{+0.030}_{-0.030}$ -- $3.538$
$t_c$ (s) $1.187008882443431^{+0.000000000000065}_{-0.000000000000061}\times 10^{9}$ -- $1.187008882443422\times 10^{9}$
SNR $1253.0573^{+0.0013}_{-0.0027}$ -- $1253.0592$

Detectors: H1

Number of posterior samples: 95547



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A2. Posteriors

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A3. Posteriors

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W2. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.043^{+0.021}_{-0.020}$ -- $5.034$
$m_2~(\mathrm{M}_\odot)$ $1.4129^{+0.0045}_{-0.0046}$ -- $1.4151$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237193^{+0.000026}_{-0.000024}$ -- $2.237183$
$q$ $3.569^{+0.027}_{-0.025}$ -- $3.557$
$t_c$ (s) $1.187008882443399^{+0.000000000000062}_{-0.000000000000057}\times 10^{9}$ -- $1.187008882443371\times 10^{9}$
SNR $1253.0556^{+0.0012}_{-0.0026}$ -- $1253.0572$

Detectors: H1

Number of posterior samples: 91460



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A2. Posteriors

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A3. Posteriors

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W3. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.059^{+0.017}_{-0.024}$ -- $5.077$
$m_2~(\mathrm{M}_\odot)$ $1.4094^{+0.0053}_{-0.0037}$ -- $1.4055$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237220^{+0.000023}_{-0.000027}$ -- $2.237240$
$q$ $3.590^{+0.021}_{-0.030}$ -- $3.612$
$t_c$ (s) $1.187008882443413^{+0.000000000000046}_{-0.000000000000071}\times 10^{9}$ -- $1.187008882443464\times 10^{9}$
SNR $1252.5995^{+0.0013}_{-0.0026}$ -- $1252.6013$

Detectors: H1

Number of posterior samples: 91756



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A2. Posteriors

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A3. Posteriors

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W4. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.168^{+0.021}_{-0.022}$ -- $5.180$
$m_2~(\mathrm{M}_\odot)$ $1.3859^{+0.0046}_{-0.0044}$ -- $1.3835$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237391^{+0.000026}_{-0.000027}$ -- $2.237403$
$q$ $3.729^{+0.027}_{-0.028}$ -- $3.744$
$t_c$ (s) $1.187008882443224^{+0.000000000000060}_{-0.000000000000061}\times 10^{9}$ -- $1.187008882443259\times 10^{9}$
SNR $1252.5393^{+0.0012}_{-0.0026}$ -- $1252.5410$

Detectors: H1

Number of posterior samples: 91195



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A2. Posteriors

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A3. Posteriors

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W5. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.047^{+0.022}_{-0.024}$ -- $5.056$
$m_2~(\mathrm{M}_\odot)$ $1.4122^{+0.0055}_{-0.0049}$ -- $1.4101$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237199^{+0.000030}_{-0.000030}$ -- $2.237208$
$q$ $3.574^{+0.028}_{-0.031}$ -- $3.586$
$t_c$ (s) $1.187008882443419^{+0.000000000000055}_{-0.000000000000069}\times 10^{9}$ -- $1.187008882443463\times 10^{9}$
SNR $1255.2577^{+0.0013}_{-0.0028}$ -- $1255.2596$

Detectors: H1

Number of posterior samples: 94949



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A2. Posteriors

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A3. Posteriors

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W6. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.052^{+0.017}_{-0.023}$ -- $5.064$
$m_2~(\mathrm{M}_\odot)$ $1.4109^{+0.0052}_{-0.0038}$ -- $1.4083$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237208^{+0.000023}_{-0.000027}$ -- $2.237220$
$q$ $3.581^{+0.022}_{-0.030}$ -- $3.596$
$t_c$ (s) $1.187008882443412^{+0.000000000000050}_{-0.000000000000068}\times 10^{9}$ -- $1.187008882443450\times 10^{9}$
SNR $1255.2577^{+0.0012}_{-0.0027}$ -- $1255.2594$

Detectors: H1

Number of posterior samples: 91218



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A2. Posteriors

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A3. Posteriors

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W7. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.159^{+0.023}_{-0.019}$ -- $5.139$
$m_2~(\mathrm{M}_\odot)$ $1.3879^{+0.0041}_{-0.0048}$ -- $1.3920$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237375^{+0.000027}_{-0.000025}$ -- $2.237353$
$q$ $3.717^{+0.029}_{-0.025}$ -- $3.692$
$t_c$ (s) $1.187008882443218^{+0.000000000000066}_{-0.000000000000053}\times 10^{9}$ -- $1.187008882443163\times 10^{9}$
SNR $1255.2012^{+0.0013}_{-0.0027}$ -- $1255.2030$

Detectors: H1

Number of posterior samples: 91611



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A2. Posteriors

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A3. Posteriors

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W8. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.048^{+0.025}_{-0.022}$ -- $5.034$
$m_2~(\mathrm{M}_\odot)$ $1.4119^{+0.0049}_{-0.0054}$ -- $1.4149$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237210^{+0.000032}_{-0.000028}$ -- $2.237197$
$q$ $3.575^{+0.031}_{-0.028}$ -- $3.558$
$t_c$ (s) $1.187008882443394^{+0.000000000000068}_{-0.000000000000058}\times 10^{9}$ -- $1.187008882443353\times 10^{9}$
SNR $1254.1093^{+0.0014}_{-0.0027}$ -- $1254.1113$

Detectors: H1

Number of posterior samples: 95193



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A2. Posteriors

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A3. Posteriors

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W9. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.049^{+0.023}_{-0.018}$ -- $5.032$
$m_2~(\mathrm{M}_\odot)$ $1.4116^{+0.0040}_{-0.0050}$ -- $1.4154$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237213^{+0.000026}_{-0.000023}$ -- $2.237195$
$q$ $3.577^{+0.029}_{-0.023}$ -- $3.555$
$t_c$ (s) $1.187008882443386^{+0.000000000000069}_{-0.000000000000049}\times 10^{9}$ -- $1.187008882443336\times 10^{9}$
SNR $1254.1095^{+0.0012}_{-0.0026}$ -- $1254.1113$

Detectors: H1

Number of posterior samples: 92141



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A2. Posteriors

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A3. Posteriors

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W10. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.158^{+0.025}_{-0.015}$ -- $5.144$
$m_2~(\mathrm{M}_\odot)$ $1.3880^{+0.0031}_{-0.0053}$ -- $1.3911$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237383^{+0.000028}_{-0.000022}$ -- $2.237366$
$q$ $3.716^{+0.033}_{-0.019}$ -- $3.698$
$t_c$ (s) $1.187008882443198^{+0.000000000000076}_{-0.000000000000038}\times 10^{9}$ -- $1.187008882443159\times 10^{9}$
SNR $1254.0511^{+0.0014}_{-0.0026}$ -- $1254.0532$

Detectors: H1

Number of posterior samples: 92565



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A2. Posteriors

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A3. Posteriors

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W11. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.032^{+0.023}_{-0.024}$ -- $5.046$
$m_2~(\mathrm{M}_\odot)$ $1.4153^{+0.0054}_{-0.0052}$ -- $1.4124$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237180^{+0.000031}_{-0.000030}$ -- $2.237193$
$q$ $3.556^{+0.030}_{-0.031}$ -- $3.573$
$t_c$ (s) $1.187008882443422^{+0.000000000000060}_{-0.000000000000067}\times 10^{9}$ -- $1.187008882443467\times 10^{9}$
SNR $1254.7296^{+0.0014}_{-0.0028}$ -- $1254.7315$

Detectors: H1

Number of posterior samples: 95417



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A2. Posteriors

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A3. Posteriors

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W12. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.043^{+0.020}_{-0.022}$ -- $5.041$
$m_2~(\mathrm{M}_\odot)$ $1.4129^{+0.0050}_{-0.0043}$ -- $1.4135$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237197^{+0.000025}_{-0.000027}$ -- $2.237195$
$q$ $3.570^{+0.025}_{-0.028}$ -- $3.566$
$t_c$ (s) $1.187008882443404^{+0.000000000000057}_{-0.000000000000062}\times 10^{9}$ -- $1.187008882443396\times 10^{9}$
SNR $1254.7293^{+0.0012}_{-0.0026}$ -- $1254.7309$

Detectors: H1

Number of posterior samples: 91330



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A2. Posteriors

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A3. Posteriors

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W13. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.151^{+0.025}_{-0.017}$ -- $5.135$
$m_2~(\mathrm{M}_\odot)$ $1.3895^{+0.0036}_{-0.0052}$ -- $1.3930$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237361^{+0.000028}_{-0.000023}$ -- $2.237344$
$q$ $3.707^{+0.032}_{-0.022}$ -- $3.686$
$t_c$ (s) $1.187008882443210^{+0.000000000000073}_{-0.000000000000045}\times 10^{9}$ -- $1.187008882443162\times 10^{9}$
SNR $1252.9822^{+0.0013}_{-0.0026}$ -- $1252.9842$

Detectors: H1

Number of posterior samples: 92216



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A2. Posteriors

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A3. Posteriors

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W14. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.152^{+0.024}_{-0.019}$ -- $5.135$
$m_2~(\mathrm{M}_\odot)$ $1.3893^{+0.0040}_{-0.0050}$ -- $1.3930$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237367^{+0.000028}_{-0.000024}$ -- $2.237348$
$q$ $3.709^{+0.031}_{-0.024}$ -- $3.686$
$t_c$ (s) $1.187008882443215^{+0.000000000000069}_{-0.000000000000050}\times 10^{9}$ -- $1.187008882443163\times 10^{9}$
SNR $1254.6610^{+0.0012}_{-0.0027}$ -- $1254.6628$

Detectors: H1

Number of posterior samples: 92059



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A2. Posteriors

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A3. Posteriors

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W15. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.058^{+0.021}_{-0.025}$ -- $5.067$
$m_2~(\mathrm{M}_\odot)$ $1.4096^{+0.0056}_{-0.0047}$ -- $1.4076$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237217^{+0.000030}_{-0.000031}$ -- $2.237224$
$q$ $3.588^{+0.027}_{-0.032}$ -- $3.600$
$t_c$ (s) $1.187008882443416^{+0.000000000000049}_{-0.000000000000073}\times 10^{9}$ -- $1.187008882443460\times 10^{9}$
SNR $1257.4426^{+0.0014}_{-0.0028}$ -- $1257.4447$

Detectors: H1

Number of posterior samples: 95788



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A2. Posteriors

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A3. Posteriors

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W16. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.057^{+0.016}_{-0.024}$ -- $5.071$
$m_2~(\mathrm{M}_\odot)$ $1.4100^{+0.0054}_{-0.0035}$ -- $1.4068$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237214^{+0.000022}_{-0.000027}$ -- $2.237229$
$q$ $3.586^{+0.020}_{-0.031}$ -- $3.605$
$t_c$ (s) $1.187008882443421^{+0.000000000000043}_{-0.000000000000072}\times 10^{9}$ -- $1.187008882443467\times 10^{9}$
SNR $1257.4428^{+0.0013}_{-0.0026}$ -- $1257.4447$

Detectors: H1

Number of posterior samples: 91762



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A2. Posteriors

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A3. Posteriors

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W17. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.165^{+0.020}_{-0.022}$ -- $5.185$
$m_2~(\mathrm{M}_\odot)$ $1.3865^{+0.0047}_{-0.0042}$ -- $1.3824$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237384^{+0.000025}_{-0.000027}$ -- $2.237404$
$q$ $3.726^{+0.026}_{-0.029}$ -- $3.751$
$t_c$ (s) $1.187008882443233^{+0.000000000000056}_{-0.000000000000064}\times 10^{9}$ -- $1.187008882443291\times 10^{9}$
SNR $1257.3898^{+0.0013}_{-0.0027}$ -- $1257.3915$

Detectors: H1

Number of posterior samples: 91505



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A2. Posteriors

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A3. Posteriors

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W18. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.047^{+0.025}_{-0.021}$ -- $5.030$
$m_2~(\mathrm{M}_\odot)$ $1.4122^{+0.0048}_{-0.0054}$ -- $1.4159$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237207^{+0.000031}_{-0.000028}$ -- $2.237189$
$q$ $3.574^{+0.031}_{-0.027}$ -- $3.552$
$t_c$ (s) $1.187008882443383^{+0.000000000000071}_{-0.000000000000056}\times 10^{9}$ -- $1.187008882443340\times 10^{9}$
SNR $1261.3188^{+0.0014}_{-0.0028}$ -- $1261.3208$

Detectors: H1

Number of posterior samples: 95306



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A2. Posteriors

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A3. Posteriors

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W19. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.044^{+0.023}_{-0.018}$ -- $5.028$
$m_2~(\mathrm{M}_\odot)$ $1.4129^{+0.0040}_{-0.0051}$ -- $1.4165$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237203^{+0.000027}_{-0.000023}$ -- $2.237187$
$q$ $3.570^{+0.030}_{-0.023}$ -- $3.549$
$t_c$ (s) $1.187008882443385^{+0.000000000000070}_{-0.000000000000049}\times 10^{9}$ -- $1.187008882443335\times 10^{9}$
SNR $1261.3190^{+0.0013}_{-0.0026}$ -- $1261.3208$

Detectors: H1

Number of posterior samples: 91759



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A2. Posteriors

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A3. Posteriors

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W20. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.151^{+0.026}_{-0.015}$ -- $5.139$
$m_2~(\mathrm{M}_\odot)$ $1.3895^{+0.0031}_{-0.0054}$ -- $1.3921$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237371^{+0.000028}_{-0.000021}$ -- $2.237359$
$q$ $3.707^{+0.033}_{-0.019}$ -- $3.692$
$t_c$ (s) $1.187008882443196^{+0.000000000000077}_{-0.000000000000035}\times 10^{9}$ -- $1.187008882443159\times 10^{9}$
SNR $1261.2681^{+0.0014}_{-0.0027}$ -- $1261.2701$

Detectors: H1

Number of posterior samples: 92937



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A2. Posteriors

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A3. Posteriors

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W21. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.046^{+0.020}_{-0.026}$ -- $5.060$
$m_2~(\mathrm{M}_\odot)$ $1.4123^{+0.0058}_{-0.0045}$ -- $1.4092$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237199^{+0.000028}_{-0.000031}$ -- $2.237214$
$q$ $3.573^{+0.026}_{-0.033}$ -- $3.591$
$t_c$ (s) $1.187008882443429^{+0.000000000000047}_{-0.000000000000072}\times 10^{9}$ -- $1.187008882443475\times 10^{9}$
SNR $1256.4645^{+0.0014}_{-0.0028}$ -- $1256.4666$

Detectors: H1

Number of posterior samples: 95718



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A2. Posteriors

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A3. Posteriors

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W22. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.050^{+0.015}_{-0.025}$ -- $5.063$
$m_2~(\mathrm{M}_\odot)$ $1.4114^{+0.0055}_{-0.0034}$ -- $1.4085$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237204^{+0.000021}_{-0.000027}$ -- $2.237217$
$q$ $3.578^{+0.019}_{-0.031}$ -- $3.595$
$t_c$ (s) $1.187008882443425^{+0.000000000000041}_{-0.000000000000072}\times 10^{9}$ -- $1.187008882443469\times 10^{9}$
SNR $1256.4646^{+0.0013}_{-0.0026}$ -- $1256.4666$

Detectors: H1

Number of posterior samples: 92221



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A2. Posteriors

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A3. Posteriors

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W23. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.160^{+0.019}_{-0.024}$ -- $5.178$
$m_2~(\mathrm{M}_\odot)$ $1.3876^{+0.0050}_{-0.0040}$ -- $1.3839$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237375^{+0.000025}_{-0.000028}$ -- $2.237393$
$q$ $3.719^{+0.025}_{-0.030}$ -- $3.742$
$t_c$ (s) $1.187008882443239^{+0.000000000000053}_{-0.000000000000067}\times 10^{9}$ -- $1.187008882443294\times 10^{9}$
SNR $1256.4053^{+0.0013}_{-0.0025}$ -- $1256.4071$

Detectors: H1

Number of posterior samples: 91430



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A2. Posteriors

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A3. Posteriors

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W24. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.037^{+0.024}_{-0.024}$ -- $5.033$
$m_2~(\mathrm{M}_\odot)$ $1.4143^{+0.0054}_{-0.0053}$ -- $1.4151$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237183^{+0.000031}_{-0.000031}$ -- $2.237179$
$q$ $3.561^{+0.031}_{-0.030}$ -- $3.557$
$t_c$ (s) $1.187008882443410^{+0.000000000000060}_{-0.000000000000067}\times 10^{9}$ -- $1.187008882443401\times 10^{9}$
SNR $1255.0915^{+0.0014}_{-0.0027}$ -- $1255.0935$

Detectors: H1

Number of posterior samples: 94614



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A2. Posteriors

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A3. Posteriors

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W25. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.086^{+0.024}_{-0.018}$ -- $10.080$
$m_2~(\mathrm{M}_\odot)$ $1.4130^{+0.0018}_{-0.0024}$ -- $1.4136$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021193^{+0.000038}_{-0.000040}$ -- $3.021190$
$q$ $7.138^{+0.029}_{-0.022}$ -- $7.131$
$t_c$ (s) $1.187008882443332^{+0.000000000000127}_{-0.000000000000063}\times 10^{9}$ -- $1.187008882443266\times 10^{9}$
SNR $1549.2058^{+0.0013}_{-0.0023}$ -- $1549.2077$

Detectors: H1

Number of posterior samples: 95306



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A2. Posteriors

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A3. Posteriors

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W26. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.082^{+0.022}_{-0.014}$ -- $10.071$
$m_2~(\mathrm{M}_\odot)$ $1.4134^{+0.0014}_{-0.0023}$ -- $1.4145$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021185^{+0.000034}_{-0.000031}$ -- $3.021171$
$q$ $7.133^{+0.027}_{-0.017}$ -- $7.119$
$t_c$ (s) $1.187008882443334^{+0.000000000000128}_{-0.000000000000057}\times 10^{9}$ -- $1.187008882443272\times 10^{9}$
SNR $1549.2058^{+0.0012}_{-0.0022}$ -- $1549.2076$

Detectors: H1

Number of posterior samples: 95238



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A2. Posteriors

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A3. Posteriors

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W27. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.100^{+0.022}_{-0.016}$ -- $10.086$
$m_2~(\mathrm{M}_\odot)$ $1.4115^{+0.0017}_{-0.0023}$ -- $1.4130$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021221^{+0.000036}_{-0.000033}$ -- $3.021205$
$q$ $7.155^{+0.027}_{-0.020}$ -- $7.138$
$t_c$ (s) $1.187008882443327^{+0.000000000000130}_{-0.000000000000078}\times 10^{9}$ -- $1.187008882443246\times 10^{9}$
SNR $1549.2018^{+0.0011}_{-0.0022}$ -- $1549.2035$

Detectors: H1

Number of posterior samples: 94128



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A2. Posteriors

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A3. Posteriors

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W28. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.086^{+0.023}_{-0.029}$ -- $10.098$
$m_2~(\mathrm{M}_\odot)$ $1.4129^{+0.0029}_{-0.0024}$ -- $1.4118$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021174^{+0.000048}_{-0.000049}$ -- $3.021190$
$q$ $7.139^{+0.029}_{-0.035}$ -- $7.152$
$t_c$ (s) $1.187008882443471^{+0.000000000000076}_{-0.000000000000126}\times 10^{9}$ -- $1.187008882443535\times 10^{9}$
SNR $1550.4516^{+0.0012}_{-0.0023}$ -- $1550.4532$

Detectors: H1

Number of posterior samples: 94319



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A2. Posteriors

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A3. Posteriors

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W29. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.103^{+0.013}_{-0.022}$ -- $10.112$
$m_2~(\mathrm{M}_\odot)$ $1.4112^{+0.0022}_{-0.0013}$ -- $1.4103$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021208^{+0.000032}_{-0.000035}$ -- $3.021218$
$q$ $7.160^{+0.016}_{-0.027}$ -- $7.171$
$t_c$ (s) $1.187008882443470^{+0.000000000000054}_{-0.000000000000126}\times 10^{9}$ -- $1.187008882443523\times 10^{9}$
SNR $1550.4509^{+0.0012}_{-0.0023}$ -- $1550.4527$

Detectors: H1

Number of posterior samples: 95156



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A2. Posteriors

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A3. Posteriors

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W30. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.119^{+0.012}_{-0.019}$ -- $10.128$
$m_2~(\mathrm{M}_\odot)$ $1.4096^{+0.0020}_{-0.0012}$ -- $1.4087$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021241^{+0.000031}_{-0.000034}$ -- $3.021252$
$q$ $7.179^{+0.015}_{-0.024}$ -- $7.189$
$t_c$ (s) $1.187008882443452^{+0.000000000000042}_{-0.000000000000111}\times 10^{9}$ -- $1.187008882443496\times 10^{9}$
SNR $1550.4460^{+0.0013}_{-0.0023}$ -- $1550.4479$

Detectors: H1

Number of posterior samples: 95945



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A2. Posteriors

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A3. Posteriors

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W31. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.076^{+0.028}_{-0.027}$ -- $10.045$
$m_2~(\mathrm{M}_\odot)$ $1.4139^{+0.0028}_{-0.0028}$ -- $1.4171$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021155^{+0.000052}_{-0.000048}$ -- $3.021105$
$q$ $7.127^{+0.034}_{-0.033}$ -- $7.089$
$t_c$ (s) $1.18700888244343^{+0.00000000000010}_{-0.00000000000011}\times 10^{9}$ -- $1.18700888244334\times 10^{9}$
SNR $1550.3309^{+0.0012}_{-0.0022}$ -- $1550.3326$

Detectors: H1

Number of posterior samples: 94166



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A2. Posteriors

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A3. Posteriors

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W32. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.094^{+0.016}_{-0.023}$ -- $10.109$
$m_2~(\mathrm{M}_\odot)$ $1.4121^{+0.0023}_{-0.0016}$ -- $1.4106$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021188^{+0.000033}_{-0.000036}$ -- $3.021206$
$q$ $7.148^{+0.020}_{-0.028}$ -- $7.166$
$t_c$ (s) $1.187008882443444^{+0.000000000000079}_{-0.000000000000130}\times 10^{9}$ -- $1.187008882443527\times 10^{9}$
SNR $1550.3304^{+0.0011}_{-0.0021}$ -- $1550.3320$

Detectors: H1

Number of posterior samples: 93931



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A2. Posteriors

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A3. Posteriors

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W33. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.112^{+0.014}_{-0.021}$ -- $10.122$
$m_2~(\mathrm{M}_\odot)$ $1.4103^{+0.0022}_{-0.0014}$ -- $1.4093$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021223^{+0.000032}_{-0.000034}$ -- $3.021234$
$q$ $7.170^{+0.017}_{-0.026}$ -- $7.182$
$t_c$ (s) $1.187008882443438^{+0.000000000000058}_{-0.000000000000126}\times 10^{9}$ -- $1.187008882443498\times 10^{9}$
SNR $1550.3225^{+0.0012}_{-0.0022}$ -- $1550.3243$

Detectors: H1

Number of posterior samples: 94701



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A2. Posteriors

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A3. Posteriors

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W34. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.084^{+0.029}_{-0.025}$ -- $10.056$
$m_2~(\mathrm{M}_\odot)$ $1.4131^{+0.0025}_{-0.0029}$ -- $1.4160$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021178^{+0.000050}_{-0.000049}$ -- $3.021134$
$q$ $7.136^{+0.035}_{-0.030}$ -- $7.102$
$t_c$ (s) $1.187008882443388^{+0.000000000000120}_{-0.000000000000089}\times 10^{9}$ -- $1.187008882443306\times 10^{9}$
SNR $1546.6294^{+0.0012}_{-0.0022}$ -- $1546.6311$

Detectors: H1

Number of posterior samples: 94160



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A2. Posteriors

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A3. Posteriors

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W35. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.040^{+0.020}_{-0.021}$ -- $5.040$
$m_2~(\mathrm{M}_\odot)$ $1.4137^{+0.0048}_{-0.0045}$ -- $1.4137$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237188^{+0.000025}_{-0.000026}$ -- $2.237187$
$q$ $3.565^{+0.026}_{-0.027}$ -- $3.565$
$t_c$ (s) $1.187008882443402^{+0.000000000000059}_{-0.000000000000060}\times 10^{9}$ -- $1.187008882443404\times 10^{9}$
SNR $1255.0917^{+0.0012}_{-0.0026}$ -- $1255.0934$

Detectors: H1

Number of posterior samples: 91375



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A2. Posteriors

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A3. Posteriors

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W36. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.096^{+0.021}_{-0.020}$ -- $10.097$
$m_2~(\mathrm{M}_\odot)$ $1.4120^{+0.0020}_{-0.0021}$ -- $1.4118$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021199^{+0.000036}_{-0.000035}$ -- $3.021201$
$q$ $7.150^{+0.025}_{-0.024}$ -- $7.152$
$t_c$ (s) $1.18700888244340^{+0.00000000000011}_{-0.00000000000011}\times 10^{9}$ -- $1.18700888244341\times 10^{9}$
SNR $1546.6292^{+0.0010}_{-0.0022}$ -- $1546.6306$

Detectors: H1

Number of posterior samples: 93409



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A2. Posteriors

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A3. Posteriors

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W37. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.116^{+0.016}_{-0.023}$ -- $10.129$
$m_2~(\mathrm{M}_\odot)$ $1.4099^{+0.0024}_{-0.0016}$ -- $1.4086$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021237^{+0.000033}_{-0.000036}$ -- $3.021253$
$q$ $7.175^{+0.020}_{-0.028}$ -- $7.191$
$t_c$ (s) $1.187008882443403^{+0.000000000000082}_{-0.000000000000132}\times 10^{9}$ -- $1.187008882443478\times 10^{9}$
SNR $1546.6255^{+0.0011}_{-0.0022}$ -- $1546.6270$

Detectors: H1

Number of posterior samples: 93958



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A2. Posteriors

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A3. Posteriors

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W38. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.088^{+0.023}_{-0.024}$ -- $10.097$
$m_2~(\mathrm{M}_\odot)$ $1.4128^{+0.0025}_{-0.0023}$ -- $1.4118$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021178^{+0.000039}_{-0.000046}$ -- $3.021192$
$q$ $7.141^{+0.028}_{-0.030}$ -- $7.152$
$t_c$ (s) $1.18700888244339^{+0.00000000000011}_{-0.00000000000010}\times 10^{9}$ -- $1.18700888244342\times 10^{9}$
SNR $1550.8618^{+0.0011}_{-0.0022}$ -- $1550.8633$

Detectors: H1

Number of posterior samples: 93471



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A2. Posteriors

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A3. Posteriors

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W39. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.086^{+0.021}_{-0.020}$ -- $10.079$
$m_2~(\mathrm{M}_\odot)$ $1.4129^{+0.0020}_{-0.0021}$ -- $1.4137$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021174^{+0.000035}_{-0.000035}$ -- $3.021167$
$q$ $7.139^{+0.026}_{-0.024}$ -- $7.129$
$t_c$ (s) $1.18700888244339^{+0.00000000000012}_{-0.00000000000010}\times 10^{9}$ -- $1.18700888244335\times 10^{9}$
SNR $1550.8618^{+0.0010}_{-0.0022}$ -- $1550.8632$

Detectors: H1

Number of posterior samples: 93544



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A2. Posteriors

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A3. Posteriors

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W40. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.106^{+0.018}_{-0.022}$ -- $10.120$
$m_2~(\mathrm{M}_\odot)$ $1.4109^{+0.0023}_{-0.0018}$ -- $1.4095$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021211^{+0.000034}_{-0.000036}$ -- $3.021227$
$q$ $7.162^{+0.022}_{-0.027}$ -- $7.180$
$t_c$ (s) $1.187008882443397^{+0.000000000000091}_{-0.000000000000125}\times 10^{9}$ -- $1.187008882443480\times 10^{9}$
SNR $1550.8561^{+0.0011}_{-0.0021}$ -- $1550.8576$

Detectors: H1

Number of posterior samples: 93594



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A2. Posteriors

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A3. Posteriors

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W41. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.097^{+0.023}_{-0.027}$ -- $10.115$
$m_2~(\mathrm{M}_\odot)$ $1.4118^{+0.0027}_{-0.0024}$ -- $1.4100$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021204^{+0.000042}_{-0.000049}$ -- $3.021229$
$q$ $7.152^{+0.029}_{-0.033}$ -- $7.174$
$t_c$ (s) $1.18700888244341^{+0.00000000000010}_{-0.00000000000011}\times 10^{9}$ -- $1.18700888244347\times 10^{9}$
SNR $1550.4175^{+0.0011}_{-0.0022}$ -- $1550.4190$

Detectors: H1

Number of posterior samples: 93705



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A2. Posteriors

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A3. Posteriors

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W42. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.098^{+0.019}_{-0.021}$ -- $10.099$
$m_2~(\mathrm{M}_\odot)$ $1.4117^{+0.0021}_{-0.0020}$ -- $1.4116$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021206^{+0.000035}_{-0.000035}$ -- $3.021208$
$q$ $7.153^{+0.024}_{-0.026}$ -- $7.154$
$t_c$ (s) $1.18700888244341^{+0.00000000000010}_{-0.00000000000012}\times 10^{9}$ -- $1.18700888244341\times 10^{9}$
SNR $1550.4175^{+0.0010}_{-0.0022}$ -- $1550.4190$

Detectors: H1

Number of posterior samples: 93469



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A2. Posteriors

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A3. Posteriors

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W43. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.117^{+0.016}_{-0.023}$ -- $10.130$
$m_2~(\mathrm{M}_\odot)$ $1.4098^{+0.0023}_{-0.0016}$ -- $1.4085$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021243^{+0.000033}_{-0.000036}$ -- $3.021258$
$q$ $7.177^{+0.019}_{-0.028}$ -- $7.192$
$t_c$ (s) $1.187008882443412^{+0.000000000000076}_{-0.000000000000131}\times 10^{9}$ -- $1.187008882443483\times 10^{9}$
SNR $1550.4151^{+0.0011}_{-0.0022}$ -- $1550.4167$

Detectors: H1

Number of posterior samples: 94160



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A2. Posteriors

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A3. Posteriors

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W44. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.094^{+0.019}_{-0.028}$ -- $10.101$
$m_2~(\mathrm{M}_\odot)$ $1.4122^{+0.0029}_{-0.0019}$ -- $1.4114$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021180^{+0.000043}_{-0.000050}$ -- $3.021186$
$q$ $7.148^{+0.023}_{-0.034}$ -- $7.157$
$t_c$ (s) $1.187008882443490^{+0.000000000000056}_{-0.000000000000122}\times 10^{9}$ -- $1.187008882443547\times 10^{9}$
SNR $1548.1183^{+0.0013}_{-0.0023}$ -- $1548.1202$

Detectors: H1

Number of posterior samples: 95061



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A2. Posteriors

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A3. Posteriors

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W45. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.103^{+0.012}_{-0.020}$ -- $10.110$
$m_2~(\mathrm{M}_\odot)$ $1.4113^{+0.0020}_{-0.0012}$ -- $1.4105$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021197^{+0.000031}_{-0.000034}$ -- $3.021207$
$q$ $7.158^{+0.015}_{-0.024}$ -- $7.168$
$t_c$ (s) $1.187008882443483^{+0.000000000000042}_{-0.000000000000114}\times 10^{9}$ -- $1.187008882443524\times 10^{9}$
SNR $1548.1182^{+0.0013}_{-0.0023}$ -- $1548.1201$

Detectors: H1

Number of posterior samples: 95363



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A2. Posteriors

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A3. Posteriors

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W46. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.149^{+0.024}_{-0.018}$ -- $5.133$
$m_2~(\mathrm{M}_\odot)$ $1.3901^{+0.0038}_{-0.0051}$ -- $1.3935$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237358^{+0.000028}_{-0.000023}$ -- $2.237342$
$q$ $3.704^{+0.031}_{-0.023}$ -- $3.683$
$t_c$ (s) $1.187008882443212^{+0.000000000000072}_{-0.000000000000047}\times 10^{9}$ -- $1.187008882443161\times 10^{9}$
SNR $1255.0343^{+0.0012}_{-0.0027}$ -- $1255.0361$

Detectors: H1

Number of posterior samples: 91938



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A2. Posteriors

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A3. Posteriors

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W47. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.118^{+0.011}_{-0.017}$ -- $10.126$
$m_2~(\mathrm{M}_\odot)$ $1.4097^{+0.0018}_{-0.0011}$ -- $1.4089$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021231^{+0.000031}_{-0.000032}$ -- $3.021244$
$q$ $7.177^{+0.014}_{-0.021}$ -- $7.187$
$t_c$ (s) $1.187008882443462^{+0.000000000000033}_{-0.000000000000098}\times 10^{9}$ -- $1.187008882443497\times 10^{9}$
SNR $1548.1141^{+0.0013}_{-0.0024}$ -- $1548.1160$

Detectors: H1

Number of posterior samples: 96373



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A2. Posteriors

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A3. Posteriors

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W48. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.076^{+0.026}_{-0.021}$ -- $10.060$
$m_2~(\mathrm{M}_\odot)$ $1.4139^{+0.0021}_{-0.0026}$ -- $1.4156$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021164^{+0.000043}_{-0.000044}$ -- $3.021140$
$q$ $7.126^{+0.031}_{-0.025}$ -- $7.106$
$t_c$ (s) $1.187008882443349^{+0.000000000000127}_{-0.000000000000070}\times 10^{9}$ -- $1.187008882443287\times 10^{9}$
SNR $1552.6468^{+0.0012}_{-0.0023}$ -- $1552.6486$

Detectors: H1

Number of posterior samples: 94394



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A2. Posteriors

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A3. Posteriors

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W49. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.078^{+0.023}_{-0.015}$ -- $10.066$
$m_2~(\mathrm{M}_\odot)$ $1.4138^{+0.0016}_{-0.0024}$ -- $1.4150$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021167^{+0.000036}_{-0.000033}$ -- $3.021157$
$q$ $7.128^{+0.028}_{-0.019}$ -- $7.114$
$t_c$ (s) $1.187008882443352^{+0.000000000000133}_{-0.000000000000072}\times 10^{9}$ -- $1.187008882443276\times 10^{9}$
SNR $1552.6469^{+0.0011}_{-0.0022}$ -- $1552.6485$

Detectors: H1

Number of posterior samples: 94321



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A2. Posteriors

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A3. Posteriors

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W50. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.096^{+0.022}_{-0.018}$ -- $10.089$
$m_2~(\mathrm{M}_\odot)$ $1.4119^{+0.0018}_{-0.0023}$ -- $1.4127$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021203^{+0.000036}_{-0.000035}$ -- $3.021195$
$q$ $7.151^{+0.027}_{-0.022}$ -- $7.141$
$t_c$ (s) $1.187008882443348^{+0.000000000000124}_{-0.000000000000094}\times 10^{9}$ -- $1.187008882443301\times 10^{9}$
SNR $1552.6442^{+0.0010}_{-0.0022}$ -- $1552.6456$

Detectors: H1

Number of posterior samples: 93623



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A2. Posteriors

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A3. Posteriors

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W51. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.098^{+0.024}_{-0.026}$ -- $10.104$
$m_2~(\mathrm{M}_\odot)$ $1.4117^{+0.0027}_{-0.0024}$ -- $1.4111$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021217^{+0.000042}_{-0.000048}$ -- $3.021225$
$q$ $7.153^{+0.029}_{-0.032}$ -- $7.160$
$t_c$ (s) $1.18700888244340^{+0.00000000000011}_{-0.00000000000011}\times 10^{9}$ -- $1.18700888244342\times 10^{9}$
SNR $1559.4498^{+0.0010}_{-0.0022}$ -- $1559.4513$

Detectors: H1

Number of posterior samples: 93515



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A2. Posteriors

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A3. Posteriors

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W52. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.100^{+0.020}_{-0.020}$ -- $10.105$
$m_2~(\mathrm{M}_\odot)$ $1.4116^{+0.0021}_{-0.0020}$ -- $1.4111$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021219^{+0.000034}_{-0.000035}$ -- $3.021224$
$q$ $7.155^{+0.024}_{-0.025}$ -- $7.161$
$t_c$ (s) $1.18700888244340^{+0.00000000000011}_{-0.00000000000011}\times 10^{9}$ -- $1.18700888244343\times 10^{9}$
SNR $1559.4499^{+0.0010}_{-0.0021}$ -- $1559.4513$

Detectors: H1

Number of posterior samples: 93503



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A2. Posteriors

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A3. Posteriors

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W53. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.118^{+0.017}_{-0.023}$ -- $10.127$
$m_2~(\mathrm{M}_\odot)$ $1.4097^{+0.0023}_{-0.0017}$ -- $1.4088$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021254^{+0.000033}_{-0.000036}$ -- $3.021266$
$q$ $7.177^{+0.021}_{-0.028}$ -- $7.189$
$t_c$ (s) $1.187008882443396^{+0.000000000000087}_{-0.000000000000125}\times 10^{9}$ -- $1.187008882443451\times 10^{9}$
SNR $1559.4444^{+0.0011}_{-0.0021}$ -- $1559.4460$

Detectors: H1

Number of posterior samples: 93958



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A2. Posteriors

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A3. Posteriors

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W54. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.087^{+0.025}_{-0.027}$ -- $10.065$
$m_2~(\mathrm{M}_\odot)$ $1.4129^{+0.0027}_{-0.0025}$ -- $1.4151$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021178^{+0.000044}_{-0.000049}$ -- $3.021146$
$q$ $7.139^{+0.030}_{-0.033}$ -- $7.112$
$t_c$ (s) $1.18700888244340^{+0.00000000000011}_{-0.00000000000011}\times 10^{9}$ -- $1.18700888244332\times 10^{9}$
SNR $1552.5499^{+0.0011}_{-0.0022}$ -- $1552.5514$

Detectors: H1

Number of posterior samples: 93163



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A2. Posteriors

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A3. Posteriors

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W55. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.090^{+0.020}_{-0.020}$ -- $10.090$
$m_2~(\mathrm{M}_\odot)$ $1.4125^{+0.0021}_{-0.0020}$ -- $1.4125$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021184^{+0.000035}_{-0.000034}$ -- $3.021186$
$q$ $7.143^{+0.024}_{-0.025}$ -- $7.144$
$t_c$ (s) $1.18700888244340^{+0.00000000000011}_{-0.00000000000011}\times 10^{9}$ -- $1.18700888244340\times 10^{9}$
SNR $1552.5500^{+0.0010}_{-0.0021}$ -- $1552.5514$

Detectors: H1

Number of posterior samples: 93258



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A2. Posteriors

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A3. Posteriors

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W56. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $10.110^{+0.017}_{-0.023}$ -- $10.124$
$m_2~(\mathrm{M}_\odot)$ $1.4105^{+0.0023}_{-0.0017}$ -- $1.4091$
$\mathcal{M}~(\mathrm{M}_\odot)$ $3.021222^{+0.000034}_{-0.000036}$ -- $3.021236$
$q$ $7.168^{+0.020}_{-0.028}$ -- $7.184$
$t_c$ (s) $1.187008882443409^{+0.000000000000080}_{-0.000000000000131}\times 10^{9}$ -- $1.187008882443490\times 10^{9}$
SNR $1552.5410^{+0.0011}_{-0.0022}$ -- $1552.5426$

Detectors: H1

Number of posterior samples: 93997



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A2. Posteriors

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A3. Posteriors

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W57. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.035^{+0.022}_{-0.025}$ -- $5.046$
$m_2~(\mathrm{M}_\odot)$ $1.4149^{+0.0057}_{-0.0049}$ -- $1.4122$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237184^{+0.000030}_{-0.000031}$ -- $2.237196$
$q$ $3.558^{+0.028}_{-0.032}$ -- $3.573$
$t_c$ (s) $1.187008882443430^{+0.000000000000056}_{-0.000000000000069}\times 10^{9}$ -- $1.187008882443484\times 10^{9}$
SNR $1255.3128^{+0.0014}_{-0.0027}$ -- $1255.3148$

Detectors: H1

Number of posterior samples: 95773



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A2. Posteriors

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A3. Posteriors

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W58. NSBH_C_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.046^{+0.018}_{-0.024}$ -- $5.062$
$m_2~(\mathrm{M}_\odot)$ $1.4124^{+0.0054}_{-0.0040}$ -- $1.4088$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237201^{+0.000023}_{-0.000028}$ -- $2.237218$
$q$ $3.573^{+0.023}_{-0.030}$ -- $3.593$
$t_c$ (s) $1.187008882443416^{+0.000000000000051}_{-0.000000000000068}\times 10^{9}$ -- $1.187008882443469\times 10^{9}$
SNR $1255.3125^{+0.0012}_{-0.0026}$ -- $1255.3142$

Detectors: H1

Number of posterior samples: 91220



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A2. Posteriors

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A3. Posteriors

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W59. BBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.153^{+0.023}_{-0.019}$ -- $5.134$
$m_2~(\mathrm{M}_\odot)$ $1.3891^{+0.0041}_{-0.0048}$ -- $1.3932$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237369^{+0.000027}_{-0.000025}$ -- $2.237349$
$q$ $3.710^{+0.029}_{-0.025}$ -- $3.685$
$t_c$ (s) $1.187008882443224^{+0.000000000000066}_{-0.000000000000054}\times 10^{9}$ -- $1.187008882443167\times 10^{9}$
SNR $1255.2479^{+0.0012}_{-0.0026}$ -- $1255.2497$

Detectors: H1

Number of posterior samples: 91943



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A2. Posteriors

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A3. Posteriors

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W60. NSBH_et

A1. Parameter Estimates

Parameter 90% Credible Interval Maximum Posterior Maximum Likelihood
$m_1~(\mathrm{M}_\odot)$ $5.053^{+0.021}_{-0.026}$ -- $5.069$
$m_2~(\mathrm{M}_\odot)$ $1.4108^{+0.0057}_{-0.0047}$ -- $1.4073$
$\mathcal{M}~(\mathrm{M}_\odot)$ $2.237211^{+0.000030}_{-0.000032}$ -- $2.237227$
$q$ $3.582^{+0.027}_{-0.032}$ -- $3.602$
$t_c$ (s) $1.187008882443423^{+0.000000000000052}_{-0.000000000000071}\times 10^{9}$ -- $1.187008882443477\times 10^{9}$
SNR $1252.5995^{+0.0014}_{-0.0027}$ -- $1252.6015$

Detectors: H1

Number of posterior samples: 95013



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A2. Posteriors

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A3. Posteriors

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Additional Files

The following files were also found in this directory: