... | @@ -38,13 +38,13 @@ The above plot shows the array of the eigenvalues. This plot indicates that the |
... | @@ -38,13 +38,13 @@ The above plot shows the array of the eigenvalues. This plot indicates that the |
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## GW190814
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## GW190814
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First, we demonstrate an example from the GW190814 event to find an appropriate cut-off on the low-rank approximation of the covariance matrix, and its effect on $`\beta`$. We choose top 5 [PE samples](https://ldas-jobs.ligo.caltech.edu/~charlie.hoy/PE/O3/S190814bv/C01/SEOBNRv4HM/samples/SEOBNRv4HM_pesummary.dat) ( largest likelihood values ) and plot $`\beta`$ as a function of the rank of the covariance matrix.
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First, we demonstrate an example from the GW190814 event to find an appropriate cut-off on the low-rank approximation of the covariance matrix, and its effect on $`\beta`$. We choose top 5 [PE samples](https://ldas-jobs.ligo.caltech.edu/~charlie.hoy/PE/O3/S190814bv/C01/SEOBNRv4HM/samples/SEOBNRv4HM_pesummary.dat) ( largest likelihood values ) and plot $`\beta`$ as a function of the rank of the covariance matrix.
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| m1 | m2 | s1z | s2z | logLikelihood |
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| m1 | m2 | s1z | s2z | logLikelihood | beta |
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| ------- | ------- | -------- | ------- | -------------- |
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| ------- | ------- | -------- | ------- | -------------- | ------ |
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| 24.2080 | 2.7402 | -0.0031 | -0.1011 | -45762.6371 |
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| 24.2080 | 2.7402 | -0.0031 | -0.1011 | -45762.6371 | 8.7 |
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| 24.2444 | 2.7392 | -0.0162 | 0.1414 | -45762.8520 |
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| 24.2444 | 2.7392 | -0.0162 | 0.1414 | -45762.8520 | 8.5 |
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| 23.4810 | 2.7965 | -0.0026 | -0.5558 | -45763.1355 |
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| 23.4810 | 2.7965 | -0.0026 | -0.5558 | -45763.1355 | 8.1 |
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| 24.0278 | 2.7539 | -0.0236 | 0.0809 | -45763.1803 |
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| 24.0278 | 2.7539 | -0.0236 | 0.0809 | -45763.1803 | 8.2 |
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| 23.5563 | 2.7887 | 0.0045 | -0.6138 | -45763.2090 |
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| 23.5563 | 2.7887 | 0.0045 | -0.6138 | -45763.2090 | 8.1 |
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The spectrum of the eigenvalues is also plotted.
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The spectrum of the eigenvalues is also plotted.
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