| ... | ... | @@ -10,6 +10,11 @@ If the mismatches, defined as the log of the absolute difference between (natura |
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By rejection sampling using the weights (true vs approximate likelihood ratios), we can find the fraction of samples obtained.
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If the rejection sampling efficiency is small, then we can say that the approximation failed and we should repeat with a more robust method.
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We do _not_ attempt to validate the performance of the automatic fiducial point finding using likelihood optimization.
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We also do not test the method on any waveform models with higher-order modes where the approximation is expected to be less robust.
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The importance sampling can be automatically performed by `bilby_pipe` using the `reweighting-configuration` argument.
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## [Unit testing](https://git.ligo.org/lscsoft/bilby/-/blob/master/test/gw/likelihood/relative_binning_test.py)
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As part of the `Bilby` CI unit testing, we verify that the binned likelihood agrees with the regular likelihood as the reference point for a range of cases.
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| ... | ... | @@ -52,7 +57,7 @@ The fiducial BNS injection has been analyzed with the relative binning likelihoo |
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In all cases where a suitable starting point was provided, we see good agreement with the ROQ-likelihood runs and good resampling efficiency.
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Here is the distribution of likelihood mismatches for two identical analyses of the fiducial BNS signal with a processing spin prior with magnitudes up to 0.4 and tidal deformability up to 5000.
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Here is the distribution of likelihood mismatches for [two identical analyses of the fiducial BNS signal](https://ldas-jobs.ligo.caltech.edu/~colm.talbot/O4/setup_configurations/outdir_dynesty_relbin_medSpin_precessing_cal/) with a processing spin prior with magnitudes up to 0.4 and tidal deformability up to 5000.
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The legend entries show the fraction of samples surviving rejection sampling.
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It is very close to 1.
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| ... | ... | @@ -60,6 +65,7 @@ It is very close to 1. |
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By accident, we performed some runs with fiducial parameters that are a very bad fit to the actual signal.
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In this case, we found that the rejection sampling efficiency was very small with large mismatches.
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The corresponding analysis can be found at `/home/sylvia.biscoveanu/bilby_pipe/runs/review_test/O4/fiducial_bns_PhenomTidal_take2/outdir_dynesty_relbin_medSpin_precessing_cal`.
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