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A lightweight python-based package to compute mock parameter estimation (PE) posteriors for gravitational wave events and generate synthetic catalogs. This is the version of GWMockCat used to produce mock catalogs for "Things that might go bump in the night: Assessing structure in the binary black hole mass spectrum". To use the code, we recommend navigating to its gitlab repository and following the installation instructions therein.
gravitational waves, bayesian inference, mass distribution, compact binary coalesence, populations
gravitational waves, bayesian inference, mass distribution, compact binary coalesence, populations
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 1 |

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