Capturing transients: an application of biostatistics to astronomy
| dc.contributor.advisor | Mcbride, Vanessa | |
| dc.contributor.advisor | Groot, Paul | |
| dc.contributor.author | van Dyk, Anke | |
| dc.date.accessioned | 2022-06-30T16:52:50Z | |
| dc.date.available | 2022-06-30T16:52:50Z | |
| dc.date.issued | 2022 | |
| dc.date.updated | 2022-06-30T14:56:54Z | |
| dc.description.abstract | Capture-recapture has been identified as a possible use case for estimating the underlying size of astrophysical transient populations. In this work, we present a series of exploratory analyses using capture-recapture methods from biostatistics. In the first of three separate analyses, we reproduce results of Laycock (2017). Strategically sampled X-ray lightcurves of simulated populations of high mass X-ray binaries (HMXBs) are used to probe estimator behaviour and efficiency. Overall, these statistically closed population estimators converge to the input population with increasing number of observations, yet estimator efficiency is shown to be significantly be affected by sampling strategy. I then employ nonstandard estimator models to account for variations in capture probability of individuals within the population, categorised into ‘behavioural', ‘temporal', and ‘heterogeneous' effects. In the second analysis, we present a methodology for closed population capture-recapture analysis using real data from the OGLE-IV XROM survey. The data samples consisted of observations that were grouped into epochs. The large variation in quiescent magnitude of the population creates heterogeneity in the capture probability of sources which requires non-standard modelling. Estimation of population size is therefore limited by the choice of observational magnitude threshold. Bias corrected estimation proves to be potentially useful in this context. In the third and final investigation, we present a ‘robust design' approach with a population of Dwarf Nova located towards and in the Galactic Bulge identified from the OGLE-II, -III, and -IV phases. This approach combines closed and open population practices that allows new individuals identified between the survey phases to be added to the study sample for dynamical estimation. These investigations provide a future course for population size estimation of transients and variable stellar population alongside population synthesis simulations. The generation of capture histories remain non-trivial through the choice of observation grouping, brightness scale, and imposed flux threshold. Further, there remain several unexplored avenues of inquiry and refinement for this methodology pertaining to astronomy using explanatory variables in the modelling. Recommendations are made for further exploration of the topic. | |
| dc.identifier.apacitation | van Dyk, A. (2022). <i>Capturing transients: an application of biostatistics to astronomy</i>. (). ,Faculty of Science ,Department of Astronomy. Retrieved from http://hdl.handle.net/11427/36593 | en_ZA |
| dc.identifier.chicagocitation | van Dyk, Anke. <i>"Capturing transients: an application of biostatistics to astronomy."</i> ., ,Faculty of Science ,Department of Astronomy, 2022. http://hdl.handle.net/11427/36593 | en_ZA |
| dc.identifier.citation | van Dyk, A. 2022. Capturing transients: an application of biostatistics to astronomy. . ,Faculty of Science ,Department of Astronomy. http://hdl.handle.net/11427/36593 | en_ZA |
| dc.identifier.ris | TY - Master Thesis AU - van Dyk, Anke AB - Capture-recapture has been identified as a possible use case for estimating the underlying size of astrophysical transient populations. In this work, we present a series of exploratory analyses using capture-recapture methods from biostatistics. In the first of three separate analyses, we reproduce results of Laycock (2017). Strategically sampled X-ray lightcurves of simulated populations of high mass X-ray binaries (HMXBs) are used to probe estimator behaviour and efficiency. Overall, these statistically closed population estimators converge to the input population with increasing number of observations, yet estimator efficiency is shown to be significantly be affected by sampling strategy. I then employ nonstandard estimator models to account for variations in capture probability of individuals within the population, categorised into ‘behavioural', ‘temporal', and ‘heterogeneous' effects. In the second analysis, we present a methodology for closed population capture-recapture analysis using real data from the OGLE-IV XROM survey. The data samples consisted of observations that were grouped into epochs. The large variation in quiescent magnitude of the population creates heterogeneity in the capture probability of sources which requires non-standard modelling. Estimation of population size is therefore limited by the choice of observational magnitude threshold. Bias corrected estimation proves to be potentially useful in this context. In the third and final investigation, we present a ‘robust design' approach with a population of Dwarf Nova located towards and in the Galactic Bulge identified from the OGLE-II, -III, and -IV phases. This approach combines closed and open population practices that allows new individuals identified between the survey phases to be added to the study sample for dynamical estimation. These investigations provide a future course for population size estimation of transients and variable stellar population alongside population synthesis simulations. The generation of capture histories remain non-trivial through the choice of observation grouping, brightness scale, and imposed flux threshold. Further, there remain several unexplored avenues of inquiry and refinement for this methodology pertaining to astronomy using explanatory variables in the modelling. Recommendations are made for further exploration of the topic. DA - 2022_ DB - OpenUCT DP - University of Cape Town KW - astronomy LK - https://open.uct.ac.za PY - 2022 T1 - Capturing transients: an application of biostatistics to astronomy TI - Capturing transients: an application of biostatistics to astronomy UR - http://hdl.handle.net/11427/36593 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/36593 | |
| dc.identifier.vancouvercitation | van Dyk A. Capturing transients: an application of biostatistics to astronomy. []. ,Faculty of Science ,Department of Astronomy, 2022 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/36593 | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | Department of Astronomy | |
| dc.publisher.faculty | Faculty of Science | |
| dc.subject | astronomy | |
| dc.title | Capturing transients: an application of biostatistics to astronomy | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationlevel | MSc |