Modelling and Mitigating the Systematics in Weak Lensing Measurements Article Swipe
N. Šarčević
,
C. Danielle Leonard
,
Markus M. Rau
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.14602273
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.14602273
Upcoming Stage IV surveys will significantly enhance the precision of weak lensing measurements but require better understanding and treatment of systematics contaminating the weak lensing signal.This thesis explores several approaches to addressing these systematics in the context of the Rubin Observatory’s Legacy Survey of Space and Time (LSST). Firstly, a novel framework is introduced that jointly models the weak lensing source galaxy redshift distribution and the intrinsic alignment of galaxies using a shared luminosity function.The impact of luminosity function parameters on the redshift distribution of a magnitude-limited sample is analyzed.Additionally, the effect of marginalizing over these parameters for standard cosmic shear analysis is demonstrated.Preliminary forecasts suggest this framework can provide cosmological parameter constraints consistent with standard analyses. Secondly, a direct method to infuse the intrinsic alignment (IA) signal into cosmological simulations is tested.These IA-infused simulations validate theoretical models in the nonlinear regime, predict IA impacts on beyond 2-point statistics, and explore the dark matter halo-IA connection.The two-point correlation functions from these simulations are validated using standard sampling analysis. Successful recovery of input parameters is demonstrated for simulations infused with the nonlinear alignment and tidal torquing models.However, further improvements are needed for other models. Thirdly, the impact of different baryon models on cosmological parameter constraints in 3$\times$2pt analyses from LSST is investigated. This study reveals the influence of small-scale physics on constraining power and parameter biases on future LSST analyses.Detailed study highlights the variations in parameter estimation and biases depending on the model, emphasizing the importance of carefully selecting and modeling baryon feedback in cosmological analyses. Lastly, this work details a pipeline and validation methods for forecasting projects.The pipeline's robustness and validation ensure reliable forecasts, highlighting critical steps that enhance the precision and accuracy of cosmological parameter constraints from LSST data.
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- en
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- http://arxiv.org/abs/2406.03352
- https://arxiv.org/pdf/2406.03352
- OA Status
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https://doi.org/10.5281/zenodo.14602273Digital Object Identifier
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Modelling and Mitigating the Systematics in Weak Lensing MeasurementsWork title
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preprintOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-08-30Full publication date if available
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N. Šarčević, C. Danielle Leonard, Markus M. RauList of authors in order
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https://arxiv.org/abs/2406.03352Publisher landing page
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https://arxiv.org/pdf/2406.03352Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.reliable | 272 |
| abstract_inverted_index.sampling | 166 |
| abstract_inverted_index.standard | 98, 115, 165 |
| abstract_inverted_index.torquing | 184 |
| abstract_inverted_index.validate | 135 |
| abstract_inverted_index.Secondly, | 117 |
| abstract_inverted_index.alignment | 67, 125, 181 |
| abstract_inverted_index.analyses. | 116, 254 |
| abstract_inverted_index.analysis. | 167 |
| abstract_inverted_index.carefully | 246 |
| abstract_inverted_index.depending | 238 |
| abstract_inverted_index.different | 197 |
| abstract_inverted_index.forecasts | 104 |
| abstract_inverted_index.framework | 51, 107 |
| abstract_inverted_index.functions | 158 |
| abstract_inverted_index.influence | 215 |
| abstract_inverted_index.intrinsic | 66, 124 |
| abstract_inverted_index.nonlinear | 140, 180 |
| abstract_inverted_index.parameter | 111, 202, 223, 234, 285 |
| abstract_inverted_index.precision | 8, 280 |
| abstract_inverted_index.selecting | 247 |
| abstract_inverted_index.treatment | 18 |
| abstract_inverted_index.two-point | 156 |
| abstract_inverted_index.validated | 163 |
| abstract_inverted_index.IA-infused | 133 |
| abstract_inverted_index.Successful | 168 |
| abstract_inverted_index.addressing | 31 |
| abstract_inverted_index.approaches | 29 |
| abstract_inverted_index.consistent | 113 |
| abstract_inverted_index.estimation | 235 |
| abstract_inverted_index.forecasts, | 273 |
| abstract_inverted_index.highlights | 230 |
| abstract_inverted_index.importance | 244 |
| abstract_inverted_index.introduced | 53 |
| abstract_inverted_index.luminosity | 73, 77 |
| abstract_inverted_index.parameters | 79, 96, 172 |
| abstract_inverted_index.pipeline's | 267 |
| abstract_inverted_index.robustness | 268 |
| abstract_inverted_index.validation | 262, 270 |
| abstract_inverted_index.variations | 232 |
| abstract_inverted_index.constraints | 112, 203, 286 |
| abstract_inverted_index.correlation | 157 |
| abstract_inverted_index.emphasizing | 242 |
| abstract_inverted_index.forecasting | 265 |
| abstract_inverted_index.signal.This | 25 |
| abstract_inverted_index.simulations | 130, 134, 161, 176 |
| abstract_inverted_index.small-scale | 217 |
| abstract_inverted_index.statistics, | 148 |
| abstract_inverted_index.systematics | 20, 33 |
| abstract_inverted_index.theoretical | 136 |
| abstract_inverted_index.3$\times$2pt | 205 |
| abstract_inverted_index.constraining | 220 |
| abstract_inverted_index.cosmological | 110, 129, 201, 253, 284 |
| abstract_inverted_index.demonstrated | 174 |
| abstract_inverted_index.distribution | 63, 83 |
| abstract_inverted_index.function.The | 74 |
| abstract_inverted_index.highlighting | 274 |
| abstract_inverted_index.improvements | 187 |
| abstract_inverted_index.measurements | 12 |
| abstract_inverted_index.projects.The | 266 |
| abstract_inverted_index.tested.These | 132 |
| abstract_inverted_index.contaminating | 21 |
| abstract_inverted_index.investigated. | 210 |
| abstract_inverted_index.marginalizing | 93 |
| abstract_inverted_index.significantly | 5 |
| abstract_inverted_index.understanding | 16 |
| abstract_inverted_index.connection.The | 155 |
| abstract_inverted_index.Observatory’s | 40 |
| abstract_inverted_index.models.However, | 185 |
| abstract_inverted_index.analyses.Detailed | 228 |
| abstract_inverted_index.magnitude-limited | 86 |
| abstract_inverted_index.analyzed.Additionally, | 89 |
| abstract_inverted_index.demonstrated.Preliminary | 103 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile |