A cross-entropy metric is introduced to distinguish transient populations and support novelty detection for LSST observing strategy optimization.
Science-driven Optimization of the LSST Observing Strategy
2 Pith papers cite this work. Polarity classification is still indexing.
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Simulated likelihood analysis shows Limber approximation, neglected RSD, and approximate nonlinear power spectra each induce cosmological biases of ~1 sigma or more (exceeding 2 sigma for Rubin) in Roman and Rubin 3x2pt studies.
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An Information-Theoretic Metric for Transient Classification and Novelty Detection
A cross-entropy metric is introduced to distinguish transient populations and support novelty detection for LSST observing strategy optimization.
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Accurate modeling for 3$\times$2pt analyses in Roman and Rubin: a study of model approximations
Simulated likelihood analysis shows Limber approximation, neglected RSD, and approximate nonlinear power spectra each induce cosmological biases of ~1 sigma or more (exceeding 2 sigma for Rubin) in Roman and Rubin 3x2pt studies.