KiLeR combines shear ratios with kinematic intrinsic shapes to mitigate first-order lensing systematics and forecasts a 192% improvement in dark energy constraints from the Roman telescope.
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AI techniques for photometric redshift estimation have converged and are now limited by the size, systematics, and selection effects in spectroscopic training samples rather than by methodology.
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Kinematic Lensing Ratio: Reviving Weak Lensing Cosmography as a Geometric Dark Energy Probe
KiLeR combines shear ratios with kinematic intrinsic shapes to mitigate first-order lensing systematics and forecasts a 192% improvement in dark energy constraints from the Roman telescope.
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Machine Learning Techniques for Astrophysics and Cosmology: Photometric Redshifts
AI techniques for photometric redshift estimation have converged and are now limited by the size, systematics, and selection effects in spectroscopic training samples rather than by methodology.