Filter-substrate refraction causes dominant lateral shifts yielding 0.3-0.4% PSF size and ellipticity residuals across most Roman bands that exceed weak lensing requirements by an order of magnitude, while longitudinal defocus shifts remain negligible.
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5 Pith papers cite this work, alongside 97 external citations. Polarity classification is still indexing.
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Galaxy clusters have an average projected ellipticity of 0.310 with axis ratio 0.527, showing no significant mass or redshift dependence, measured via weak lensing on DES Y3 data and verified with mocks.
IRMaGiC extends redMaGiC to z=1-2 using joint LSST optical and Roman infrared data, reducing photo-z scatter and bias for LRGs.
A machine learning model trained on IllustrisTNG predicts galaxy baryonic properties from dark matter subhalo features, producing a mock catalog for the A-SPEC survey that matches observed galaxy clustering.
Lecture series on the physics, phenomenology, and statistics of large-scale cosmic structure evolution and non-Gaussian predictions.
citing papers explorer
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Modeling the impact of filter-substrate refraction in the Roman point spread function
Filter-substrate refraction causes dominant lateral shifts yielding 0.3-0.4% PSF size and ellipticity residuals across most Roman bands that exceed weak lensing requirements by an order of magnitude, while longitudinal defocus shifts remain negligible.
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Constraining Galaxy Cluster Triaxiality via Weak Lensing -- I. Preparation for the Rubin Data Beyond Leading Order
Galaxy clusters have an average projected ellipticity of 0.310 with axis ratio 0.527, showing no significant mass or redshift dependence, measured via weak lensing on DES Y3 data and verified with mocks.
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IRMaGiC: Extending Luminous Red Galaxy Selection into the Infrared with Joint Rubin Observatory's Large Survey of Space Time and Roman's High Latitude Imaging Survey
IRMaGiC extends redMaGiC to z=1-2 using joint LSST optical and Roman infrared data, reducing photo-z scatter and bias for LRGs.
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Constructing a Mock Galaxy Catalog for the All-sky SPECtroscopic Survey of Nearby Galaxies (A-SPEC) Using the Machine-assisted Semi-Simulation Model
A machine learning model trained on IllustrisTNG predicts galaxy baryonic properties from dark matter subhalo features, producing a mock catalog for the A-SPEC survey that matches observed galaxy clustering.
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Large-scale structures of the Universe: physics, phenomenology, statistics
Lecture series on the physics, phenomenology, and statistics of large-scale cosmic structure evolution and non-Gaussian predictions.