A denoising diffusion model trained on transformed JWST observations generates multi-band galaxy images that match key statistical properties of real galaxies for Roman weak lensing simulations.
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A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.
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Diffusion-based Galaxy Simulations for the Roman High Latitude Survey
A denoising diffusion model trained on transformed JWST observations generates multi-band galaxy images that match key statistical properties of real galaxies for Roman weak lensing simulations.
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Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.