Derives the power spectrum evolution and cross-spectra for arbitrary multi-species wave and particle dark matter, incorporating free-streaming, Jeans scales, and intrinsic fluctuations.
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A 1D convolutional neural network reconstructs the dark-matter phase-space distribution from the matter power spectrum with greater accuracy and broader applicability than an earlier empirical formula.
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Growth of Structure in Multi-species Wave Dark Matter
Derives the power spectrum evolution and cross-spectra for arbitrary multi-species wave and particle dark matter, incorporating free-streaming, Jeans scales, and intrinsic fluctuations.
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Machine Learning Does It and Does It Better: Unearthing Primordial Dark-Matter Velocities from the Matter Power Spectrum
A 1D convolutional neural network reconstructs the dark-matter phase-space distribution from the matter power spectrum with greater accuracy and broader applicability than an earlier empirical formula.