Vision transformer models segment proto-halo regions in initial cosmological density fields by final mass at z=0, outperforming both CNNs and the PINOCCHIO perturbation-theory code.
The Gaussian streaming model and Lagrangian effective field theory
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abstract
We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion. After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order. We discuss the connection to the Gaussian peaks formalism. We compare the ingredients of the GSM to a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum. We highlight the importance of a general biasing scheme, which we find to be as important as higher-order corrections due to non-linear evolution for the halos we consider on the scales of interest to us.
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FolpsD combines EFT power spectrum and tree-level bispectrum with damping to enable joint analyses that improve cosmological constraints from DESI-like galaxy mocks by up to 30% on As and omega_cdm while extending the usable k-range without significant biases for LRG samples.
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Segmenting proto-halos with vision transformers
Vision transformer models segment proto-halo regions in initial cosmological density fields by final mass at z=0, outperforming both CNNs and the PINOCCHIO perturbation-theory code.
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FolpsD: combining EFT and phenomenological approaches for joint power spectrum and bispectrum analyses
FolpsD combines EFT power spectrum and tree-level bispectrum with damping to enable joint analyses that improve cosmological constraints from DESI-like galaxy mocks by up to 30% on As and omega_cdm while extending the usable k-range without significant biases for LRG samples.