Conditioning CAMELS-SAM simulations on the stellar mass function or stellar-to-halo mass relation reduces uncertainty in b_phi by 88-97% for DESI emission line galaxy samples while remaining consistent across galaxy formation variations.
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9 Pith papers cite this work, alongside 548 external citations. Polarity classification is still indexing.
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Mutual information analysis of TNG50 simulations shows gravitational potential and total energy retain merger mass and infall time information longest, while radial velocity loses it within ~5 Gyr, with washout depending on radius, merger age, and mass.
Simulations show gas cooling and stellar feedback dominate assembly bias for stellar-mass selected galaxies while star formation gives way to gas cooling for SFR-selected galaxies as number density rises.
Simulations demonstrate that high-specific-energy supernova outflows sustain hot CGM at virial temperature, raise t_cool/t_ff above 10, and transition dwarf galaxy feedback from ejective to preventive mode around 5 Gyr.
Joint real and redshift space analysis of CosmicFlows-4++ yields BAO scales of 132±8 h^{-1}Mpc (real) and 139±7 h^{-1}Mpc (redshift) at z=0.07 together with fσ8=0.344±0.105.
A conditional graph neural network serves as an accurate and fast surrogate for semi-analytic galaxy formation models, predicting key properties across cosmic time.
An extended parametric model for SIDM halos incorporates mass accretion to delay core collapse and reduces errors in predicted V_max at z=0 relative to the prior Yang et al. (2024b) model.
Convolutional neural networks can infer galaxy cluster virial masses and scale radii from 2D projected position and line-of-sight velocity distributions with nearly unbiased results and reduced scatter when richness is added or training is limited to relaxed systems.
FOGGIE cosmological simulations find that less HI-populated CGMs produce thin, coherently rotating extended disks while more populated CGMs yield irregular morphologies, with all systems settling kinematically by z=0 independent of mass.
citing papers explorer
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Informative Priors on Primordial Non-Gaussianity Bias $b_{\phi}$ From Galaxy Formation
Conditioning CAMELS-SAM simulations on the stellar mass function or stellar-to-halo mass relation reduces uncertainty in b_phi by 88-97% for DESI emission line galaxy samples while remaining consistent across galaxy formation variations.
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Galactic Amnesia: The Information Washout of the Milky Way Merger History
Mutual information analysis of TNG50 simulations shows gravitational potential and total energy retain merger mass and infall time information longest, while radial velocity loses it within ~5 Gyr, with washout depending on radius, merger age, and mass.
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Correlation between baryonic process and galaxy assembly bias
Simulations show gas cooling and stellar feedback dominate assembly bias for stellar-mass selected galaxies while star formation gives way to gas cooling for SFR-selected galaxies as number density rises.
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How High-Specific-Energy Winds Regulate the Circumgalactic Medium of Dwarf Galaxies
Simulations demonstrate that high-specific-energy supernova outflows sustain hot CGM at virial temperature, raise t_cool/t_ff above 10, and transition dwarf galaxy feedback from ejective to preventive mode around 5 Gyr.
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Measuring $f\sigma_8$ and BAO scale in the Local Universe: a joint real and redshift space analysis from CosmicFlows-4++
Joint real and redshift space analysis of CosmicFlows-4++ yields BAO scales of 132±8 h^{-1}Mpc (real) and 139±7 h^{-1}Mpc (redshift) at z=0.07 together with fσ8=0.344±0.105.
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A graph-based Neural Network surrogate model for accelerating semi-analytical model of galaxy formation and evolution
A conditional graph neural network serves as an accurate and fast surrogate for semi-analytic galaxy formation models, predicting key properties across cosmic time.
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An Extended Parametric Model for Self-interacting Dark Matter Halos
An extended parametric model for SIDM halos incorporates mass accretion to delay core collapse and reduces errors in predicted V_max at z=0 relative to the prior Yang et al. (2024b) model.
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Inferring Halo Mass and Scale Radius of Galaxy Clusters Using Convolutional Neural Networks and Uchuu-UniverseMachine Catalogs
Convolutional neural networks can infer galaxy cluster virial masses and scale radii from 2D projected position and line-of-sight velocity distributions with nearly unbiased results and reduced scatter when richness is added or training is limited to relaxed systems.
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FOGGIE: Figuring Out Gas & Galaxies In Enzo XII. The Formation and Evolution of Extended HI Galactic Disks and Warps with a Dynamic Circumgalactic medium
FOGGIE cosmological simulations find that less HI-populated CGMs produce thin, coherently rotating extended disks while more populated CGMs yield irregular morphologies, with all systems settling kinematically by z=0 independent of mass.