PRFM-vol is a new subgrid star formation model for cosmological simulations that computes SFR from ambient densities via PRFM theory and a modified effective EOS, producing taller stellar scale heights, slightly higher stellar mass, and morphology changes including Toomre-driven clumps compared to p
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3 Pith papers cite this work, alongside 299 external citations. Polarity classification is still indexing.
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representative citing papers
Composite time-delay lens modelling of JWST WFI2033–4723 yields intermediate stellar IMF normalisation and a steep gNFW inner slope γ_in≃1.3 that is robust to the choice of external cosmology.
Simulations indicate LISA could statistically distinguish CDM from SIDM (constant 1 cm²/g cross-section) with at least ~70 high-SNR massive black hole merger detections.
citing papers explorer
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Learning the Universe with PRFM-vol: Introducing a new subgrid model for star formation in cosmological simulations
PRFM-vol is a new subgrid star formation model for cosmological simulations that computes SFR from ambient densities via PRFM theory and a modified effective EOS, producing taller stellar scale heights, slightly higher stellar mass, and morphology changes including Toomre-driven clumps compared to p
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Disentangling the dark and stellar mass through precise lens modelling of the JWST observation of lensed quasar WFI2033--4723
Composite time-delay lens modelling of JWST WFI2033–4723 yields intermediate stellar IMF normalisation and a steep gNFW inner slope γ_in≃1.3 that is robust to the choice of external cosmology.
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Probing the Nature of Dark Matter Self-Interactions Through Observations of Massive Black Hole Mergers
Simulations indicate LISA could statistically distinguish CDM from SIDM (constant 1 cm²/g cross-section) with at least ~70 high-SNR massive black hole merger detections.