Corrected empirical limits show the most massive galaxies never exceed the theoretical baryonic maximum of 0.16 times halo virial mass, keeping observations consistent with LambdaCDM at all redshifts.
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8 Pith papers cite this work, alongside 252 external citations. Polarity classification is still indexing.
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SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
The TNG SAM reproduces TNG hydro simulation gas and metal flows plus galaxy and halo properties within 30% accuracy out to z=6 via five targeted updates to the Santa Cruz SAM calibrated on stellar feedback-dominated galaxies.
Radio AGN jets inject a total kinetic power density of 10^32 to 10^33 W per cubic megaparsec from z=0 to 2.5, matching requirements for feedback in galaxy evolution models.
A machine learning model trained on IllustrisTNG predicts galaxy baryonic properties from dark matter subhalo features, producing a mock catalog for the A-SPEC survey that matches observed galaxy clustering.
Including radiative losses in analytic models of high-redshift radio galaxies reduces predicted radio and X-ray luminosities compared to models that neglect them.
MeerKLASS applies on-the-fly imaging on MeerKAT for a 10,000 sq. deg. UHF-band continuum survey at 14 arcsec resolution and 25 μJy/beam rms, run commensally with HI intensity mapping.
Reviews multiple higher-order statistics for 21-cm intensity mapping and forecasts their detectability with SKAO, incorporating noise and foreground effects.
citing papers explorer
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Empirical estimates of how massive galaxies can be in {\Lambda}CDM
Corrected empirical limits show the most massive galaxies never exceed the theoretical baryonic maximum of 0.16 times halo virial mass, keeping observations consistent with LambdaCDM at all redshifts.
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Cosmological constraints from the small scale clustering of Emission Line Galaxies
SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
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TNG SAM: Bridging Hydrodynamical Complexity and Semi-Analytic Efficiency to Model Galaxy Formation
The TNG SAM reproduces TNG hydro simulation gas and metal flows plus galaxy and halo properties within 30% accuracy out to z=6 via five targeted updates to the Santa Cruz SAM calibrated on stellar feedback-dominated galaxies.
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A population-based approach to understanding radio AGN feedback with LOFAR: The LoTSS Deep Fields
Radio AGN jets inject a total kinetic power density of 10^32 to 10^33 W per cubic megaparsec from z=0 to 2.5, matching requirements for feedback in galaxy evolution models.
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Constructing a Mock Galaxy Catalog for the All-sky SPECtroscopic Survey of Nearby Galaxies (A-SPEC) Using the Machine-assisted Semi-Simulation Model
A machine learning model trained on IllustrisTNG predicts galaxy baryonic properties from dark matter subhalo features, producing a mock catalog for the A-SPEC survey that matches observed galaxy clustering.
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A simulation-based analytic model of radio galaxies II: self-consistent radiative losses
Including radiative losses in analytic models of high-redshift radio galaxies reduces predicted radio and X-ray luminosities compared to models that neglect them.
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Fast Simultaneous Surveys with On-the-Fly Mapping
MeerKLASS applies on-the-fly imaging on MeerKAT for a 10,000 sq. deg. UHF-band continuum survey at 14 arcsec resolution and 25 μJy/beam rms, run commensally with HI intensity mapping.
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Cosmology with Intensity Mapping via Statistics Beyond the Power Spectrum in the SKAO Era
Reviews multiple higher-order statistics for 21-cm intensity mapping and forecasts their detectability with SKAO, incorporating noise and foreground effects.