47 citations · 289 across the 13 of their papers we have counts for
5 papers · 1 filter
Non-parametric Lagrangian biasing from the insights of neural nets
Xiaohan Wu, Julian B. Munoz, Daniel J. Eisenstein
We present a Lagrangian model of galaxy clustering bias in which we train a neural net using the local properties of the smoothed initial density field to predict the late-time mas…
A fully Lagrangian, non-parametric bias model for dark-matter halos
Xiaohan Wu, Julian B. Munoz, Daniel Eisenstein
We present a non-parametric Lagrangian biasing model and fit the ratio of the halo and mass densities at the field level using the mass-weighted halo field in the AbacusSummit simu…
The high-redshift tail of stellar reionization in LCDM is beyond the reach of the low- CMB
Xiaohan Wu, Matthew McQuinn, Daniel Eisenstein +1
The first generation (Pop-III) stars can ionize 1-10% of the universe by , when the metal-enriched (Pop-II) stars may contribute negligibly to the ionization. This low ioniza…
On the accuracy of common moment-based radiative transfer methods for simulating reionization
Xiaohan Wu, Matthew McQuinn, Daniel Eisenstein
Cosmological simulations of reionization often treat radiative transfer by solving for the monopole and dipoles of the intensity field and by making ansatz for the quadrupole momen…
Imprints of temperature fluctuations on the Lyman- forest: a view from radiation-hydrodynamic simulations of reionization
Xiaohan Wu, Matthew McQuinn, Rahul Kannan +5
Reionization leads to large spatial fluctuations in the intergalactic temperature that can persist well after its completion. We study the imprints of such fluctuations on the $z\s…