128 citations · 501 across the 12 of their papers we have counts for
12 papers
Robust marginalization of baryonic effects for cosmological inference at the field level
Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar +11
We train neural networks to perform likelihood-free inference from 2D maps containing the total mass surface density from thousands of hydrodynamic simula…
Multifield Cosmology with Artificial Intelligence
Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel +10
Astrophysical processes such as feedback from supernovae and active galactic nuclei modify the properties and spatial distribution of dark matter, gas, and galaxies in a poorly und…
Simultaneously constraining cosmology and baryonic physics via deep learning from weak lensing
Tianhuan Lu, Zoltán Haiman, José Manuel Zorrilla Matilla
Ongoing and planned weak lensing (WL) surveys are becoming deep enough to contain information on angular scales down to a few arcmin. To fully extract information from these small…
Cosmological Constraints from Weak Lensing Peaks: Can Halo Models Accurately Predict Peak Counts?
Alina Sabyr, Zoltán Haiman, José Manuel Zorrilla Matilla +1
In order to extract full cosmological information from next-generation large and high-precision weak lensing (WL) surveys (e.g. Euclid, Roman, LSST), higher-order statistics that p…
Interpreting deep learning models for weak lensing
José Manuel Zorrilla Matilla, Manasi Sharma, Daniel Hsu +1
Deep Neural Networks (DNNs) are powerful algorithms that have been proven capable of extracting non-Gaussian information from weak lensing (WL) data sets. Understanding which featu…
Optimizing simulation parameters for weak lensing analyses involving non-Gaussian observables
José Manuel Zorrilla Matilla, Stefan Waterval, Zoltán Haiman
We performed a series of numerical experiments to quantify the sensitivity of the predictions for weak lensing statistics obtained in raytracing DM-only simulations, to two hyper-p…
Probing gaseous galactic halos through the rotational kSZ effect
José Manuel Zorrilla Matilla, Zoltán Haiman
The rotational kinematic Sunyaev-Zeldovich (rkSZ) signal, imprinted on the cosmic microwave background (CMB) by the gaseous halos (spinning "atmospheres") of foreground galaxies, w…
Constraining neutrino mass with tomographic weak lensing peak counts
Zack Li, Jia Liu, José Manuel Zorrilla Matilla +1
Massive cosmic neutrinos change the structure formation history by suppressing perturbations on small scales. Weak lensing data from galaxy surveys probe the structure evolution an…
Non-Gaussian information from weak lensing data via deep learning
Arushi Gupta, José Manuel Zorrilla Matilla, Daniel Hsu +1
Weak lensing maps contain information beyond two-point statistics on small scales. Much recent work has tried to extract this information through a range of different observables o…
MassiveNuS: Cosmological Massive Neutrino Simulations
Jia Liu, Simeon Bird, José Manuel Zorrilla Matilla +5
The non-zero mass of neutrinos suppresses the growth of cosmic structure on small scales. Since the level of suppression depends on the sum of the masses of the three active neutri…
Geometry and growth contributions to cosmic shear observables
José Manuel Zorrilla Matilla, Zoltán Haiman, Andrea Petri +1
We explore the sensitivity of weak lensing observables to the expansion history of the universe and to the growth of cosmic structures, as well as the relative contribution of both…
Do dark matter halos explain lensing peaks?
José Manuel Zorrilla Matilla, Zoltán Haiman, Daniel Hsu +2
We have investigated a recently proposed halo-based model, Camelus, for predicting weak-lensing peak counts, and compared its results over a collection of 162 cosmologies with thos…