1 citations · 2 across the 4 of their papers we have counts for
4 papers
Attention-Based Neural Network Emulators for Multi-Probe Data Vectors Part II: Assessing Tension Metrics
Evan Saraivanov, Kunhao Zhong, Vivian Miranda +3
The next generation of cosmological surveys is expected to generate unprecedented high-quality data, consequently increasing the already substantial computational costs of Bayesian…
Improving Convolutional Neural Networks for Cosmological Fields with Random Permutation
Kunhao Zhong, Marco Gatti, Bhuvnesh Jain
Convolutional Neural Networks (CNNs) have recently been applied to cosmological fields -- weak lensing mass maps and galaxy maps. However, cosmological maps differ in several ways…
Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part I: Forecasting the Growth-Geometry split
Kunhao Zhong, Evan Saraivanov, James Caputi +4
We present a new class of machine-learning emulators that accurately model the cosmic shear, galaxy-galaxy lensing, and galaxy clustering real space correlation functions in the co…
Constraining Baryonic Physics with DES Y1 and Planck data -- Combining Galaxy Clustering, Weak Lensing, and CMB Lensing
Jiachuan Xu, Tim Eifler, Vivian Miranda +6
We constrain cosmology and baryonic feedback scenarios with a joint analysis of weak lensing, galaxy clustering, cosmic microwave background (CMB) lensing, and their cross-correlat…