7 papers
Machine Learning and the SKA for Cosmic Dawn and the Epoch of Reionization
Anshuman Acharya, Michele Bianco, Daniela Breitman +18
When operational, the SKA will generate unprecedented amounts of data and provide exquisite sensitivity for 21 cm tomography of Cosmic Dawn (CD) and the Epoch of Reionization (EoR)…
Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?
Emanuel Sommer, Kangning Diao, Jakob Robnik +2
Scaling inference methods such as Markov chain Monte Carlo to high-dimensional models remains a central challenge in Bayesian deep learning. A promising recent proposal, microcanon…
Multi-fidelity emulator for large-scale 21 cm lightcone images: a few-shot transfer learning approach with generative adversarial network
Kangning Diao, Yi Mao
Emulators using machine learning techniques have emerged to efficiently generate mock data matching the large survey volume for upcoming experiments, as an alternative approach to…
Detecting Modeling Bias with Continuous Time Flow Models on Weak Lensing Maps
Kangning Diao, Biwei Dai, Uros Seljak
Simulation-based inference provides a powerful framework for extracting rich information from nonlinear scales in current and upcoming cosmological surveys, and ensuring its robust…
Modeling Foreground Spatial Variations in 21 cm Gaussian Process Component Separation
Kangning Diao, Richard D. P. Grumitt, Yi Mao
Gaussian processes (GPs) have been extensively utilized as nonparametric models for component separation in 21 cm data analyses. This exploits the distinct spectral behavior of the…
: A Differentiable and GPU-accelerated Synchrotron Simulation Package
Kangning Diao, Zack Li, Richard D. P. Grumitt +1
We introduce synax, a novel library for automatically differentiable simulation of Galactic synchrotron emission. Built on the JAX framework, synax leverages JAX's capabilities, in…