Fast Wiener filtering of CMB maps with Neural Networks

Understand

We show how a neural network can be trained to Wiener filter masked CMB maps to high accuracy.

• We propose an innovative neural network architecture, the WienerNet, which guarantees linearity in the data map.
• Our method does not require Wiener filtered training data, but rather learns Wiener filtering from tailored loss functions which are mathematically guaranteed to be minimized by the exact solution.
• Once trained, the neural network Wiener filter is extremely fast, about a factor of 1000 faster than the standard conjugate gradient method.