This is code for a convolutional neural network model for reconstruction of the initial conditions, accompanying my CNN reconstruction paper. It uses PyTorch library. Trainer and inference codes are both included.
This is a code that implements the Hada & Eisenstein (2018) reconstruction algorithm in Python, with a few calculation simplifications for the original algorithm, accompanying my reconstruction analysis paper.
The following are a few commonly used functions in LSS analysis. These do not require special packages and run fast.
This code implements the triangular-shaped cloud particle assignment scheme, and includes periodic boundary conditions.
Two-point statistics calculation (a few scripts inside this repository)
This includes calculations of multipole power spectrum, two-point correlation function, cross-correlation coefficient and propagator, on a grid. Two-point correlation function is calculated via FFT.
This is a BAO fitting code that uses a fitting model largely follows Beutler et al. (2017) and in Fourier space. Fits are performed on a grid. This code does not require any special packges to run.