# Code

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.

A fast Python implementation of Hada & Eisenstein (2018) reconstruction method

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.

Standard (Eisenstein et al. (2007)) reconstruction method

A code executing standard reconstruction algorithm with isotropic reconstruction convention.

The following are a few commonly used functions in LSS analysis. These do not require special packages and run fast.

Triangular-shaped cloud (TSC) particle assignment code

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.

All reconstruction, particle assignment and two-point statistics calculation codes can be found in this repository.

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.