CosmoWAP
Cosmological Python package for forecasts of Large-Scale Structutre clustering with the fourier power spectra and bispectra. Focusing on large scales with the inclusion of wide-separation, relativistic and primordial non-gaussianity.
Install / Use
/learn @craddis1/CosmoWAPREADME
CosmoWAP
______ _ _____ ____
/ ____/___ _________ ___ ____| | / / | / __ \
/ / / __ \/ ___/ __ `__ \/ __ \ | /| / / /| | / /_/ /
/ /___/ /_/ (__ ) / / / / / /_/ / |/ |/ / ___ |/ ____/
\____/\____/____/_/ /_/ /_/\____/|__/|__/_/ |_/_/
Cosmology with Wide-separation, relAtivistic and Primordial non-Gaussian contributions.
CosmoWAP is an effort to provide a (hopefully) self consistent framework to compute contributions within standard perturbation theory to the Fourier power spectrum and bispectrum including wide-separation and relativistic effects as well as Primordial non-Gaussianity (PNG). These expressions can be very cumbersome and it can be tricky to check for consistency in the community and so hopefully this code should be useful in that regard.
CosmoWAP is a Python package to analyse the power spectra and bispectra but the analytical expressions themselves are computed analytically in Mathematica using routines which are publicly available at MathWAP and then exported as .py files. Therefore the main functionality of CosmoWAP is to take these expressions and implement them for a given cosmology (from CLASS) and set of survey parameters.
Documentation
Full documentation is available at ReadtheDocs.
[!NOTE] Note this is still in progress as this is an evolving repo! Occasionally parts will be outdated and will contain deprecated methods.
Installation
[!NOTE] Requires at least Python >=3.10 for full functionality. For use of CosmoPower emulators we recommend using Python 3.10 or 3.11 - See Docs for full details.
pip install cosmowap
For Development mode...
Clone repository:
git clone https://github.com/craddis1/CosmoWAP.git
and then make editable install:
cd cosmowap
pip install -e .
See requirements.txt for full list of dependencies (most are common python libraries). classy (CLASS python wrapper) is necessary to fully use CosmoWAP.
Features
CosmoWAPs aim is to provide self-consistent modelling for the linear bispectrum and power spectrum. It contains redshift space expressions for the 3D Fourier (multipoles and full LOS dependent expressions) power spectrum (with multi-tracer capabilities) as well as the bispectrum (with Sccoccimarro spherical harmonic multipoles), including terms from:
- Wide separation (WS) effects (i.e. wide angle and radial redshift contributions) up to second order in the WS expansion
- Local Relativistic (GR) effects (including projection and dynamical effects) up to $\left(\frac{\mathcal{H}}{k}\right)^2$
- Integrated Effects, (e.g. lensing + ISW...) (power spectrum only currently)
- Primordial non-Gaussian (PNG) contribution for local, equilateral and orthogonal types
It also has a fully integrated forecasting and plotting library that allows these expressions to be explored.
additional features
- Bias modelling through Luminosity functions and HOD/HMF
- Multi-tracer multipole covariances (assuming gaussianity)
- Finger-of-God damping and non-linear corrections
- TriPOSH bispectrum expansion terms (Coming soon)
Usage
Base code based on work in arXiv:2407.00168
For Integrated effects see: arXiv:2511.09466
For PNG and Forecasting routines related please also refer to: arXiv:25xx.xxxx
Contact
If you find any bugs or errors or have any questions and suggestions feel free to get in touch :) - c.l.j.addis@qmul.ac.uk
Related Skills
next
A beautifully designed, floating Pomodoro timer that respects your workspace.
product-manager-skills
50PM skill for Claude Code, Codex, Cursor, and Windsurf: diagnose SaaS metrics, critique PRDs, plan roadmaps, run discovery, and coach PM career transitions.
devplan-mcp-server
3MCP server for generating development plans, project roadmaps, and task breakdowns for Claude Code. Turn project ideas into paint-by-numbers implementation plans.
