Skip to content

mrummphys/axion_statistics

Repository files navigation

Axion Statistics

Fourier and machine learning tools for constraining axion-like-particles in astrophysical observations as described in https://arxiv.org/abs/1808.05916 .

Requirements

Python 2.7, PyXspec 2

for Fourier Analysis: https://github.com/NFFT/nfft

for Machine Learning: tensorflow 1.5

Usage

  1. Use mathematica notebook PhotonAxionConversionCluster.nb to generate output: survivalProbs_*Bfield.txt

  2. Delete all survivalProbs_*Bfield.mod files

  3. Use python ALPmod.py to generate survivalProbs_*Bfield.mod table models as input for PyXspec.

  4. Run python PyXspec.py to perform PyXspec scan over all *.mod files. Output: g_chisq.txt

  5. Run python Analyze.py to analyze g_chsiq.txt. Outputs: histo_*.pdf and g_deltachi2.pdf

  6. Residuals can also be fed to the machine learning algorithm described in tf.py.

About

Fourier and machine learning tools for constraining axion-like-particles in astrophysical observations

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published