Welcome to Weak Lensing Tutorial’s Documentation!
- Day 1 - Introduction
- Day 1 Solutions
- Day 2 - Finding neighbours
- Reading the lens/source catalog
- Visualising the coordinate space of input data
On-sky distancebetween two points on the surface of a unit sphere- Brute force search for neighbour objects within a specified distance
- Using k-d tree algorithm to query the neighbour points within a given distance
- Compare the computer time required by our brute force algorithm vs the k-d tree algorithm
- Congratulations! Now you have learnt to -
- Day 2 Solutions
- Reading the lens/source catalog
- Visualising the coordinate space of input data
On-sky distancebetween two points on the surface of a unit sphere- Brute force search for neighbour objects within a specified distance
- Using k-d tree algorithm to query the neighbour points within a given distance
- Compare the computer time required by our brute force algorithm vs the k-d tree algorithm
- Congratulations! Now you have learnt to -
- Day 3 - Get the Weak Lensing Signals
- Required Steps
- Reading data from the catalog and appying the selection cuts.
- Computing the tangential shear \(e_{\rm t}\) and inverse critical density \(\Sigma^{-1}_{\rm crit}\)
- \(\Delta \Sigma\) measurements using cKDTree and writing the output to a file.
- Plotting the weak lensing signal
- The bias corrected measurements
- Day 3 Solutions
- Day 4 - Model the weak lensing signal
- Day 4 Solutions