Weak Lensing with the Lyman Forest Prakruth Adari

  • Slides: 16
Download presentation
Weak Lensing with the Lyman-α Forest Prakruth Adari Anže Slosar 1

Weak Lensing with the Lyman-α Forest Prakruth Adari Anže Slosar 1

What? ● Remapping quasars and then using the displacement map we can get, to

What? ● Remapping quasars and then using the displacement map we can get, to create a kappa map 2

Method We can create a displacement field and use that to get the kappa

Method We can create a displacement field and use that to get the kappa map Observed distance should be true distance + noise Can get likelihood for true positions 3

Least Squares For each pair, we have a solution so least squares fit for

Least Squares For each pair, we have a solution so least squares fit for each quasar against its nearest neighbors Use first degree taylor expansion of great circle distance Set overdetermined system of linear equations for each i and find best fit A= = 4

Least Squares Fit 250, 000 points uniformly over a sphere with the 100 nearest

Least Squares Fit 250, 000 points uniformly over a sphere with the 100 nearest neighbors 5

250 k points 6

250 k points 6

7

7

8

8

9

9

Samantha Prakruth 10

Samantha Prakruth 10

Limitations ● Computationally intensive due to iterations (149, 000 points is 3360 seconds per

Limitations ● Computationally intensive due to iterations (149, 000 points is 3360 seconds per iteration on a single core) ● Doesn’t do well with edges/holes which can stem from not enough data ○ ○ Can find the unlensed positions but going from displacement field to kappa map is not good Correlation is resolution dependent 24 k points 11

Conclusions ● Able to get unlensed points in a non-ridiculous amount of time ○

Conclusions ● Able to get unlensed points in a non-ridiculous amount of time ○ ○ Able to get an accurate displacement map Non-ridiculous because of cluster access so it’s only kind of ridiculous ● Not able to get an accurate kappa map ○ Too many “holes” in the data lead to it being really spotchy 12

Kappa Estimator (Samantha) 13

Kappa Estimator (Samantha) 13

14

14

15

15

Thanks! Questions? 16

Thanks! Questions? 16