CPLUOS Astrophysics team meeting

Monday 10 Jan 2022, 16:30 → 18:10 Asia/Seoul

물리학과

https://uos-ac-kr.zoom.us/j/8264902652

COSMOLOGY

1 Dr.Sangnam Park's Report - FDM_Offset

Speaker: Sangnam Park

2 Hyeonmo's report - FDM vs CDM Halo Collision

Speaker: Hyeonmo Koo (University of Seoul)

FDM vs CDM Halo Collision

• Data and and λ-Fitting are almost identical, and are graphed in inverse proportion to the Velocity Before Collision - Velocity Decrease
  • As a result of comparing the result with the graph in FDM, FDM data has a higher value than CDM data.
• Head-on Collision of Fuzzy/Cold Dark Matter Halos
  • We numerically study the movement of two colliding fuzzy dark matter solitons without explicit self-interaction and find the effective cross section of dissipative change in velocity. The cross section turns out to be inversely proportional to the velocity cubed, and we present its analytic interpretation. Using the result we roughly estimate spatial offsets during head-on collisions of two fuzzy dark matter halos, which can be related to the spatial offsets between stars and dark matter in collisions of some galaxy clusters. We also show that the gravitational cooling plays an important role during the collisions. (ABSTRACT)

3 Young's report. FoF and MST algorithm

Speaker: Young Ju

FoF and MST algorithm

• Controlled random data 2 : Halo mass function + NFW profile
  • Get NFW profile : radius range = 1 ~ 10^4 (kpc)
  • 1. Generate random halo distribution
  • 2. Get the number of galaxies in the halo using halo mass function
  • 3. Get the NFW profile for each halo
  • 4. For each halo, get radius using NFW cumulative prob.
  • 5. Using uniform random distribution, calculate sphere point
  • 6. Repeat 4~5 process for each galaxies
  • 50 halo ; total number of galaxies = 4512
  • Increase number of halo : 50 → 500 ; total number of galaxies : 50257
  • Member > 50, Linking-Length = 4.0, For FoF : mean-separation x 0.74, (MST, FoF, MGS, DBSCAN, Hierarchical)
    • (455, 397, 475, 483, 453)

4 CHOA(Cosmology of High-Order Statistics)

Speaker: Sumi Kim (University of Seoul)

CHOA(Cosmology of High-Order Statistics)

• Until now
  • DDDD/RRRR - 1 → NNNN/RRRR
  • Now we need new calculated mocks result
  • Calculated observation data by new code
  • Fixed it by modifying our code and data
  • We had the estimator problem
• Finding proper bin number
  • To reduce statistical error and noise
  • Mocks Larger Bin test 4pcf for 1 mock
  • Calculated 1 mock from bin 40 to bin 15 to find proper bin size
  • Mocks Larger Bin test 4pcf
  • Mocks Larger Bin test Bin 15 for 1 mock
  • Bin 15 seemed less noisy and seems to have slight signal, so calculated 65 mocks for bin 15.
  • Bin 15 for 65 mocks
  • Need to investigate more to see BAO

5 Hannah's Report - Weak Lensing with Machine Learning

Speaker: Hannah Jhee (University of Seoul)

Weak Lensing with Machine Learning

• Composition : Source galaxies + Lens Cluster + Shear map
• (Reduced) Shear Map
  • Randomly cropping 500x500 (32`x32`) shear map to 386x368 (24.7` x 24.7`)
  • Random flipping to up/down/left/right.
• Convergence Map (Trust Map)
  • Averaging 498x498 convergence map to 166x166 before randomly cropping to 128x128.
  • Random flipping to up/down/left/right.
• GAN(Generative Adversarial Network)

6 Dr.Sabiu's Report - N-PCF

Speaker: Dr Cristiano Sabiu (University of Seoul)

N-PCF

• 4-point correlation function - all bins (configurations)
• Testing the General N-point code
  • Define 4 points in 3D space
  • Making a tetrahedra of side length=2
  • Copy them N times
  • Perturb them with random translations and rotations
• 2-PCF
• 3-PCF
• 4-PCF

7 Discussion