CPLUOS Astrophysics team meeting

Asia/Seoul
물리학과

물리학과

Zoom Meeting https://uos-ac-kr.zoom.us/j/8264902652 Meeting ID: 826 490 2652
Description

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

    • 14:00 14:50
      COSMOLOGY
      • 14:00
        Hyeonmo's Report_Planar System Generation 10m
        Speaker: Hyeonmo Koo (University of Seoul)

        Planar System Generation

        • Refer to "Analyzing Planar Galactic Halo Distributions with Fuzzy/Cold Dark Matter Models.
        • Each Planar System has a quantity of the following.
          • Number of Halo(Hernquist Profile Seed): 100
          • Each mass of Halo(Seed): 𝜋×108𝑀⊙
          • Profile of System: Plummer Profile 𝜌𝑟 = (3𝑀0/4𝜋𝑎3)(1+r2/a2)(-5/2)
          • Half-Light Radius of System: 𝑎 = 13.6 kpc
          • Radius Cut of System: 𝑅max  = 40.8 kpc
          • 𝑣ini  = 𝑞1𝑣P+𝑞2𝑣±
            • q1  = randomness
          • Comparison of CDM and FDM plots
        • Next work
          • Find ellipticity and planarity of satellites.
          • Colliding two planar system.
      • 14:10
        Young's report. FoF and MST algorithm 10m
        Speaker: Young Ju

        FoF and MST algorithm

        • We submitted the paper to MNRAS.
        • Also, we can see the paper on arxiv: arXiv:2301.03278
        • Our plans are the followng.
          • Improve MGS code.
          • Find more topological variables.
          • Parameter constraint  using MGS
        • 1. Increase speed of calculation.
          • We use MPI and increase speed of density calculation.
          • Normal way: ~110 seconds
          • MPI using 6 processes (laptop): ~25 seconds
        • 2. For test, We made topological variables with size of cluster.
      • 14:20
        Hannah's Report 10m
        Speaker: Hannah Jhee (University of Seoul)

        Halos infalling a cluster through filaments

        • No progress
      • 14:30
        Seyeon's Report - CLML 10m
        Speaker: Se Yeon Hwang (Universe of Seoul)

        Cosmology with Large scale structure using Machine Learning (CLML)

        • Preview
          • CNN result
        • These are the plots from CNN and ViT.
          • From CNN
          • From ViT
        • They predicted gravitational lensing parameter.
          • Blue: CNN (ResNet)
          • Orange: ViT
        • What we are doing now: We are trying to use pre-trained 3-D ViT so that can make any differences with previous result.
      • 14:40
        Dr.Sabiu's Report 10m
        Speaker: Dr Cristiano Sabiu (University of Seoul)

        Deep Learning the Deep Sky: Recovering low surface brightness objects with machine learning

        • No progress
    • 14:50 15:00
      Discussion 10m