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 14:40
      COSMOLOGY
      • 14:00
        Hyeonmo's Report 10m
        Speaker: Hyeonmo Koo (University of Seoul)

        Planar System Generation

        • MATLAB-PyUltraLight: Collision comparison
          • Initial condition is same.
        • r[kpc]-ρ[M0/kpc3] graph
        • Goal
          • 1. Finding offset.
          • 2. Applying gas particles.
      • 14:10
        Young's report. FoF and MST algorithm 10m
        Speaker: Young Ju

        FoF and MST algorithm

        • MGS comments
          • This is a mass function using a simulation data.
          • Based on dark matter particle.
          • Blue line: Dark matter mass function (Press & Schechter)
          • Min sample-Number of clusters graph
            • We use 3.
      • 14:20
        Seyeon's Report - CLML 10m
        Speaker: Se Yeon Hwang (Universe of Seoul)

        Cosmology with Large scale structure using Machine Learning (CLML)

        • Used CNN: Ωm, σ8, w0, ns, h
        • We made linear correlation.
        • Also we are considering weighted loss function to reduce this bias.
          • Red line: Truth-to-truth line
          • Blue: Average value
          • Before correction
            • x axis: Truth
            • y axis: Prediction
          • After correction
            • x axis: Truth
            • y axis: Prediction
        • Comparing with other result
          • (Left) using snapshot data at z = 0: 5 graph (Ωm, σ8, w0, ns, h), Lazanu, 2021, JCAP
          • (Right) using lightcone data z = 0.3 ~ 0.8
            • Plot with error
            • CNN: 5 graph (Ωm, σ8, w0, ns, h)
            • Plot scatter
            • CNN: 5 graph (Ωm, σ8, w0, ns, h)
        • CNN & ViT
        • 2pcf & Dense neural network
        • Next step
          • We are going to apply the observation data on our trained model.
      • 14:30
        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
    • 14:40 14:50
      Discussion 10m