CPLUOS Astrophysics team meeting

Friday 10 Feb 2023, 14:00 → 15:20 Asia/Seoul

물리학과

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

14:00 → 14:40 COSMOLOGY¶

14:00 Hyeonmo's Report¶

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¶

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¶

Speaker: Se Yeon Hwang (Universe of Seoul)

Cosmology with Large scale structure using Machine Learning (CLML)

• Used CNN: Ω_m, σ₈, w₀, n_s, 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 (Ω_m, σ₈, w₀, n_s, h), Lazanu, 2021, JCAP
  • (Right) using lightcone data z = 0.3 ~ 0.8
    • Plot with error
    • CNN: 5 graph (Ω_m, σ₈, w₀, n_s, h)
    • Plot scatter
    • CNN: 5 graph (Ω_m, σ₈, w₀, n_s, 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¶

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¶