# Reconstructing the cosmic web

florpi

https://florpi.github.io/

IAIFI Fellow

Carol Cuesta-Lazaro

Victoria Ono, Core Francisco Park, Nayantara Mudur and Yueying Ni

p_\phi(\rho_\mathrm{DM}|\rho_\mathrm{Galaxies})

1 to Many:

Galaxy distribution

Underlying Dark matter distribution ?

 "Probabilistic Reconstruction of Dark Matter fields from galaxies using diffusion models"
arXiv:2311.08558
Core Francisco Park,  Victoria Ono, Nayantara Mudur, Yueying Ni, Carolina Cuesta-Lazaro 

A 2D animation of a folk music band composed of anthropomorphic autumn leaves, each playing traditional bluegrass instruments, amidst a rustic forest setting dappled with the soft light of a harvest moon

Maximize the likelihood of the training samples

\hat \theta = \argmax \left[ \log p_\theta (x_\mathrm{train}) \right]
x_1
x_2

Model

p_\theta(x)

Training Samples

x_\mathrm{train}

## Generative Models 101

x_1
x_2

Trained Model

p_\theta(x)

Generate Novel Samples

Evaluate probabilities

Anomaly detection, model comparison...

Reverse diffusion: Denoise previous step

Forward diffusion: Add Gaussian noise (fixed)

A person half Yoda half Gandalf

q_\theta(z_0|z_1)
p(z_1|z_0)
p(z_0)
p(z_T)
p(z_2)
p(z_1)
p(z_2|z_1)
p(z_T|z_2)
q_\theta(z_1|z_2)
q_\theta(z_2|z_T)

## Diffusion Models

Truth

Sampled

Observed

25 \, h^{-1}\mathrm{Mpc}

~10-100 pc

Molecular clouds

where stars form

### A matrioska of scales

~10-50 kpc

Galaxies

where clouds form

TNG50 ~50 Mpc

Cosmic web

(where galaxies form)

MXXL ~ 4 Gpc

### Stay tuned: Huybrid ML simulators for the ISM

High Res Sim

Springel and Hernquist 03

By carol cuesta

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