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
Hydro sims:
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
Reconstructing cosmic web
By carol cuesta
