Carol Cuesta-Lazaro
IAIFI Fellow
Initial Conditions of the Universe
Laws of gravity
3-D distribution of galaxies
Which are the ICs of OUR Universe?
Primordial non-Gaussianity?
Probe Inflation
Galaxy formation
3-D distribution of dark matter
Is GR modified on large scales?
How do galaxies form?
Neutrino mass hierarchy?
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
Emulate complex processes in high dimensions
arXiv:2206.04594
Super resolution
arxiv:2010.06608
Compare data and simulations optimally
Simulation-based Inference
arXiv:1911.01429
Detect anomalies
arxiv:2010.14554
Model uncertainties
arxiv:2010.14554
Current Universe
Initial Conditions
Represent complex priors
arxiv:2206.14820
how does a galaxy look like?
lensing
Data
A parametric PDF
Maximise the likelihood
(or something similar)
2. Sample
1. Estimate densities
Explicit Density
Implicit Density
Tractable Density
Approximate Density
Normalising flows
Variational Autoencoders
Diffusion models
Generative Adversarial Networks
The zoo of generative models
Reverse diffusion: Denoise previous step
Forward diffusion: Add Gaussian noise (fixed)
A person half Yoda half Gandalf
Diffusion on point clouds
Reverse diffusion: Denoise previous step
Forward diffusion: Add Gaussian noise (fixed)
Cosmology
"Diffusion generative modeling for galaxy surveys: emulating clustering for inference at the field level" Carolina Cuesta-Lazaro, Siddarth Mishra-Sharma
Setting tight constraints with only 5000 halo positions
Halo Mass Function
Velocity
Mean pairwise velocity
"Probabilistic Reconstruction of Dark Matter fields from galaxies using diffusion models" Victoria Ono, Core Francisco Park, Nayantara Mudur, Yueying Ni, Carolina Cuesta-Lazaro (in prep)
"Probabilistic Reconstruction of Dark Matter fields from galaxies using diffusion models" Victoria Ono, Core Francisco Park, Nayantara Mudur, Yueying Ni, Carolina Cuesta-Lazaro (in prep)
Node features coordinates (+mass, velocities)
Input
Noisy halo properties
Output
Noise prediction
Graph Neural Networks as score models
kNN (~20)