deck

Learning The Universe (LtU)

TNG50

Image credit: Sarah Jeffreson

Image credit: Lehman Garrison, AbacusSummit

\frac{\mathrm{d} \mathbf{x}}{\mathrm{d} a } = \frac{1}{a^3 E(a)}\mathbf{v}

\frac{\mathrm{d} \mathbf{x}}{\mathrm{d} a } = \frac{1}{a^3 E(a)}\mathbf{v}

\frac{\mathrm{d} \mathbf{v}}{\mathrm{d} a } = \frac{1}{a^2 E(a)}\mathbf{F}(\mathbf{x},a)

\frac{\mathrm{d} \mathbf{v}}{\mathrm{d} a } = \frac{1}{a^2 E(a)}\mathbf{F}(\mathbf{x},a)

Physics Simulator

x_{\rm Initial}

x_{\rm Initial}

x_{\rm Final}

x_{\rm Final}

Neural Network

x_{\rm Initial}

x_{\rm Initial}

x_{\rm Final}

x_{\rm Final}

Hybrid Model

\frac{\mathrm{d} \mathbf{x}}{\mathrm{d} a } = \frac{1}{a^3 E(a)}\mathbf{v}

\frac{\mathrm{d} \mathbf{x}}{\mathrm{d} a } = \frac{1}{a^3 E(a)}\mathbf{v}

\frac{\mathrm{d} \mathbf{v}}{\mathrm{d} a } = \frac{1}{a^2 E(a)}\mathbf{F}(\mathbf{x},a) +

\frac{\mathrm{d} \mathbf{v}}{\mathrm{d} a } = \frac{1}{a^2 E(a)}\mathbf{F}(\mathbf{x},a) +

x_{\rm Initial}

x_{\rm Initial}

x_{\rm Final}

x_{\rm Final}

Nbody

Slow

Non-differentiable

Particle mesh

Accurate

Fast

Differentiable

Missing small scales

Nbodyify

Fast

Differentiable

Accurate

"Nbodyify: adaptive mesh corrections for PM simulations" Carolina Cuesta-Lazaro, Chirag Modi (in prep)

\frac{\mathrm{d} \mathbf{x}}{\mathrm{d} a } = \frac{1}{a^3 E(a)}\mathbf{v}

\frac{\mathrm{d} \mathbf{x}}{\mathrm{d} a } = \frac{1}{a^3 E(a)}\mathbf{v}

\frac{\mathrm{d} \mathbf{v}}{\mathrm{d} a } = \frac{1}{a^2 E(a)}\mathbf{F}(\mathbf{x},a)

\frac{\mathrm{d} \mathbf{v}}{\mathrm{d} a } = \frac{1}{a^2 E(a)}\mathbf{F}(\mathbf{x},a)

\mathbf{F}_\theta(\mathbf{x},a) = \frac{3 \Omega_m}{2} \nabla \left[\phi^\mathrm{PM}(\mathbf{x}) + \phi^\mathrm{corr}_\theta(\mathbf{x}, a, \phi^\mathrm{PM}, \delta^\mathrm{PM}) \right]

\mathbf{F}_\theta(\mathbf{x},a) = \frac{3 \Omega_m}{2} \nabla \left[\phi^\mathrm{PM}(\mathbf{x}) + \phi^\mathrm{corr}_\theta(\mathbf{x}, a, \phi^\mathrm{PM}, \delta^\mathrm{PM}) \right]

\mathbf{F}(\mathbf{x},a) = \frac{3 \Omega_m}{2} \nabla \phi^\mathrm{PM}(\mathbf{x})

\mathbf{F}(\mathbf{x},a) = \frac{3 \Omega_m}{2} \nabla \phi^\mathrm{PM}(\mathbf{x})

Gravitational evolution ODE

Particle-mesh

Hybrid Simulator

\mathcal{L} = \sum_t \left(x_t^{\rm pred} - x_t^{\rm HR}\right)^2

\mathcal{L} = \sum_t \left(x_t^{\rm pred} - x_t^{\rm HR}\right)^2

\delta_\mathrm{LR}

\delta_\mathrm{LR}

\phi_\mathrm{LR}

\phi_\mathrm{LR}

Density

Gravitational Potential

1. CNN

2. Read features at position using attention

h_\theta(\mathbf{x})

h_\theta(\mathbf{x})

\mathbf{F}_\theta(\mathbf{x},a) = f_\theta(h_\theta(\mathbf{x}), a)

\mathbf{F}_\theta(\mathbf{x},a) = f_\theta(h_\theta(\mathbf{x}), a)

3. Compute correction to force

4. Run corrected simulation

d_{\rm pm}

d_{\rm pm}

W_{\rm m} = f_\theta(d_{\rm pm}, h_{\rm m})

W_{\rm m} = f_\theta(d_{\rm pm}, h_{\rm m})

h(x) = \sum_m w_{\rm m} h_{\rm m}

h(x) = \sum_m w_{\rm m} h_{\rm m}

Power Spectrum

Cross correlation

Power Spectrum

Cross correlation

Improving small scales?

p(x_{\rm LR}|x_{\rm HR})

p(x_{\rm LR}|x_{\rm HR})

Do we need particle-particle interactions?

Turn probabilistic!

Hybrid simulators for cosmology