Differentiable Analysis Blueprint

Session

Beyond LHC

6 Mar 2026, 15:40

4/3-006 - TH Conference Room (CERN)

17. Differentiable Detector Simulation with GEANT [15' + 5']

Jeffrey Krupa (SLAC)

06/03/2026, 15:40

Applying automatic differentiation (AD) to particle simulations such as Geant4 opens the possibility of gradient-based optimization for detector design and parameter tuning in high-energy physics. We extend our previous work on differentiable Geant simulations by incorporating multiple Coulomb scattering into the physics model, moving closer to realistic detector modeling. The inclusion of...

19. End-to-End Differentiable Analysis in IceCube [20' + 10']

Oliver Janik (FAU Erlangen-Nürnberg (DE))

06/03/2026, 16:00

Measurements of the astrophysical neutrino flux with the IceCube Neutrino Observatory traditionally rely on binned forward-folding likelihood analyses. These methods require Monte Carlo simulations to predict event distributions. Limited Monte Carlo statistics restrict the dimensionality of the binning and therefore the amount of exploitable information.
This talk presents a fully...

21. Automatic Differentiation Beyond HEP [20' + 10']

Giacomo Acciarini (European Space Agency (ESA))

06/03/2026, 16:30

Differentiable programming is advancing scientific computing by enabling gradients to flow through complex numerical models. In spaceflight mechanics, a field governed by nonlinear dynamics, uncertainty, and strict operational constraints, this approach opens new avenues for optimization, state estimation, uncertainty quantification, and decision-making.
In this talk, I will present our...