4 citations · 18 across the 21 of their papers we have counts for
6 papers · 1 filter
SFFT-Based Homogenization: Using Tensor Trains to Enhance FFT-Based Homogenization
Sascha H. Hauck, Matthias Kabel, Mazen Ali +1
Homogenization is a fundamental technique for estimating the macroscopic properties of materials with microscale heterogeneity. Among Homogenization methods, the FFT-based Homogeni…
Efficient Forward-Mode Algorithmic Derivatives of Geant4
Max Aehle, Xuan Tung Nguyen, Mihály Novák +5
We have applied an operator-overloading forward-mode algorithmic differentiation tool to the Monte-Carlo particle simulation toolkit Geant4. Our differentiated version of Geant4 al…
Exploring End-to-end Differentiable Neural Charged Particle Tracking -- A Loss Landscape Perspective
Tobias Kortus, Ralf Keidel, Nicolas R. Gauger
Measurement and analysis of high energetic particles for scientific, medical or industrial applications is a complex procedure, requiring the design of sophisticated detector and d…
Optimization Using Pathwise Algorithmic Derivatives of Electromagnetic Shower Simulations
Max Aehle, Mihály Novák, Vassil Vassilev +4
Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Co…
Local Adjoints for Simultaneous Preaccumulations with Shared Inputs
Johannes Blühdorn, Nicolas R. Gauger
In shared-memory parallel automatic differentiation, inputs that are shared among simultaneous thread-local preaccumulations lead to data races if Jacobians are accumulated with a…
Hybrid parallel discrete adjoints in SU2
Johannes Blühdorn, Pedro Gomes, Max Aehle +1
The open-source multiphysics suite SU2 features discrete adjoints by means of operator overloading automatic differentiation (AD). While both primal and discrete adjoint solvers su…