20 citations · 21 across the 5 of their papers we have counts for
5 papers
Exploring the Boundaries of Differentiable Radiation Transport and Detector Simulation
Jeffrey Krupa, Yiyang Zhao, Mihaly Novak +9
We present an application of automatic differentiation for particle transport through matter using a Geant4-like radiation transport simulation with a full electromagnetic physics…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
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…
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…
Potential of the Julia programming language for high energy physics computing
J. Eschle, T. Gal, M. Giordano +15
Research in high energy physics (HEP) requires huge amounts of computing and storage, putting strong constraints on the code speed and resource usage. To meet these requirements, a…