activity
20232026
most citedProgress in End-to-End Optimization of Detectors for Fundamental Physics with Differentiable Programming

4 citations · 18 across the 21 of their papers we have counts for

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6 papers · 1 filter

cs.CE2026

Image Generation Techniques for Urban Planning

Katharina Roth, Eva Hagen, Alexander Bartscher +2

In the context of urban planning, architects are normally instructed with creating presentation images that visualize proposed buildings within their urban context. This work aims…

physics.ins-det2026

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…

physics.ins-det2026★ 1 cited

On the Codesign of Scientific Experiments and Industrial Systems

Tommaso Dorigo, Pietro Vischia, Shahzaib Abbas +84

The optimization of large experiments in fundamental science, such as detectors for subnuclear physics at particle colliders, shares with the optimization of complex systems for in…

cs.CE2026

Parameter conditioned interpretable U-Net surrogate model for data-driven predictions of convection-diffusion-reaction processes

Michael Urs Lars Kastor, Jan Rottmayer, Anna Hundertmark +1

We present a combined numerical and data-driven workflow for efficient prediction of nonlinear, instationary convection-diffusion-reaction dynamics on a two-dimensional phenotypic…

physics.flu-dyn2026

Boundary treatment algorithms for meshfree RANS turbulence modeling

Mohan Padmanabha, Jörg Kuhnert, Nicolas R. Gauger +1

In this paper, we propose improved wall-treatment strategies for meshfree methods applied to turbulent flows. The goal is to enhance wall-function handling in simulations of high-R…

physics.ins-det2026★ 2 cited

Differentiable Surrogate for Detector Simulation and Design with Diffusion Models

Xuan Tung Nguyen, Long Chen, Tommaso Dorigo +7

In this work, we present a conditional denoising-diffusion surrogate for electromagnetic calorimeter showers that is trained to generate high-fidelity energy-deposition maps condit…