A highly granular calorimeter, similar to CALICE is simulated in Geant4. The calorimeters showers are represented as either images or point clouds. Two state-of-the-art score based diffusion models, on image based and the other point cloud based, are trained on the same set of calorimeter simulations and directly compared to each other. These files include the original Geant4 simulation, an intermediate form of the data required for training, and the samples generated by the image and point cloud models
The ATLAS physics program at the LHC relies on very large samples of simulated events. Most of these...
The ATLAS physics program relies on very large samples of simulated events. Most of these samples ar...
Fast calorimeter simulation in LHCb In HEP experiments CPU resources required by MC simulations are...
Score based generative models are a new class of generative models that have been shown to accuratel...
With the huge amount of data collected with ATLAS, there is a need to produce a large number of simu...
The tremendous need for simulated samples now and even more so in the future, encourage the developm...
The ATLAS physics program relies on very large samples of GEANT4 simulated events, which provide a h...
Score-based generative models are a new class of generative algorithms that have been shown to produ...
International audienceThe ATLAS physics program relies on very large samples of Geant4 simulated eve...
International audienceDetectors of High Energy Physics experiments, such as the ATLAS dectector [1] ...
The ATLAS physics program relies on very large samples of GEANT4 simulated events, which provide a h...
Detailed simulation of showers in calorimeters is often the most time-consuming part of computing fo...
Score-based generative models are a new class of generative algorithms that have been shown to produ...
This is dataset 3 of the “Fast Calorimeter Simulation Challenge 2022”. It consists of four files wit...
Diffusion generative models are promising alternatives for fast surrogate models, producing high-fid...
The ATLAS physics program at the LHC relies on very large samples of simulated events. Most of these...
The ATLAS physics program relies on very large samples of simulated events. Most of these samples ar...
Fast calorimeter simulation in LHCb In HEP experiments CPU resources required by MC simulations are...
Score based generative models are a new class of generative models that have been shown to accuratel...
With the huge amount of data collected with ATLAS, there is a need to produce a large number of simu...
The tremendous need for simulated samples now and even more so in the future, encourage the developm...
The ATLAS physics program relies on very large samples of GEANT4 simulated events, which provide a h...
Score-based generative models are a new class of generative algorithms that have been shown to produ...
International audienceThe ATLAS physics program relies on very large samples of Geant4 simulated eve...
International audienceDetectors of High Energy Physics experiments, such as the ATLAS dectector [1] ...
The ATLAS physics program relies on very large samples of GEANT4 simulated events, which provide a h...
Detailed simulation of showers in calorimeters is often the most time-consuming part of computing fo...
Score-based generative models are a new class of generative algorithms that have been shown to produ...
This is dataset 3 of the “Fast Calorimeter Simulation Challenge 2022”. It consists of four files wit...
Diffusion generative models are promising alternatives for fast surrogate models, producing high-fid...
The ATLAS physics program at the LHC relies on very large samples of simulated events. Most of these...
The ATLAS physics program relies on very large samples of simulated events. Most of these samples ar...
Fast calorimeter simulation in LHCb In HEP experiments CPU resources required by MC simulations are...