Related papers: Generative Artificial Intelligence for Air Shower …
We present the 3DGAN for the simulation of a future high granularity calorimeter output as three-dimensional images. We prove the efficacy of Generative Adversarial Networks (GANs) for generating scientific data while retaining a high level…
A method is proposed and evaluated to model large and inconvenient phase space files used in Monte Carlo simulations by a compact Generative Adversarial Network (GAN). The GAN is trained based on a phase space dataset to create a neural…
VERITAS (Very Energetic Radiation Imaging Telescope Array System) is the current-generation array comprising four 12-meter optical ground-based Imaging Atmospheric Cherenkov Telescopes (IACTs). Its primary goal is to indirectly observe…
For the analysis of data taken by Imaging Air Cherenkov Telescopes (IACTs), a large number of air shower simulations are needed to derive the instrument response. The simulations are very complex, involving computational and…
Dark matter in the universe evolves through gravity to form a complex network of halos, filaments, sheets and voids, that is known as the cosmic web. Computational models of the underlying physical processes, such as classical N-body…
In particle physics, the demand for rapid and precise simulations is rising. The shift from traditional methods to machine learning-based approaches has led to significant advancements in simulating complex detector responses. CaloShowerGAN…
High-precision modeling of subatomic particle interactions is critical for many fields within the physical sciences, such as nuclear physics and high energy particle physics. Most simulation pipelines in the sciences are computationally…
Physicists at the Large Hadron Collider (LHC) rely on detailed simulations of particle collisions to build expectations of what experimental data may look like under different theory modeling assumptions. Petabytes of simulated data are…
The precise modeling of subatomic particle interactions and propagation through matter is paramount for the advancement of nuclear and particle physics searches and precision measurements. The most computationally expensive step in the…
Simulations of particle showers in calorimeters are computationally time-consuming, as they have to reproduce both energy depositions and their considerable fluctuations. A new approach to ultra-fast simulations are generative models where…
Cosmic ray shower detection using large radio arrays has gained significant traction in recent years. With massive improvements in signal modelling and microscopic simulations, the analysis of incoming events is still severely limited by…
The prospect of quantum computing with a potential exponential speed-up compared to classical computing identifies it as a promising method in the search for alternative future High Energy Physics (HEP) simulation approaches. HEP…
Recently a type of neural networks called Generative Adversarial Networks (GANs) has been proposed as a solution for fast generation of simulation-like datasets, in an attempt to bypass heavy computations and expensive cosmological…
Despite various breakthroughs in machine learning and data analysis techniques for improving smart operation and management of urban water infrastructures, some key limitations obstruct this progress. Among these shortcomings, the absence…
A new approach to simulate fluorescence photons produced in extensive air showers is described. A Monte Carlo program based on CORSIKA produces the fluorescence photons for each charged particle in the development of the shower. This method…
Simulations of geosynchrotron radio emission from extensive air showers performed with the Monte Carlo code REAS1 used analytical parameterisations to describe the spatial, temporal, energy and angular particle distributions in air showers.…
A simple method for the parallelization of extensive air shower simulations is described. A shower is simulated at fixed steps in altitude. At each step, daughter particles below a specified energy threshold are siphoned off and tabulated…
Simulations of radio emission from extensive air showers we have published so far were performed with a Monte Carlo code using analytical parametrisations to describe the spatial, temporal, energy and angular particle distributions in the…
When researchers develop new econometric methods it is common practice to compare the performance of the new methods to those of existing methods in Monte Carlo studies. The credibility of such Monte Carlo studies is often limited because…
The reliable simulation of extensive air showers induced by different primary particles (e. g. proton, iron, gamma etc.) is of great importance in high energy cosmic ray research. The CORSIKA is a standard Monte-Carlo simulation package to…