Zobrazeno 1 - 10
of 1 922
pro vyhledávání: '"Krücker, Dirk"'
The simulation of calorimeter showers presents a significant computational challenge, impacting the efficiency and accuracy of particle physics experiments. While generative ML models have been effective in enhancing and accelerating the conventional
Externí odkaz:
http://arxiv.org/abs/2403.15782
In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, the generation of large point clouds in a short time is required, while the comple
Externí odkaz:
http://arxiv.org/abs/2312.00042
In High Energy Physics, detailed and time-consuming simulations are used for particle interactions with detectors. To bypass these simulations with a generative model, the generation of large point clouds in a short time is required, while the comple
Externí odkaz:
http://arxiv.org/abs/2311.12616
Autor:
Rehm, Florian, Vallecorsa, Sofia, Borras, Kerstin, Krücker, Dirk, Grossi, Michele, Varo, Valle
Publikováno v:
IOP Quantum Science and Technology (October 2023)
The Quantum Angle Generator (QAG) is a new full Quantum Machine Learning model designed to generate accurate images on current Noise Intermediate Scale (NISQ) Quantum devices. Variational quantum circuits form the core of the QAG model, and various c
Externí odkaz:
http://arxiv.org/abs/2307.05253
The main challenge of quantum computing on its way to scalability is the erroneous behaviour of current devices. Understanding and predicting their impact on computations is essential to counteract these errors with methods such as quantum error miti
Externí odkaz:
http://arxiv.org/abs/2306.08427
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 simulations, such as
Externí odkaz:
http://arxiv.org/abs/2305.07284
Autor:
Scham, Moritz A.W.1,2,3 moritz.scham@desy.de, Krücker, Dirk1, Käch, Benno1,4, Borras, Kerstin1,3
Publikováno v:
EPJ Web of Conferences. 5/6/2024, Vol. 295, p1-7. 7p.
Autor:
Käch, Benno, Krücker, Dirk, Melzer-Pellmann, Isabell, Scham, Moritz, Schnake, Simon, Verney-Provatas, Alexi
Fast data generation based on Machine Learning has become a major research topic in particle physics. This is mainly because the Monte Carlo simulation approach is computationally challenging for future colliders, which will have a significantly high
Externí odkaz:
http://arxiv.org/abs/2211.13630
Data generation based on Machine Learning has become a major research topic in particle physics. This is due to the current Monte Carlo simulation approach being computationally challenging for future colliders, which will have a significantly higher
Externí odkaz:
http://arxiv.org/abs/2211.13623
Autor:
Humble, Travis S., Delgado, Andrea, Pooser, Raphael, Seck, Christopher, Bennink, Ryan, Leyton-Ortega, Vicente, Wang, C. -C. Joseph, Dumitrescu, Eugene, Morris, Titus, Hamilton, Kathleen, Lyakh, Dmitry, Date, Prasanna, Wang, Yan, Peters, Nicholas A., Evans, Katherine J., Demarteau, Marcel, McCaskey, Alex, Nguyen, Thien, Clark, Susan, Reville, Melissa, Di Meglio, Alberto, Grossi, Michele, Vallecorsa, Sofia, Borras, Kerstin, Jansen, Karl, Krücker, Dirk
Quantum computing offers a new paradigm for advancing high-energy physics research by enabling novel methods for representing and reasoning about fundamental quantum mechanical phenomena. Realizing these ideals will require the development of novel c
Externí odkaz:
http://arxiv.org/abs/2203.07091