6 research outputs found
Soft and diffractive scattering with the cluster model in Herwig
We present a new model for soft interactions in the event-generator Herwig. The model consists of two components. One to model diffractive final states on the basis of the cluster hadronization model and a second component that addresses soft multiple interactions as multiple particle production in multiperipheral kinematics. We present much improved results for minimum-bias measurements at various LHC energies
Soft and diffractive scattering with the cluster model in Herwig
We present a new model for soft interactions in the event-generator Herwig. The model consists of two components. One to model diffractive final states on the basis of the cluster hadronization model and a second component that addresses soft multiple interactions as multiple particle production in multiperipheral kinematics. We present much improved results for minimum-bias measurements at various LHC energies
Event Generators for High-Energy Physics Experiments
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments
Event Generators for High-Energy Physics Experiments
We provide an overview of the status of Monte-Carlo event generators for
high-energy particle physics. Guided by the experimental needs and
requirements, we highlight areas of active development, and opportunities for
future improvements. Particular emphasis is given to physics models and
algorithms that are employed across a variety of experiments. These common
themes in event generator development lead to a more comprehensive
understanding of physics at the highest energies and intensities, and allow
models to be tested against a wealth of data that have been accumulated over
the past decades. A cohesive approach to event generator development will allow
these models to be further improved and systematic uncertainties to be reduced,
directly contributing to future experimental success. Event generators are part
of a much larger ecosystem of computational tools. They typically involve a
number of unknown model parameters that must be tuned to experimental data,
while maintaining the integrity of the underlying physics models. Making both
these data, and the analyses with which they have been obtained accessible to
future users is an essential aspect of open science and data preservation. It
ensures the consistency of physics models across a variety of experiments.Comment: 153 pages, 10 figures, contribution to Snowmass 202
Event generators for high-energy physics experiments
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular emphasis is given to physics models and algorithms that are employed across a variety of experiments. These common themes in event generator development lead to a more comprehensive understanding of physics at the highest energies and intensities, and allow models to be tested against a wealth of data that have been accumulated over the past decades. A cohesive approach to event generator development will allow these models to be further improved and systematic uncertainties to be reduced, directly contributing to future experimental success. Event generators are part of a much larger ecosystem of computational tools. They typically involve a number of unknown model parameters that must be tuned to experimental data, while maintaining the integrity of the underlying physics models. Making both these data, and the analyses with which they have been obtained accessible to future users is an essential aspect of open science and data preservation. It ensures the consistency of physics models across a variety of experiments.peerReviewe