Researchers Improve Hadronic Collision Modeling with Event Generators for High-energy Physics Analyses

Event generators are fundamental tools in both high-energy and astroparticle physics, underpinning analyses ranging from simple observations to complex deep learning applications, yet accurately modelling hadronic interactions remains a significant challenge. Johannes Albrecht, Julia Becker Tjus, Noah Behling, and colleagues present a new approach to refine these models, recognising a critical disconnect between accelerator-based experiments and astroparticle observations. Current event generators, typically tuned using data from particle colliders, often fail to adequately describe astroparticle data, which probes higher energy ranges and different production angles of resulting particles. This work establishes a roadmap for unifying these two datasets, enabling a more comprehensive and accurate tuning of event generators and ultimately improving our understanding of fundamental particle interactions across a broader range of energies and conditions.

High Energy Particle Interactions and Cross Sections

Researchers are meticulously cataloging data from numerous experiments investigating high-energy particle interactions, crucial for understanding both fundamental physics and the origins of cosmic rays. These studies focus on measuring the probability of particle interactions, known as cross-sections, and identifying the particles created in these collisions, including pions, kaons, and protons. Experiments span a broad energy range, allowing scientists to probe particle behavior at increasingly high energies. This comprehensive collection of data forms the foundation for developing and refining theoretical models of particle interactions, essential for interpreting experimental results and predicting new phenomena. The research highlights the importance of experiments conducted at facilities like CERN, which provide high-intensity particle beams for detailed studies of these interactions.

Hadronic Interactions and Event Generator Improvement

Event generators, vital for simulating particle interactions in both high-energy physics and astroparticle physics, require continuous refinement to accurately model observed phenomena. These programs predict the characteristics of particle collisions, informing experimental design, data analysis, and the search for rare processes. A significant challenge lies in modeling hadronic interactions at low momentum transfer, a regime where standard theoretical approaches struggle and reliance on empirical models introduces uncertainty. Currently, event generator development primarily utilizes data from accelerator-based experiments, but these often fail to accurately describe data from astroparticle experiments.

To address this, scientists are pioneering a novel approach, integrating data from both accelerator and astroparticle experiments into a unified tuning process for event generators. This combined approach leverages the strengths of each data source, improving the accuracy of simulations across a wider range of energies and collision scenarios. Researchers carefully compare simulated events with observations from diverse experiments, including those detecting cosmic rays, neutrinos, and gamma-rays, analyzing the development of particle cascades to validate the accuracy of the models.

Unifying Collider and Astroparticle Event Simulations

Researchers have achieved a significant advancement in modeling high-energy and astroparticle physics events by unifying data from accelerator experiments and astroparticle observations. Previously, discrepancies between these two data sets hindered accurate simulations. The team discovered that existing event generators often fail to accurately describe astroparticle data, particularly regarding hadrons produced at high energies and specific angles. This work establishes a roadmap for simultaneously tuning event generators using both accelerator-based and astroparticle data, enabling a more comprehensive and accurate representation of hadronic interactions.

The study presents a detailed comparison of five leading event generators, highlighting their theoretical foundations and tuning capabilities. Results demonstrate that each generator employs distinct approaches to modeling particle production, ranging from parton-based models to Gribov Regge theory. Effective tuning is critical for accurate simulations, and researchers emphasize that incorporating data from both accelerator experiments and astroparticle observations significantly improves the accuracy of event generators, paving the way for more reliable simulations of high-energy phenomena.

Unified Tuning Bridges Particle and Astroparticle Data

This work demonstrates the potential for a unified tuning of event generators by combining data from high-energy physics experiments at accelerators and astroparticle experiments. Currently, event generators are primarily tuned using accelerator data, but often fail to accurately describe data from astroparticle experiments, which probe higher energy ranges and different collision characteristics. The authors highlight that incorporating data from both sources could significantly improve the accuracy and reliability of these models across a broader spectrum of energies and collision types. The research identifies technical challenges in achieving this unified tuning, particularly the need for improved software tools capable of handling data from diverse experiments.

While extending existing software presents one path forward, developing a new translator specifically designed for this purpose offers advantages in flexibility and development speed. The authors acknowledge a potential circular dependency when simultaneously tuning event generators and cosmic ray composition models, but propose solutions to mitigate this issue. Future work will focus on addressing these technical hurdles and refining the tuning process to fully exploit the complementary nature of accelerator and astroparticle data.