Interactive Web-Based Visualization of Multidimensional Physical and Astronomical Data.

Area of Science:

• Physics
• Data Science
• Scientific Computing

Background:

• Scientific data repositories are crucial for research reproducibility and collaboration.
• Analyzing multiparametric solutions in physical models often requires extensive computational resources and specialized tools.
• Current methods for reanalyzing and comparing phenomenological data can be time-consuming and lack interactivity.

Purpose of the Study:

• To propose the expanded utilization of scientific repositories (e.g., Zenodo, HEP data) for studying multiparametric solutions in physical models.
• To demonstrate the benefits of interactive web-based visualizations for efficient data reanalysis and comparison.
• To showcase practical applications in areas like dark matter, supersymmetry, and LHC simulations.

Main Methods:

• Leveraging existing scientific data repositories for hosting and accessing multiparametric model data.
• Developing and implementing interactive web-based visualization tools for data exploration.
• Applying the proposed framework to specific case studies in particle physics and cosmology.

Main Results:

• Demonstrated feasibility of using repositories for multiparametric physical model data.
• Interactive visualizations significantly enhance the speed and ease of data reanalysis.
• Successful application to dark matter models, supersymmetry exclusions, and LHC simulations, providing valuable insights.

Conclusions:

• Expanded use of scientific repositories coupled with interactive visualizations offers a powerful approach for studying complex physical models.
• This methodology improves accessibility, reanalysis capabilities, and collaborative potential in physics research.
• The presented examples highlight the broad applicability and effectiveness of the proposed framework.