Principal Component Analysis of Event-by-Event Fluctuations

Area of Science:

• High-energy physics
• Nuclear physics

Background:

• Relativistic heavy-ion collisions create complex particle interactions.
• Understanding event-by-event fluctuations is crucial for nuclear matter studies.

Purpose of the Study:

• To apply Principal Component Analysis (PCA) to analyze event-by-event fluctuations.
• To investigate multiplicity fluctuations and anisotropic flow in heavy-ion collisions.
• To reveal previously unobserved patterns in particle momentum distributions.

Main Methods:

• Application of Principal Component Analysis (PCA) to two-particle correlations.
• Analysis of ALICE data and simulated events from relativistic heavy-ion collisions.
• Study of elliptic and triangular flow fluctuations versus transverse momentum and rapidity.

Main Results:

• PCA provides a physically transparent method for extracting information from correlations.
• New subleading modes were identified in rapidity and transverse momentum.
• Detailed analysis of elliptic and triangular flow fluctuations was performed.

Conclusions:

• PCA is a powerful tool for uncovering hidden structures in heavy-ion collision data.
• The identified subleading modes offer new insights into particle production mechanisms.
• This approach enhances the understanding of fluctuations in relativistic heavy-ion collisions.