Detection of hidden structures for arbitrary scales in complex physical systems.

Area of Science:

• Materials Science
• Condensed Matter Physics
• Network Science

Background:

• Complex materials with numerous atomic configurations are frequently discovered.
• Understanding these materials requires tools to detect structures across various scales.
• Existing methods may struggle with systems lacking clear definitions of order.

Purpose of the Study:

• To introduce a novel method for analyzing complex material structures.
• To enable the detection of pertinent structures on all spatial and temporal scales.
• To provide tools for systems where order is not clearly defined.

Main Methods:

• The new method integrates concepts from network analysis and information theory.
• It is applicable to both static and dynamic systems.
• The approach efficiently identifies fundamental structures and defects.

Main Results:

• The method successfully identifies basic unit cells within complex materials.
• It detects topological defects, crucial for understanding material properties.
• Candidate natural structures are efficiently identified, aiding further analysis.

Conclusions:

• The proposed method offers a powerful new tool for analyzing complex materials.
• It is particularly valuable for systems with ill-defined order.
• The identified features provide a foundation for deeper scientific investigation.