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Characterizing graph symmetries through quantum Jensen-Shannon divergence.

Luca Rossi1, Andrea Torsello, Edwin R Hancock

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This study links quantum walks and graph symmetries using quantum Jensen-Shannon divergence. Maximum divergence between quantum walks indicates graph symmetries, enabling symmetry characterization.

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Area of Science:

  • Quantum Information Science
  • Graph Theory
  • Quantum Computing

Background:

  • Quantum walks are a fundamental primitive in quantum computation.
  • Graph symmetries play a crucial role in understanding graph structures.
  • Analyzing quantum walk behavior without wave function collapse is an open challenge.

Purpose of the Study:

  • To investigate the relationship between quantum walks and graph symmetries.
  • To develop a method for analyzing quantum walks on graphs without wave function collapse.
  • To quantify graph symmetry using quantum information-theoretic tools.

Main Methods:

  • Designing an experimental framework to analyze quantum walks without wave function collapse.
  • Utilizing the quantum Jensen-Shannon divergence to compare quantum walk evolutions.
  • Assigning divergence values to node pairs and averaging to characterize graph symmetry.

Main Results:

  • Quantum Jensen-Shannon divergence is maximized for quantum walks on graphs with symmetries.
  • A novel method is established to measure graph symmetry via quantum walk behavior.
  • The quantum Jensen-Shannon divergence serves as a robust indicator of graph symmetries.

Conclusions:

  • Quantum walks can be effectively used to detect and quantify graph symmetries.
  • The quantum Jensen-Shannon divergence provides a powerful tool for analyzing quantum systems on graphs.
  • This research bridges quantum information theory and graph analysis, opening new avenues for research.