Applications of network theory
I apply network science tools to problems in statistical physics and quantum systems, and study novel percolation processes with non-local rules.
Statistical physics of networks
Using network-based measures and topological data analysis, I characterised phase transitions in the Ising model, revealing distinct network-science Ising states of matter. I also developed non-parametric learning approaches for critical behavior in Ising partition functions using PCA entropy and intrinsic dimension.
Quantum networks
I studied entanglement transmission in quantum networks, uncovering the importance of nonshortest paths — a finding that challenges conventional shortest-path-based analyses of quantum communication.
Non-local percolation
I investigated shortest-path percolation, a novel process where edges are removed in a spatially and temporally correlated fashion, and revealed markedly different critical behaviour on Erdős–Rényi and scale-free networks.
Related publications
- Unveiling the importance of nonshortest paths in quantum networks — Science Advances
- Network science: Ising states of matter — Physical Review E
- Non-parametric learning critical behavior in Ising partition functions: PCA entropy and intrinsic dimension — SciPost Physics Core
- Shortest-path percolation on scale-free networks — Physical Review E
