PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 3, 2026npj Acoustics0 citationsOpen Access

Direct measurement of Zak phase and higher winding numbers in an electroacoustic cavity system

GHGe HeZCZhaoxian ChenXZXiao-Meng Zhang

Key Points

  • Quantized Zak phase was directly observed, confirming the presence of topological invariants during state evolution.
  • The method involved tracking phase differences of states along parameter-space paths under external driving fields.
  • Experimental approach utilized electroacoustic coupled resonators to emulate bulk wavefunctions of periodic systems.
  • This work opens pathways for investigating more complex topological systems beyond the SSH model.

Abstract

Topological phases are states of matter defined by global topological invariants that remain invariant under adiabatic parameter variations, provided no topological phase transition occurs. Experimentally, these phases are often identified indirectly by observing robust boundary states, protected by the bulk-boundary correspondence. Here, we propose an experimental method for the direct measurement of topological invariants via adiabatic state evolution in electroacoustic coupled resonators, where time-dependent cavity modes effectively emulate the bulk wavefunction of a periodic system. Under varying external driving fields, specially prepared initial states evolve along distinct parameter-space paths. By tracking the relative phase differences among states along these trajectories, we successfully observe the quantized Zak phase in both the conventional Su–Schrieffer–Heeger (SSH) model and its extension incorporating long-range coupling. This approach provides compelling experimental evidence for the precise identification of topological invariants and can be extended to more complex topological systems.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

He et al. (2026) studied this question.

synapsesocial.com/papers/69a765fabadf0bb9e87db233https://doi.org/10.1038/s44384-025-00039-0
Ask AI
Helpful
Bookmark
Share
View Full Paper