Quick Navigation
Topics
Quantum Simulation
Wigner Cat Phases: A finely tunable system for exploring the transition to quantum chaos
arXiv
Authors: M. Süzen
Year
2025
Paper ID
6004
Status
Preprint
Abstract Read
~2 min
Abstract Words
157
Citations
N/A
Abstract
A transition to quantum chaos is characterized by a finely tunable mixed random matrix ensemble. The {\it mixed Gaussian Orthogonal Ensemble (mGOE)} offers a pedagogically accessible framework for simulating {\it Many-Body Localization (MBL)} transitions. It can be tuned from chaotic to localized and heavy-tailed phases in a continuous fashion, providing an opportunity to explore new phases. We numerically study how the spectral properties of mGOE evolve across these transitions. Characterization of the transition to quantum chaos is computed and analyzed via empirical spectral density, nearest-neighbor spacing, and adjacent gap, with statistical uncertainty quantification that strengthens the robustness of the evidence for transitions. The transitions are identified as the {\it Wigner Cat Phases}, due to the shape of empirical spectral density, which depend on the tunable parameter. These simulated phases in mGOE provide a valuable framework to study the {\it Eigenstate Thermalization Hypothesis (ETH)} and its related transitions, representing a family of systems with tunable localization and disorder.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- A transition to quantum chaos is characterized by a finely tunable mixed random matrix ensemble.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.