Quick Navigation
Topics
Quantum Networks
Quantum Simulation
Q2NSViz: An Open-source Standalone Visualizer for Quantum Network Simulations
arXiv
Authors: Francesco Mazza, Marcello Caleffi, Angela Sara Cacciapuoti
Year
2026
Paper ID
72816
Status
Preprint
Abstract Read
~2 min
Abstract Words
153
Citations
N/A
Abstract
The unique and non-classical features of quantum networks make their simulation and intuitive understanding inherently difficult. In this work, we present Q2NSViz, an open-source Python-based visualization tool for replaying and inspecting quantum-network simulation traces. Q2NSViz reconstructs the time evolution of the simulated network state, including physical topology, stored and in-flight qubits, classical bits and packets, measurements, and entanglement relationships. In this way, it exposes not only physical connectivity, but also the dynamic entanglement-induced structure produced, consumed, and transformed by protocol execution. Q2NSViz is built around a decoupled JSON/NDJSON trace contract, a Qt-free replay engine, and an interactive PyQt6 interface, making it a standalone companion to Q2NS and reusable by other simulation backends that emit the same trace format. By turning execution traces into navigable and reproducible visual artifacts, Q2NSViz provides a zero-coding tool for researchers and educators, narrowing the gap between abstract protocol logic and concrete execution.
Why This Paper Matters
- This paper contributes to the Quantum Networks research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- The unique and non-classical features of quantum networks make their simulation and intuitive understanding inherently difficult.
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.