Quantum
Programmable Preparation of Topological Entangled States
Publication: quant-ph updates on arXiv.org
Author: M. Javad Zakeri, Alaric Pan, Darren D Hudson, Andrea Blanco-Redondo
Source published: 19/10/2026, 04:00:00 UTC
Briefing created: 19/10/2026, 04:17:35 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 19/10/2026, 04:13:24 UTC.
Briefings
A 2026 arXiv preprint reports the first demonstration of programmable preparation of topological entangled states using inverse-engineered nonlinear optical pump profiles in silicon photonic superlattices. The study achieves deterministic control over entangled state dimensionality and modal structure while preserving topological protection. Site-resolved measurements confirm robustness against nanofabrication disorder, enabling tailored Schmidt dimensionalities for high-dimensional quantum communication.
Key points
- Researchers demonstrated programmable preparation of topological entangled states by inverse-engineering the nonlinear optical pump profile in integrated silicon photonic superlattices.
- Site-resolved two-photon correlation measurements confirmed reproducible results across nominally identical devices, demonstrating robustness to realistic nanofabrication-induced disorder.
Context
Topological photonic platforms offer robust quantum-state generation via symmetry-protected modes, but previous entangled states were dictated by fixed lattice geometry. This work enables deterministic control over entangled state properties via tailored pump excitations, establishing a pathway for application-specific quantum resources in quantum networking and photonic computing.
Limitations
The evidence is an unverified arXiv preprint from October 2026, so experimental validation and peer review are pending. Results are based on a single fabrication batch, limiting generalizability to other device geometries or fabrication processes. Future work is required to confirm reproducibility across diverse manufacturing conditions and to scale the approach for commercial deployment.
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