quantum-network-control

name

quantum-network-control

description

Optimize entanglement distribution in quantum networks via link-layer control strategies. Compare sequential vs simultaneous entanglement swapping for multi-hop quantum communication. Use when: (1) designing quantum network architectures, (2) optimizing entanglement distribution, (3) comparing quantum repeater strategies, (4) quantum internet protocol design, (5) entanglement swapping optimization, (6) quantum network link-layer control.

Quantum Network Control

Optimize entanglement distribution and swapping in multi-hop quantum networks. Based on sequential vs simultaneous entanglement swapping analysis (arXiv:2605.04047).

Core Concepts

Entanglement Swapping Strategies

Sequential Swapping:

• Nodes act on local state information only
• Each hop waits for previous hop to complete
• Simpler but higher latency
• Lower resource requirements per node

Simultaneous Swapping:

• Multiple nodes perform Bell measurements concurrently
• Requires global coordination or pre-agreed schedules
• Lower latency but higher resource demands
• Better throughput for long-distance links

Progressive Swapping to the Middle (PSM): (Updated 2026-06-02, arXiv:2605.31493)

• Establish entanglement in parallel on all segments, then progressively swap toward the middle
• Minimizes memory holding time: O(log n) vs O(n) for sequential
• Specifically adapted for networks with imperfect quantum memories
• When to use: Multi-hop networks where memory decoherence is the bottleneck (T_coh < (n-1) × t_swap)
• Key advantage: Memory-aware scheduling accounts for heterogeneous node coherence times
• See progressive-swapping-quantum-network-protocol skill for detailed PSM implementation patterns

Key Metrics

• Fidelity: Quality of end-to-end entangled state
• Rate: Entangled pairs generated per second
• Latency: Time from request to entanglement delivery
• Memory requirements: Qubits needed at each node

Optimization Framework

Step 1: Model the Network

network = {
    "nodes": ["A", "B", "C", "D"],
    "links": [
        ("A", "B", {"distance_km": 50, "fidelity": 0.95}),
        ("B", "C", {"distance_km": 50, "fidelity": 0.95}),
        ("C", "D", {"distance_km": 50, "fidelity": 0.95}),
    ],
    "memory_coherence_time_ms": 100,
    "bell_measurement_fidelity": 0.98,
}

Step 2: Choose Swapping Strategy

Criterion	Sequential	Simultaneous
Latency	O(n) rounds	O(1) rounds
Memory per node	1 qubit	O(degree) qubits
Coordination	Local	Global
Best for	Long chains	Dense networks

Step 3: Optimize Link-Layer Control

• Scheduling: When to attempt entanglement generation
• Buffering: How long to store entangled pairs
• Routing: Which path to use for multi-hop connections
• Purification: When to apply entanglement distillation

Workflow

1. Define network topology and link parameters
2. Compute expected fidelity for each path
3. Select optimal swapping strategy per route
4. Simulate or analyze throughput/latency tradeoffs
5. Tune memory management and purification thresholds

Key References

• Entanglement swapping optimization: arXiv:2605.04047
• Progressive Swapping to the Middle (PSM) protocol: arXiv:2605.31493 - see progressive-swapping-quantum-network-protocol skill for memory-aware PSM implementation
• Related: quantum-systems-engineering, distributed-quantum-computing, progressive-swapping-quantum-network-protocol

Limitations

• Assumes perfect classical communication for coordination
• Fidelity models may not capture all hardware imperfections
• Scaling to large networks requires approximation methods