Quantum Networks & Repeaters
Quantum Networks — Entanglement Distribution & Repeaters · Quantum Networking
Build a quantum internet — distribute entanglement over continental distances by beating fibre loss with repeaters and memories.
📋 The problem
A quantum internet needs entanglement shared over long distances, but photon loss kills direct transmission exponentially. Quantum repeaters with memories and entanglement swapping restore a usable rate — if scheduled well.
🧗 Why it's a grand challenge
Memories decohere, swaps succeed only probabilistically, and the optimal cutoff/scheduling policy is a stochastic control problem over a large state space.
🧮 Governing model
R_direct ∝ η = e^{−L/L_att}; R_repeater ∝ (η^{1/n})·p_swap^{n−1}·f(τ_mem)Entanglement-distribution rate over a repeater chain: direct transmission decays as R∝e^{−L/L_att}; n-segment repeaters with memories restore a polynomial scaling set by swap success and memory coherence.
Current best: Memory-based repeater links (quantum-network testbeds, Delft/Hefei)
🧭 Possible approaches
- RL / optimal scheduling of swapping and cutoff policies
- Link-layer protocol discovery
- Co-optimization of memory quality vs rate
🎯 Build the benchmark
Maximize end-to-end entanglement rate at a fixed target fidelity over realistic repeater chains, vs direct transmission.
Metric: ent_rate — entangled pairs/s at 1000 km (higher better)
Datasets to start from: Repeater-chain link-budget corpus, Quantum-memory coherence dataset
🤖 Build an AI agent to solve it
An agent that designs and schedules repeater-chain protocols for a target distance and fidelity.
Once a benchmark exists, an AI4Science agent can iterate solutions against it — every verified solution earns PWM.
This is a frontier framing page — an open problem, not yet benchmarked or verified, unlike PWM's mature computational-imaging benchmarks.