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npx versuz@latest install hiyenwong-ai-collection-collection-skills-distributed-quantum-computinggit clone https://github.com/hiyenwong/ai_collection.gitcp ai_collection/SKILL.MD ~/.claude/skills/hiyenwong-ai-collection-collection-skills-distributed-quantum-computing/SKILL.md---
name: distributed-quantum-computing
description: 'Distributed Quantum Computing architecture and patterns. Apply when designing multi-QPU systems, quantum communication protocols, or scaling quantum computing beyond single device limitations.'
metadata:
{
"openclaw":
{
"emoji": "⏛",
"source": "arxiv:2212.10609,arxiv:2404.01265",
"authors": ["Caleffi et al.", "Barral et al."],
"year": 2024,
},
}
---
# Distributed Quantum Computing
Framework from arxiv:2212.10609 & arxiv:2404.01265 - scaling quantum computing via distributed paradigm.
## Core Problem
**Single QPU Limitation:**
- Current: ~100-1000 noisy qubits
- Need: ~10,000-1,000,000 noise-free qubits for practical quantum advantage
- Solution: **Distributed quantum computing** - multiple QPUs communicating and cooperating
## Architecture
```
┌─────────────────────────────────────────────────────────────┐
│ Distributed Quantum Computing System │
├─────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ QPU-1 │ │ QPU-2 │ │ QPU-3 │ │
│ │ 100 qubits│ │ 100 qubits│ │ 100 qubits│ │
│ └──────────┘ ┌──────────┘ └──────────┘ │
│ │ │ │ │
│ └──────────────┼──────────────┘ │
│ │ │
│ ┌───────▼───────┐ │
│ │ Quantum Network│ │
│ │ (Entanglement │ │
│ │ Distribution)│ │
│ └───────┬───────┘ │
│ │ │
│ ┌───────▼───────┐ │
│ │ Distributed │ │
│ │ Quantum Gates│ │
│ └───────┬───────┘ │
│ │ │
│ ┌───────▼───────┐ │
│ │ Scheduler │ │
│ │ (Task Distribution)│ │
│ └───────┴───────┘ │
│ │
└─────────────────────────────────────────────────────────────┘
```
## Key Components
### 1. Quantum Communication Protocols
| Protocol | Purpose |
|----------|---------|
| **Teleportation** | Transfer quantum state between QPUs |
| **Entanglement swapping** | Create entanglement across non-directly connected QPUs |
| **Quantum routing** | Route qubits through quantum network |
### 2. Distributed Quantum Gates
- **Non-local gates:** Gates acting on qubits across different QPUs
- **CAT gates:** Communication-Assisted Teleportation gates
- **Telegate protocol:** Teleport gate execution to remote QPU
### 3. Scheduler
- Task decomposition across QPUs
- Minimize communication overhead
- Balance QPU workload
## Challenges
| Challenge | Description | Current Solutions |
|-----------|-------------|-------------------|
| **Entanglement distribution** | Create/maintain entanglement across QPUs | Quantum repeaters, entanglement swapping |
| **Noise propagation** | Errors spread across distributed system | Distributed error correction |
| **Communication overhead** | Teleportation requires classical communication | Minimize non-local gates |
| **Synchronization** | QPUs must be synchronized | Distributed quantum clock |
| **Scalability** | Network topology limits scaling | Hierarchical architecture |
## Design Patterns
### Pattern 1: Quantum Circuit Partitioning
```python
def partition_circuit(circuit, n_qpus):
"""Partition quantum circuit across multiple QPUs."""
partitions = []
for i in range(n_qpus):
partition = extract_local_gates(circuit, qpu_range=i)
non_local_gates = extract_non_local_gates(circuit, qpu_range=i)
partitions.append({
'local': partition,
'non_local': non_local_gates,
'communication': estimate_teleportation_cost(non_local_gates)
})
return optimize_partition(partitions)
```
### Pattern 2: Entanglement Distribution Network
```
QPUs connected via quantum network:
- Direct links: High-fidelity entanglement
- Indirect links: Entanglement swapping via repeaters
- Topology: Minimize shortest path between any two QPUs
```
### Pattern 3: Distributed Error Correction
- Surface code adapted for distributed QPUs
- Parity checks across QPU boundaries
- Requires entangled ancilla qubits
## Metrics
| Metric | Target |
|--------|--------|
| Entanglement fidelity | > 0.99 for distributed gates |
| Communication latency | < 1ms for teleportation |
| QPU utilization | > 80% parallel execution |
| Error rate | < 0.001 per distributed operation |
## Applications
- **Distributed Shor's algorithm:** Factor large numbers across QPUs
- **Distributed QAOA:** Optimize large-scale optimization problems
- **Quantum simulation:** Simulate larger quantum systems
- **Quantum machine learning:** Train larger quantum models
## Relation to OpenClaw
OpenClaw's distributed agent architecture parallels DQC:
- Multiple QPUs → Multiple agent instances
- Quantum communication → Agent communication protocols
- Distributed gates → Cross-agent tool calls
- Scheduler → Agent orchestrator
---
*Sources: arxiv:2212.10609 (Caleffi et al., 2024), arxiv:2404.01265 (Barral et al., 2024)*