Quantum Orchestration Patterns

As quantum computing matures, the need for multi-cloud orchestration becomes critical. This document presents patterns for managing quantum workloads across providers like IBM Quantum, Amazon Braket, and Azure Quantum.

Pattern 1: Provider Fallback

When a primary quantum provider is unavailable, automatically route to secondary providers.

Implementation

def execute_with_fallback(circuit, providers):

for provider in providers:

try:

return provider.execute(circuit)

except ProviderUnavailable:

continue

raise AllProvidersUnavailable()

Pattern 2: Cost-Optimized Routing

Select providers based on current pricing, queue depth, and job complexity.

Factors to Consider

**Queue Depth**: Shorter queues mean faster results

**Price per Shot**: Varies by provider and hardware

**Hardware Fidelity**: Higher fidelity = better results

Pattern 3: Hybrid Preprocessing

Use classical cloud resources for preprocessing before quantum execution.

Workflow

Prepare circuit on classical compute

Optimize using classical simulation

Submit to quantum hardware

Post-process results classically

Implementation Guidelines

The Xubits platform implements these patterns through its agent-based architecture. Our orchestration agents automatically select optimal providers based on the patterns described above.

Multi-Cloud Quantum Orchestration Patterns