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Strangeworks Optimization

The Strangeworks Optimization SDK provides an abstraction layer for solving optimization problems using classical, quantum-inspired, and quantum solvers. It enables you to seamlessly switch between different optimization backends while maintaining a consistent interface.

Features

  • Unified API for multiple optimization solvers (quantum, quantum-inspired, and classical)
  • Support for multiple problem formats including QUBO, MPS, LP, and more
  • Solver-agnostic interface that allows easy switching between providers
  • Job management with status tracking and result retrieval

Installation

pip install strangeworks-optimization

Quick Start

import strangeworks as sw
from dimod import BinaryQuadraticModel
from strangeworks_optimization import StrangeworksOptimizer

# Authenticate with your API key
sw.authenticate("your-api-key")

# Create a QUBO model
linear = {1: -2, 2: -2, 3: -3, 4: -3, 5: -2}
quadratic = {(1, 2): 2, (1, 3): 2, (2, 4): 2, (3, 4): 2, (3, 5): 2, (4, 5): 2}
model = BinaryQuadraticModel(linear, quadratic, "BINARY")

# Create and run the optimizer with Quantagonia
optimizer = StrangeworksOptimizer(model=model, solver="quantagonia.qubo")
job = optimizer.run()

# Get results
results = optimizer.results(job.slug)
print(results.solution)

Documentation

Comprehensive documentation is available at docs.strangeworks.com/optimization.

The documentation includes:

  • Getting started guides
  • API reference
  • Supported solvers and providers
  • Problem format specifications
  • Examples and tutorials

Supported Solvers

The SDK supports a wide range of optimization solvers including:

  • Classical solvers: Gurobi, Quantagonia
  • Quantum annealers: D-Wave Leap, D-Wave Sampler
  • Quantum-inspired: Hitachi, NEC, Toshiba
  • Hybrid solvers: D-Wave Hybrid, Strangeworks Hybrid

For a complete list and solver-specific configuration options, see the documentation.

Requirements

  • Python 3.11 or higher
  • A Strangeworks account and API key (Get started)

License

This project is licensed under the Apache License 2.0.

Support

For support, questions, or feature requests, please visit:

Metadata

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