# Dynex SDK

## Docs

- [Compute Backends](https://dynex.mintlify.app/annealing/backends.md): Run on Dynex neuromorphic GPU chips or test locally
- [Defining Models](https://dynex.mintlify.app/annealing/models.md): BQM, CQM, and DQM — choosing and building the right model
- [Parallel Sampling](https://dynex.mintlify.app/annealing/parallel.md): Run multiple samplers simultaneously for federated learning and ensemble methods
- [Sampling Models](https://dynex.mintlify.app/annealing/sampling.md): Sampling parameters, backends, and result interpretation
- [DynexCircuit](https://dynex.mintlify.app/api-reference/dynex-circuit.md): Execute quantum gate circuits on the Dynex platform
- [DynexConfig](https://dynex.mintlify.app/api-reference/dynex-config.md): Configuration handler for credentials, backend selection, and SDK behavior
- [DynexSampler](https://dynex.mintlify.app/api-reference/dynex-sampler.md): Submit annealing jobs and retrieve results from the Dynex platform
- [API Reference](https://dynex.mintlify.app/api-reference/introduction.md): Complete reference for all Dynex SDK classes and methods
- [Model Classes](https://dynex.mintlify.app/api-reference/models.md): BQM, CQM, DQM — Dynex model wrappers
- [DynexCircuit](https://dynex.mintlify.app/circuits/dynex-circuit.md): Execute PennyLane, Qiskit, and OpenQASM circuits on the Dynex platform
- [Circuit Examples](https://dynex.mintlify.app/circuits/examples.md): Bell state, Grover, Shor, QFT, and quantum transformer circuits on Dynex
- [Quantum Gates](https://dynex.mintlify.app/circuits/overview.md): Quantum gate reference for PennyLane, Qiskit, and OpenQASM on Dynex
- [Grover's Algorithm](https://dynex.mintlify.app/examples/algorithms/grover.md): Integer factorization via quantum amplitude amplification on Dynex
- [Optimization Algorithms](https://dynex.mintlify.app/examples/algorithms/optimization.md): MaxCut, graph partitioning, job sequencing, and combinatorial problems on Dynex
- [Shor's Algorithm](https://dynex.mintlify.app/examples/algorithms/shor.md): Period-finding for efficient integer factorization on Dynex
- [BQM Usage Examples](https://dynex.mintlify.app/examples/basic/bqm-usage.md): Working with Binary Quadratic Models in Dynex SDK
- [Simple BQM Sampling](https://dynex.mintlify.app/examples/basic/simple-sampling.md): Basic example of sampling a Binary Quadratic Model
- [Quantum Machine Learning](https://dynex.mintlify.app/examples/ml/overview.md): QSVM, QPCA, QBM, QNN, and feature selection on Dynex
- [Quantum RBM / QBM](https://dynex.mintlify.app/examples/ml/qrbm.md): Quantum Restricted Boltzmann Machine via quantum annealing on Dynex
- [Quantum SVM](https://dynex.mintlify.app/examples/ml/qsvm.md): Quantum Support Vector Machine for classification on Dynex
- [Neuromorphic Torch Layers](https://dynex.mintlify.app/examples/ml/torch-layers.md): Drop-in PyTorch layers backed by Dynex quantum computation
- [Examples Overview](https://dynex.mintlify.app/examples/overview.md): Practical examples across optimization, machine learning, algorithms, and circuits
- [Automotive & Aerospace](https://dynex.mintlify.app/examples/use-cases/automotive-aerospace.md): Quantum computing applications in vehicle design, traffic optimization, and aerospace engineering
- [Finance](https://dynex.mintlify.app/examples/use-cases/finance.md): Quantum computing applications in portfolio optimization, risk management, and financial services
- [Logistics & Operations](https://dynex.mintlify.app/examples/use-cases/logistics.md): Quantum computing applications in routing, scheduling, and supply chain optimization
- [Pharma & Health](https://dynex.mintlify.app/examples/use-cases/pharma-health.md): Quantum computing applications in drug discovery, protein folding, and biomedical research
- [Telecommunication](https://dynex.mintlify.app/examples/use-cases/telecom.md): Quantum computing applications in network optimization and infrastructure planning
- [Installation](https://dynex.mintlify.app/installation.md): Install the Dynex SDK and configure your environment
- [Introduction](https://dynex.mintlify.app/introduction.md): Dynex Quantum Platform: A cloud-based, qubit-agnostic platform
- [Algorithmic Emulation Resources](https://dynex.mintlify.app/platform/algorithmic-emulation-resources.md): In addition to physical hardware, Dynex provides access to high-performance software-based emulation resources
- [Dynex Compute Systems](https://dynex.mintlify.app/platform/dynex-compute-systems.md): Dynex Compute Systems
- [Integration of External Quantum Hardware](https://dynex.mintlify.app/platform/external-quantum-hardware.md): Dynex supports interoperability with a range of external quantum computing providers
- [Overview](https://dynex.mintlify.app/platform/overview.md): Dynex Quantum Platform: A cloud-based, qubit-agnostic platform
- [Runtime and Deployment Model](https://dynex.mintlify.app/platform/runtime-deployment-model.md): The Dynex runtime environment is designed for flexible, managed execution
- [Workflow: Formulation and Sampling](https://dynex.mintlify.app/platform/workflow.md): The standard Dynex SDK workflow from problem definition to result analysis
- [Quickstart](https://dynex.mintlify.app/quickstart.md): Run your first quantum computation in under 5 minutes

## OpenAPI Specs

- [openapi](https://dynex.mintlify.app/api-reference/openapi.json)

## Optional

- [GitHub](https://github.com/Dynex-Development/PY-SDK-V2)
- [Community](https://join.slack.com/t/dynex-workspace/shared_invite/zt-22eb1n4mo-aXS5zsUBoPs613Dofi8Q4A)
- [Publications](https://dynex.co/learn/scientific-publications)