Reverse Dependencies of dimod

The following projects have a declared dependency on dimod:

• amazon-braket-ocean-plugin — An open source framework for interacting with D-Wave's Ocean library through Amazon Braket
• AQMLator — A package for auto quantum machine learning-izing your experiments!
• beit-qubo-solver — Client package for the exact qubo solver by BEIT available at AWS Marketplace.
• bqs — Better Quantum Software
• bqtmizer — BQTmizer: A Tool for Test Case Minimization with Quantum Annealing
• dimod-cache — A replay cache for the `dimod.Sampler`-class.
• dwave-cloud-client — A minimal client for interacting with D-Wave cloud resources.
• dwave-hybrid — Hybrid Asynchronous Decomposition Solver Framework
• dwave-inspector — D-Wave Problem Inspector tool
• dwave-micro-client-dimod — dimod wrapper for the D-Wave Micro Client
• dwave-networkx — A NetworkX extension providing graphs and algorithms relevent to working with the D-Wave System
• dwave-ocean-sdk — Software development kit for open source D-Wave tools
• dwave-preprocessing — An API for preprocessing tools
• dwave-qbsolv — no summary
• dwave_sage — General Ising graph simulated annealing solver
• dwave-samplers — Ocean-compatible collection of solvers/samplers
• dwave-sapi-dimod — no summary
• dwave-scikit-learn-plugin — A plugin to scikit-learn for quantum hybrid solving
• dwave-sdk — Software development kit for open source D-Wave tools
• dwave-system — All things D-Wave System.
• dwavebinarycsp — Solves constraints satisfaction problems with binary quadratic model samplers
• dynex — Dynex SDK Neuromorphic Computing
• falcondale — Falcondale SDK
• FastHareComposite — A composite for using FastHare reduction with the samplers from D-Wave Ocean SDK
• jij-cimod — C++ library for a binary (and polynomial) quadratic model.
• jijcloud — no summary
• jijmodeling-transpiler — no summary
• kipu-client — Python client for Kipu platform
• luna-quantum — Python SDK for Aqarios' Luna Platform
• npqtools — Library for reinterpretation main np-problems into Ising model for quantum computer
• omniqubo — Extensible framework for transforming optimization models to binary models
• omnisolver — Extensible framework for creating and running Binary Quadratic Model solvers and samplers.
• openjij — Framework for the Ising model and QUBO.
• penaltymodel — Package for creating penalty models.
• penaltymodel-cache — A local cache for penalty models.
• penaltymodel-lp — Generates penalty models using SciPy's linear programming.
• penaltymodel-mip — Generates penalty models using Google Optimization Tools' Mixed-Integer Programming capability.
• pygrnd — A python library for quantum algorithms and software
• pyqubo — PyQUBO allows you to create QUBOs or Ising models from mathematical expressions.
• pyqubo2 — PyQUBO allows you to create QUBOs or Ising models from mathematical expressions with support for Python 3.12
• qaga — no summary
• qc-benchmark-dwave — caict qc benchmark tooklit for Dwave Leap cloud
• qonic — The Qonic project is an open source, expandable framework for solving problems using hybrid quantum computing solutions.
• quantagonia — This package contains the CLI and API to access Quantagonia's HybridSolver.
• quark-famework — Framework for Quantum Computing Application Benchmarking
• quark-framework — Framework for Quantum Computing Application Benchmarking
• qudas — Quantum data transform package
• strangeworks-hybrid-optimize — Extension to strangeworks sdk to allow user to run the hybrid optimization service
• strangeworks-optimization — This SDK extends the Strangeworks SDK to provide access to the Strangeworks Optimization API.
• strangeworks-optimization-models — Pydantic models for strangeworks optimization SDK and application
• strangeworks-qaoa — Extension to strangeworks sdk to allow user to run qaoa service
• tno.quantum.problems.portfolio-optimization — Quantum Computing based Portfolio Optimization
• uqo — Client of the optimization framework UQO
• uqoclient — Client of the optimisation framework UQO
• uvic-qplex — an open-source Python library that enables developers to implement combinatorial optimization models and execute them seamlessly on multiple classical and quantum devices using different quantum algorithms.
• v-quantum-annealing — Quantum Computer Library for Everyone
• vqa-cimod — Quantum Computer Library for Everyone
• vrp-quantum-solver — Package to solve vehicle routing problems using quantum optimization algorithms