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As in the computer world, not all programming languages are suitable for everything.

Php = Backend
Javascript = Frontend
Data Analsys/ML = Python
embedded systems = C
Mobilphone/apps = Android / Swift

As far as I know not all quantum languages solve the same problems. I would like to know which framework(qiskit, cirq..) would be suitable for optimisation problems (for example Travel Salesman Problem).

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There is Qiskit Optimization application module entirely suitable for solving optimization problems as it can be noticed from the name. This module is based on Qiskit and provides high level interfaces to optimization define problems and solve them via various quantum algorithms. The module is written in python. Take a look at the module page and tutorials:

Documentation: https://qiskit.org/documentation/optimization/

Tutorials: https://qiskit.org/documentation/optimization/tutorials/index.html

Solving traveling salesman problem problem: https://qiskit.org/documentation/optimization/tutorials/06_examples_max_cut_and_tsp.html#Traveling-Salesman-Problem

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I also suggest Xanadu's Pennylane (https://pennylane.ai/).

Examples/tutorials: https://pennylane.ai/qml/demonstrations.html

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D-Wave is the main provider of quantum annealers for the last 20 years. The company just announced its expansion into gate-based quantum systems (making it the only provider of both types at the time of this writing).

https://www.dwavesys.com/company/newsroom/press-release/let-s-get-practical-d-wave-details-product-expansion-cross-platform-roadmap/

Quantum annealing is a metaheuristic procedure that finds the global minimum of an objective function (corresponding to the "minimum energy"). Quantum annealing is best suited for combinatorial optimization problems with a large discrete search space (and many local minima).

D-Wave technical documentation: https://www.dwavesys.com/learn/resource-library/

D-Wave code examples: https://github.com/dwave-examples

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