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Everything about Quantum optimization algorithms
Optimization algorithms using quantum computing
Quantum optimization algorithms are quantum algorithms that are used to solve optimization problems. Mathematical optimization deals with finding the best solution to a problem from a set of possible solutions. Mostly, the optimization problem is formulated as a minimization of a target functional. For combinatorial optimization problems no proven exponential speed up has ever been found. Most provable results are similar to Grover's algorithm and have the potential for a modest polynomial speed up. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Quantum optimization algorithmsA 5-minute orientation
- Skim a recent paper: Quantum-Inspired Algorithms and Perspectives for OptimizationInfluential work since 2022
- Pick up a classic book: Particle Swarm OptimisationThe most-reprinted book on the subject
- Read the landmark paper: Quantum optimization using variational algorithms on near-term quantum devicesCited 659 times
- Go sideways: Optimal controlA closely related topic
- Go sideways: Levenberg–Marquardt algorithmA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Quantum optimization using variational algorithms on near-term quantum devices
Limitations of optimization algorithms on noisy quantum devices
Sequential minimal optimization for quantum-classical hybrid algorithms
Filtering variational quantum algorithms for combinatorial optimization
Performance comparison of optimization methods on variational quantum algorithms
Portfolio optimization with digitized counterdiabatic quantum algorithms
Depth optimization of quantum search algorithms beyond Grover's algorithm
Quantum-Informed Recursive Optimization Algorithms
🆕 Influential since 2022
Quantum-Inspired Algorithms and Perspectives for Optimization
Resilience Optimization of Post-Quantum Cryptography Key Encapsulation Algorithms
Performance of quantum annealing inspired algorithms for combinatorial optimization problems
Surrogate-based optimization for variational quantum algorithms
Unitary block optimization for variational quantum algorithms
📚 Books worth reading
- 📕Particle Swarm OptimisationJun Sun, Choi-Hong Lai · 2013
- 📕Particle swarm optimisationJun Sun · 2011
- 📕Recent advances in scientific computing and applicationsNev.) International Conference on Scientific Computing and Applications (8th 2012 Las Vegas · 2013
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Duality (optimization) In mathematical optimization theory, duality or the duality principle is the principle that optimization problems may be viewed from either of two perspectives…
- Gaudin model In physics, the Gaudin model, sometimes known as the quantum Gaudin model, is a model, or a large class of models, in statistical mechanics first described…
- Variational quantum eigensolver In quantum computing, the variational quantum eigensolver (VQE) is a quantum algorithm for quantum chemistry, quantum simulations and optimization problems…
- Multi-objective optimization In multiple-criteria decision making, multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization…
- Adiabatic quantum computation Adiabatic quantum computation (AQC) is a form of quantum computing which relies on the adiabatic theorem to perform calculations and is closely related…