Quantum Thermodynamics Inspired Heuristic Optimization Algorithm Article Swipe
This paper proposes a novel heuristic optimization algorithm that directly draws upon the core principles of quantum thermodynamics, including coherent evolution, thermal dissipation, quantum fluctuations, entropy generation, and the work-information coupling mechanism. Traditional optimization algorithms often get trapped in local optima when dealing with complex non-convex problems, lacking global exploration capabilities and dynamic diversity control. The proposed algorithm constructs a density matrix to represent the candidate solution set, maps the objective function to a dynamic energy level Hamiltonian, and achieves an organic combination of global exploration and local accelerated convergence through alternating updates using coherent evolution, thermal dissipation, quantum fluctuation operators, and work-information coupling operators. This paper elaborates on the algorithm's mathematical model, update mechanism, entropy-energy control strategy, and pseudocode implementation, providing a complete theoretical framework and a new approach to complex optimization problems.
Related Topics
Concepts
Mathematical optimization
Computer science
Heuristic
Quantum
Convergence (economics)
Entropy (arrow of time)
Global optimization
Local optimum
Coupling (piping)
Optimization problem
Quantum computer
Algorithm
Quantum annealing
Function (biology)
Density matrix
Core (optical fiber)
Optimization algorithm
Quantum phase estimation algorithm
Thermal
Mathematics
Energy (signal processing)
Matrix (chemical analysis)
Derivative-free optimization
Quantum algorithm
Random optimization
Metaheuristic
Meta-optimization
Metadata
- Type
- preprint
- Landing Page
- https://doi.org/10.5281/zenodo.17852922
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7110940611
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7110940611Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17852922Digital Object Identifier
- Title
-
Quantum Thermodynamics Inspired Heuristic Optimization AlgorithmWork title
- Type
-
preprintOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-08Full publication date if available
- Authors
-
Zhang JinchengList of authors in order
- Landing page
-
https://doi.org/10.5281/zenodo.17852922Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5281/zenodo.17852922Direct OA link when available
- Concepts
-
Mathematical optimization, Computer science, Heuristic, Quantum, Convergence (economics), Entropy (arrow of time), Global optimization, Local optimum, Coupling (piping), Optimization problem, Quantum computer, Algorithm, Quantum annealing, Function (biology), Density matrix, Core (optical fiber), Optimization algorithm, Quantum phase estimation algorithm, Thermal, Mathematics, Energy (signal processing), Matrix (chemical analysis), Derivative-free optimization, Quantum algorithm, Random optimization, Metaheuristic, Meta-optimizationTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
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