Quantum optimization algorithms' performance under different problem structures

• Grant number: 23/13524-0
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: March 01, 2024
• End date: July 31, 2028
• Field of knowledge: Physical Sciences and Mathematics - Physics
• Principal Investigator: Marcos César de Oliveira
• Grantee: Arthur Kenzo Feltrin Iwakami
• Host Institution: Instituto de Física Gleb Wataghin (IFGW). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The objectives of this project involve improving quantum optimization algorithms through a combination of simulations and real quantum hardware experimentation from commercial providers. Key areas of exploration include:- Enhanced initialization techniques (warm-starting) for the algorithms.- Strategies for customizing algorithm parameters or structures to specific problem classes.- Expanding algorithm applicability to domains where it currently cannot operate, such as handling integer variables instead of binary.- Investigating diverse practical applications of the algorithms, as their performance heavily depends on the mathematical characteristics of the optimization problem and its application context.Project objectives ordered by priority:1. Develop general Python framework for quantum optimization algo-rithm benchmarking.2. Choose and evaluate a set of algorithms under various problemsets and objective function classes. Establish relations between thealgorithm's and the problem's mathematical structure based on results.3. Improve performance of a chosen algorithm by making problem-specific modification to its structure.4. Extend existing algorithms to new variable domains beyond binary.5. Find new quantum analogs to classical optimization algorithms andmeta-heuristics.