Theme: Quantum for Impact: Fostering Education, Research, and Collaboration towards SDG’s
Following the E-Learning African International School on Quantum Science and Technology (ELAIS-QST 2024), the African International Conference on Quantum Algorithms for Simulation <AoC|Q> will gather leading experts, scientists, researchers and students from across Africa in different fields such as materials science, physics, chemistry, engineering and others to explore cutting-edge quantum algorithms and their applications in simulating complex systems. This 7-day event will feature a rich program of opening ceremony, keynote presentations, roundtable discussions, interactive workshop series with lectures, tutorials or hands-on, outreach to senior high schools in Kumasi, and poster sessions, each designed to delve into various aspects of classical-quantum algorithms of complex systems.
The key focus of the conference will be to explore the understanding of development and refinement made in:
1. classical algorithms and computation such as machine learning, tensor network representations or mapping random circuits to statistical mechanics models and others for quantum many-body in quantum materials and quantum chemistry.
2. quantum algorithms, such as adaptive and control variational quantum eigenvalue solvers algorithms, quantum machine learning algorithms, quantum approximate optimization algorithms and others which offer new possibilities for simulating materials.
3. policy direction such as national plan, centres, and others for building a national quantum ecosystem to find solutions for local and global issues
Topic: Classical - Quantum Algorithms, (Quantum) Machine Learning, Quantum Simulation and Quantum Computing.
Audience:
Students - a) Undergraduates b) Graduates from Bachelors c) National Service Personnel d) Master Students with Related Courses and Potential Thesis Topic in the Area e) PhD candidate of related field
Professional - a) Faculty members b) Scientists c) Industrialist d) Policy Makers - Governmental workers
Expected Background: Physics, Mathematics, Computer Science, Chemistry, Pharmaceutical Sciences, Engineering and others with related background