QGen: Quantum Generative Models
This project explores the exciting potential of quantum computing to solve complex problems more efficiently than traditional computers.
Start
2025-01-01
Planned completion
2025-12-31
Main financing
Research group
Project manager at MDU
Our project explores the exciting potential of quantum computing to solve complex problems more efficiently than traditional computers. We focus on generative models, which are used in various real-world applications like designing new drugs and improving decision-making in industries. There are different types of generative models, each with its own strengths and weaknesses. In our research, we aim to improve generative models by using concepts from mathematics to organize how they learn. This approach allows us to make better sense of the data they work with. We plan to test our ideas using advanced computer simulations that mimic quantum computing, comparing their performance with traditional methods. This will help us understand whether a mix of quantum and classical computing can lead to better solutions for complex challenges.
Project objectives
- Enhance Generative Models: Improve the ability of generative models to create useful new data, which can lead to breakthroughs in fields like drug design and decision-making in industries.
- Leverage Quantum Computing: Utilize the power of quantum computing to make these models more efficient and effective compared to traditional computing methods.
- Conduct Comparative Research: Test and compare the performance of quantum-based generative models with classical approaches using advanced computer simulations to identify the best solutions for complex challenges.