Introduction
- Motivate the need for distributed quantum computing as a way to scale up quantum computation and enable quantum networks
- Define distributed quantum computing as a model where multiple quantum computers communicate and cooperate via a network
- Give some examples of applications and challenges of distributed quantum computing
Distributed quantum memory
- Explain the concept and importance of quantum memory for storing and retrieving quantum information
- Compare different types of quantum memory devices, such as atom-based, ion-based, spin-based, etc.
- Discuss some recent progress and open problems on distributed quantum memory, such as entanglement distribution, robustness, efficiency, etc.
Distributed quantum algorithms
- Explain the concept and importance of quantum algorithms for performing specific tasks on quantum data
- Compare different types of quantum algorithms, such as variational, simulation, optimization, etc.
- Discuss some recent progress and open problems on distributed quantum algorithms, such as parallelization, network control, resource allocation, etc.
Error detection and correction codes on a distributed quantum system
- Explain the concept and importance of error detection and correction codes for protecting quantum information from noise and decoherence
- Compare different types of error detection and correction codes, such as stabilizer codes, surface codes, topological codes, etc.
- Discuss some recent progress and open problems on error detection and correction codes on a distributed quantum system, such as fault tolerance, scalability, adaptability, etc.
Conclusion
- Summarize the main points and findings of the talk
- Highlight the potential and challenges of distributed quantum computing
- Suggest some future directions and open questions for further research