Quantum Architecture Search with Meta-learning

Understand

Variational quantum algorithms (VQAs) have been successfully applied to quantum approximate optimization algorithms, variational quantum compiling and quantum machine learning models.

• The performances of VQAs largely depend on the architecture of parameterized quantum circuits (PQCs).
• Quantum architecture search (QAS) aims to automate the design of PQCs in different VQAs with classical optimization algorithms.
• However, current QAS algorithms do not use prior experiences and search the quantum architecture from scratch for each new task, which is inefficient and time consuming.