SURF Mentoring

Potential projects/topics: In this research project, the student will delve into the exciting field of quantum computing by focusing on compilation solutions for variational quantum circuits. Variational quantum circuits play a pivotal role in quantum machine learning and optimization algorithms, where parameterized quantum gates are tuned to minimize a cost function. The student will explore novel compilation strategies to enhance the efficiency and performance of variational quantum circuits. This involves investigating gate synthesis, circuit optimization, architecture-aware representations, and resource-aware compilation techniques to minimize gate count, depth, and overall computational cost. The student will gain hands-on experience with quantum programming language interface, quantum circuit optimization tools, and quantum cloud offerings, contributing to advancing practical quantum computing applications.

Overall, the project will provide a unique opportunity for the student to work at the intersection of quantum computing and compilation, gaining valuable insights into the challenges and opportunities within the field. By the end of the project, the student is expected to produce a comprehensive report detailing the developed compilation strategies, their impact on variational quantum circuits, and potential avenues for further research. This project will enhance the student's understanding of quantum computing compilers and contribute to the broader goal of making quantum algorithms more practical and scalable for real-world applications.

Potential skills gained: Fundamental knowledge of quantum computing and programming

Required qualifications or skills: Student should have Python knowledge

Direct mentor: Faculty/P.I.