[1] Kaye, R., Laflamme, R., & Mosca, M. (2007). An Introduction to Quantum Computing. Oxford University Press.
[2] Barenco, A., et al. (1995). "Elementary gates for quantum computation." Physical Review A, 52(5), 3457.
[3] Amy, M., Maslov, D., & Mosca, M. (2013). "Polynomial-time T-depth optimization of Clifford+T circuits via matroid partitioning." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 32(6), 818–830.
[4] Shende, V. V., Bullock, S. S., & Markov, I. L. (2006). "Synthesis of quantum logic circuits." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 25(6), 1000–1010.
[5] Gottesman, D. (1997). "Stabilizer codes and quantum error correction." PhD Thesis, California Institute of Technology.
[6] Qiskit Textbook. (2023). Learn Quantum Computation Using Qiskit. Online resource.
Quantum circuit optimization
| Language of instruction | angličtina, čeština |
|---|---|
| Code | 9600-1036 |
| Abbreviation | OKO |
| Course title | Quantum circuit optimization |
| Coordinating department | IT4Innovations |
| Course coordinator | prof. RNDr. Marek Lampart, Ph.D. |
Anotace
Quantum Circuit Optimization is a key course that enables students to understand and apply the principles of optimizing quantum algorithms and circuits. The course is designed to provide both a theoretical foundation in the design and analysis of quantum circuits and practical skills in circuit optimization, focusing on minimizing depth, gate count, and other parameters crucial for efficient implementation on real quantum devices. Emphasis is placed on the use of modern tools and algorithms, such as QAOA, variational quantum algorithms, and optimization techniques integrated into quantum compilers. The course is oriented toward practical applications in designing optimized circuits using platforms like Qiskit or Cirq and covers a wide range of topics from basic circuit synthesis to the implementation of complex error-correction-compatible algorithms. This course is designed for master's students interested in quantum informatics who already have foundational knowledge of quantum algorithms and programming.
Povinná literatura
Doporučená literatura
[1] Nielsen, M. A. (1998). Quantum Information Theory (Doctoral dissertation, The University of New Mexico).
[2] Farhi, E., Goldstone, J., & Gutmann, S. (2014). "A quantum approximate optimization algorithm." arXiv preprint arXiv:1411.4028.
[3] McClean, J. R., et al. (2016). "The theory of variational hybrid quantum-classical algorithms." New Journal of Physics, 18(2), 023023.
[2] Farhi, E., Goldstone, J., & Gutmann, S. (2014). "A quantum approximate optimization algorithm." arXiv preprint arXiv:1411.4028.
[3] McClean, J. R., et al. (2016). "The theory of variational hybrid quantum-classical algorithms." New Journal of Physics, 18(2), 023023.