Talk accepted by QCTiP 2024!

Paper on reversing unknown quantum processes is selected for talk in QCTiP 2024 🎉

Our paper Reversing Unknown Quantum Processes via Virtual Combs: for Channels with Limited Information by Chengkai Zhu, Yin Mo, Yu-Ao Chen, and Xin Wang was selected for a talk at QCTiP 2024!

For QCTiP 2024: The third Quantum Computing Theory in Practice (QCTiP) conference, hosted by the Quantum Software Lab and the University of Edinburgh from the 16th-18th April, 2024. Building on the success of the previous Heilbronn quantum algorithms meetings (2010-2019) held in Bristol and Cambridge, QCTiP serves as a platform for fostering discussions among theorists and practitioners in the field of quantum computing.

For the paper Reversing Unknown Quantum Processes via Virtual Combs: for Channels with Limited Information: We introduce the notion of virtual combs by lifting the positivity requirement on quantum combs. Physically, a virtual comb corresponds to sampling quantum combs with positive and negative coefficients and performing post-processing. We find that the simulation of the inverse of an unknown channel could be achieved with a virtual comb under certain conditions. For depolarizing channels, we unveil the remarkable capability of an $n$-slot virtual comb to exactly reverse a depolarizing channel with an unknown noise parameter among $n+1$ possible candidates. A worst-case error decay of $\mathcal{O}(n^{-1})$ is unveiled for depolarizing channels within a specified noise region. Moreover, we show that virtual combs can universally reverse unitary operations and investigate the trade-off between the slot number and the sampling overhead.

Chengkai Zhu
Chengkai Zhu
PhD Student

I obtained my BS in Applied Mathematics from China Agricultural University under the supervision of Prof. Zhencai Shen. I obtained my MS degree in Cyberspace Security from University of Chinese Academy of Sciences under the supervision of Prof. Zhenyu Huang. My research interests include quantum information theory and quantum computation.