no code implementations • 6 Oct 2022 • Hsin-Yuan Huang, Yu tong, Di Fang, Yuan Su
In contrast, the best previous algorithms, such as recent works using gradient-based optimization or polynomial interpolation, require a total evolution time of $\mathcal{O}(\epsilon^{-2})$ and $\mathcal{O}(\epsilon^{-2})$ experiments.
no code implementations • 7 May 2022 • Yuan Su, Zeyuan Wang, Yihua Cao
The corresponding control variables obtained locate in a reasonable control range, with a maximum power reduced of 13% at 100m/s, which showcases the potential of the Hybrid Trim strategy.
no code implementations • 15 Nov 2018 • Sheng Xu, Jian-Feng Zhang, Yi-Yan Wang, Lin-Lin Sun, Huan Wang, Yuan Su, Xiao-Yan Wang, Kai Liu, Tian-Long Xia
An electron-type quasi-2D Fermi surface is found by the angle-dependent Shubnikov-de Haas oscillations, de Haas-van Alphen oscillations and the first-principles calculations.
Materials Science Mesoscale and Nanoscale Physics
1 code implementation • 13 Mar 2018 • Yunseong Nam, Yuan Su, Dmitri Maslov
The ability to implement the Quantum Fourier Transform (QFT) efficiently on a quantum computer enables the advantages offered by a variety of fundamental quantum algorithms, such as those for integer factoring, computing discrete logarithm over Abelian groups, and phase estimation.
Quantum Physics Emerging Technologies
1 code implementation • 29 Nov 2017 • Andrew M. Childs, Dmitri Maslov, Yunseong Nam, Neil J. Ross, Yuan Su
With quantum computers of significant size now on the horizon, we should understand how to best exploit their initially limited abilities.
Quantum Physics
4 code implementations • 19 Oct 2017 • Yunseong Nam, Neil J. Ross, Yuan Su, Andrew M. Childs, Dmitri Maslov
We develop and implement automated methods for optimizing quantum circuits of the size and type expected in quantum computations that outperform classical computers.
Quantum Physics Emerging Technologies