7.2k citations · 7.4k across the 5 of their papers we have counts for
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ORQVIZ: Visualizing High-Dimensional Landscapes in Variational Quantum Algorithms
Manuel S. Rudolph, Sukin Sim, Asad Raza +5
Variational Quantum Algorithms (VQAs) are promising candidates for finding practical applications of near to mid-term quantum computers. There has been an increasing effort to stud…
What the foundations of quantum computer science teach us about chemistry
Jarrod R. McClean, Nicholas C. Rubin, Joonho Lee +5
With the rapid development of quantum technology, one of the leading applications is the simulation of chemistry. Interestingly, even before full scale quantum computers are availa…
Variational Quantum Algorithms
M. Cerezo, Andrew Arrasmith, Ryan Babbush +8
Applications such as simulating complicated quantum systems or solving large-scale linear algebra problems are very challenging for classical computers due to the extremely high co…
Accurately computing electronic properties of a quantum ring
C. Neill, T. McCourt, X. Mi +89
A promising approach to study condensed-matter systems is to simulate them on an engineered quantum platform. However, achieving the accuracy needed to outperform classical methods…
Focus beyond quadratic speedups for error-corrected quantum advantage
Ryan Babbush, Jarrod McClean, Michael Newman +3
In this perspective, we discuss conditions under which it would be possible for a modest fault-tolerant quantum computer to realize a runtime advantage by executing a quantum algor…
Power of data in quantum machine learning
Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni +4
The use of quantum computing for machine learning is among the most exciting prospective applications of quantum technologies. However, machine learning tasks where data is provide…