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20052026
most citedBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

24.4k citations

Showing 2020 · quant-phShow all

5 papers · 2 filters

quant-ph20202 cited

Quantum block lookahead adders and the wait for magic states

Craig Gidney

We improve the Toffoli count of low depth quantum adders, and analyze how their spacetime cost reacts to having a limited number of magic state factories. We present a block lookah…

quant-ph2020149 cited

Microwaves in Quantum Computing

Joseph C. Bardin, Daniel H. Slichter, David J. Reilly

Quantum information processing systems rely on a broad range of microwave technologies and have spurred development of microwave devices and methods in new operating regimes. Here…

quant-ph2020148 cited

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…

quant-ph202024 cited

The Snake Optimizer for Learning Quantum Processor Control Parameters

Paul V. Klimov, Julian Kelly, John M. Martinis +1

High performance quantum computing requires a calibration system that learns optimal control parameters much faster than system drift. In some cases, the learning procedure require…

quant-ph202013 cited

Investigating Quantum Approximate Optimization Algorithms under Bang-bang Protocols

Daniel Liang, Li Li, Stefan Leichenauer

The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices. We analyze the algorithm as a bang-bang…