activity
19962023
most citedQuantum Machine Learning

4.7k citations · 53.3k across the 233 of their papers we have counts for

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Showing 2004Show all

16 papers · 1 filter

cond-mat.mes-hall2004★ 1 cited

Bang-Bang refocusing of a qubit exposed to telegraph noise

H. Gutmann, F. K. Wilhelm, W. M. Kaminsky +1

We investigate the decoherence effect of telegraph noise on a single qubit, usually provoked by bistable fluctuators. To diminish the dephasing and relaxation impact an effective r…

quant-ph2004★ 3.1k cited

Quantum-enhanced measurements: beating the standard quantum limit

Vittorio Giovannetti, Seth Lloyd, Lorenzo Maccone

Quantum mechanics, through the Heisenberg uncertainty principle, imposes limits to the precision of measurement. Conventional measurement techniques typically fail to reach these l…

quant-ph2004★ 98 cited

Entanglement Assisted Metrology

Paola Cappellaro, Joseph Emerson, Nicolas Boulant +3

We propose a new approach to the measurement of a single spin state, based on nuclear magnetic resonance (NMR) techniques and inspired by the coherent control over many-body system…

quant-ph2004★ 234 cited

Random Quantum Circuits and Pseudo-Random Operators: Theory and Applications

Joseph Emerson

Pseudo-random operators consist of sets of operators that exhibit many of the important statistical features of uniformly distributed random operators. Such pseudo-random sets of o…

quant-ph2004★ 17 cited

Conditions for the multiplicativity of maximal l_p-norms of channels for fixed integer p

Vittorio Giovannetti, Seth Lloyd, Mary Beth Ruskai

We introduce a condition for memoryless quantum channels which, when satisfied guarantees the multiplicativity of the maximal l_p-norm with p a fixed integer. By applying the condi…

quant-ph2004★ 179 cited

Quantum Process Tomography of the Quantum Fourier Transform

Yaakov S. Weinstein, Timothy F. Havel, Joseph Emerson +4

The results of quantum process tomography on a three-qubit nuclear magnetic resonance quantum information processor are presented, and shown to be consistent with a detailed model…