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arXiv · 1411.4641

Algorithmic Cooling in Liquid State NMR

Yosi Atia·Yuval Elias·Tal Mor·Yossi Weinstein
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Abstract

Algorithmic cooling is a method that employs thermalization to increase qubit purification level, namely it reduces the qubit-system's entropy. We utilized gradient ascent pulse engineering (GRAPE), an optimal control algorithm, to implement algorithmic cooling in liquid state nuclear magnetic resonance. Various cooling algorithms were applied onto the three qubits of $^{13}$C$_2$-trichloroethylene, cooling the system beyond Shannon's entropy bound in several different ways. In particular, in one experiment a carbon qubit was cooled by a factor of 4.61. This work is a step towards potentially integrating tools of NMR quantum computing into in vivo magnetic resonance spectroscopy.

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Yosi Atia, Yuval Elias, Tal Mor, Yossi Weinstein. 2015-11-08. Algorithmic Cooling in Liquid State NMR. https://doi.org/10.1103/physreva.93.012325

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