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Proceedings Paper

Optimization of algorithmic cooling for NMR quantum computers
Author(s): Alexei Kaltchenko
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Paper Abstract

To achieve scalability of NMR computers, one needs a large number of highly polarized spins in liquid nuclearspin systems at finite temperature. In quantum computing terminology, such spin-half states are (almost) pure qubit states. Producing highly polarized spins (almost pure qubit states) out of non-polarized spins (non-pure qubit states) is sometimes called "purification". From a thermodynamic point of view, purification can be viewed as cooling spins to a very low temperature. In this work, we study how classical data compression codes can be used to design cooling algorithms for both short and long molecules. We argue that so designed cooling (purification) algorithms potentially outperform other methods in terms of the closeness of the output state to the ideal pure state, which in turn implies lower output temperature. We also analyze how the mismatch of the algorithm's computational basis and the actual eigenbasis of the spins' density matrix will affect the cooling (purification) performance.

Paper Details

Date Published: 25 April 2007
PDF: 7 pages
Proc. SPIE 6573, Quantum Information and Computation V, 657309 (25 April 2007); doi: 10.1117/12.720147
Show Author Affiliations
Alexei Kaltchenko, Wilfrid Laurier Univ. (Canada)

Published in SPIE Proceedings Vol. 6573:
Quantum Information and Computation V
Eric J. Donkor; Andrew R. Pirich; Howard E. Brandt, Editor(s)

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