Solid-state multiple quantum NMR in quantum information processing: exactly solvable models

Serge I. Doronin, Edward B. Fel’dman, I. D. Lazarev

Edward B. Fel’dman, Alexey N. Pyrkov, Alexander Ivanovich Zenchuk

Multiple quantum (MQ) NMR is an effective tool for the generation of a large cluster of correlated particles, which, in turn, represent a basis for quantum information processing devices. Studying the available exactly solvable models clarifies many aspects of the quantum information. In this study, we consider two exactly solvable models in the MQ NMR experiment: (i) the isolated system of two spin-1/2 particles (dimers) and (ii) the large system of equivalent spin-1/2 particles in a nanopore. The former model is used to describe the quantum correlations and their relations with the MQ NMR coherences, whereas the latter helps one to model the creation and decay of large clusters of correlated particles.

T. S. Mahesh

Ivan S. Oliveira, Tito José Bonagamba, Roberto S. Sarthour +2 more

Garett M. Leskowitz, Nima Ghaderi, Ryan A. Olsen +1 more

We report the first implementation of NMR quantum information processing in a static single-crystal solid, illustrating pseudopure state preparation and gate manipulations on a three-qubit system, U–13C2, N15-glycine (H215N13CH213COOH). We consider issues important to single-crystal NMR implementations of quantum information processing and introduce several innovations specific to such implementations. In particular, concurrent cross-polarization of both the C13 and N15 spins from proton magnetization enhances and equalizes populations on these nuclei in a single step. This multiple cross-polarization step simplifies preparation of pseudopure spin states relative to previously described multiple-pulse sequences. Also, proton decoupling, which prolongs coherence during spin-evolution and detection periods, is switched off to dephase unwanted coherences during preparation of pseudopure spin states. Such “relaxation averaging” (or T2 averaging) is an alternative to spatial averaging, which requires special hardware and large gradient strengths for small crystals.

Chandrasekhar Ramanathan, Nicolas Boulant, Zhiying Chen +3 more