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Science

Bulk Spin-Resonance Quantum Computation

Neil Gershenfeld, Isaac L. Chuang

Published Jan 17, 1997• 1,527 citations
Publisher

Abstract

Quantum computation remains an enormously appealing but elusive goal. It is appealing because of its potential to perform superfast algorithms, such as finding prime factors in polynomial time, but also elusive because of the difficulty of simultaneously manipulating quantum degrees of freedom while preventing environmentally induced decoherence. A new approach to quantum computing is introduced based on the use of multiple-pulse resonance techniques to manipulate the small deviation from equilibrium of the density matrix of a macroscopic ensemble so that it appears to be the density matrix of a much lower dimensional pure state. A complete prescription for quantum computing is given for such a system.

DOI
10.1126/science.275.5298.350

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Quantum computation remains an enormously appealing but elusive goal. It is appealing because of its potential to perform superfast algorithms, such as finding prime factors in polynomial time, but also elusive because of the difficulty of simultaneously manipulating quantum degrees of freedom while preventing environmentally induced decoherence. A new approach to quantum computing is introduced based on the use of multiple-pulse resonance techniques to manipulate the small deviation from equilibrium of the density matrix of a macroscopic ensemble so that it appears to be the density matrix of a much lower dimensional pure state. A complete prescription for quantum computing is given for such a system.
Certain difficult computational problems, such as finding prime factors, could be performed much faster if quantum computing, in which interactions of pure quantum states correspond to logical operations, could be realized in a practical manner. Most schemes implemented or proposed require isolating or controlling single atoms to maintain the coherence of quantum states. Gershenfeld and Chuang (p. 350; see the news story by Taubes, p. 307) propose a different approach in which the manipulation of nuclear spins in a chemical compound with nuclear magnetic resonance (NMR) methods performs quantum computation. Such an approach might seem improbable in that the nuclear spins of a bulk sample form a statistical ensemble that would rapidly undergo decoherence. However, the authors show that the deviation from the equilibrium spin states can be manipulated so that it acts like a pure, low-dimensional quantum state.
We show that quantum computation is possible with mixed states instead of pure states as inputs. This is performed by embedding within the mixed state a subspace that transforms like a pure state and that can be identified by labelling it based on logical (spin), temporal, or spatial degrees of freedom. This permits quantum computation to be realized with bulk ensembles far from the ground state. Experimental results are presented for quantum gates and circuits implemented with liquid nuclear magnetic resonance techniques and verified by quantum state tomography.
In bulk quantum computation one can manipulate a large number of indistinguishable quantum computers by parallel unitary operations and measure expectation values of certain observables with limited sensitivity. The initial state of each computer in the ensemble is known but not pure. Methods for obtaining effective pure input states by a series of manipulations have been described by Gershenfeld and Chuang (logical labeling) [Science 275, 350 (1997)] and Cory et al. (spatial averaging) [Proc. Natl. Acad. Sci. USA 94, 1634 (1997)] for the case of quantum computation with nuclear magnetic resonance. We give a different technique called temporal averaging. This method is based on classical randomization, requires no ancilla quantum bits, and can be implemented in nuclear magnetic resonance without using gradient fields. We introduce several temporal averaging algorithms suitable for both high-temperature and low-temperature bulk quantum computing and analyze the signal-to-noise behavior of each. Most of these algorithms require only a constant multiple of the number of experiments needed by the other methods for creating effective pure states.
Quantum algorithms for problems such as integer factorization and database search have spurred great interest in quantum computation. However, the construction of scalable quantum computers has proved to be extremely difficult. Among the challenging requirements that must be fulfilled in the “standard model” of quantum computation, one must be able to initialize qubits into known pure states. In addition, quantum computers must be protected from noise due to unwanted interactions with their environment. This work is concerned with two theoretical issues motivated by these difficulties. First, I analyze the efficiency of an algorithm for an alternate model for quantum computation that is motivated by bulk nuclear magnetic resonance. In such ensemble systems, the initial state is not a fiducial pure state, but is instead a maximally-mixed density operator. The algorithm that I consider allows one to estimate the free energy of arbitrary spin-1/2 lattice models. To determine the efficiency of this algorithm, I calculate the computation time required to estimate the free energy to bounded error as a function of the lattice size. In the absence of stochastic fluctuations in the measurement output, it is found that the algorithm is efficient. However, evidence is presented that suggests that the algorithm becomes exponentially sensitive to fluctuations as the lattice size increases. While techniques such as quantum error-correcting codes and decoherence-free subsystem encodings have been devised to mitigate errors due to unwanted environmental couplings, these methods require many additional qubits or complicated encodings. Here, I investigate a simple approach to reduce errors in the quantum search algorithm due to a collective decoherence model. This method takes advantage of the freedom inherent in compiling the search algorithm into fundamental gates. Transition rate calculations and more rigorous quantum master equation simulations are carried out for small-qubit instances to contrast the performance of the original and modified algorithm. It is shown that the expected computational effort can be reduced by 22% for selected five-bit instances of the quantum search algorithm. While this approach does not constitute a general strategy for quantum error-correction, it illustrates the importance of judicious gate design in mitigating decoherence.