Dahlem Center for Complex Quantum Systems, Freie Universität Berlin, D-14195 Berlin, Germany.
Institute for Theoretical Physics, University of Cologne, D-50937 Cologne, Germany.
Nat Commun. 2017 May 17;8:15305. doi: 10.1038/ncomms15305.
Well-controlled quantum devices with their increasing system size face a new roadblock hindering further development of quantum technologies. The effort of quantum tomography-the reconstruction of states and processes of a quantum device-scales unfavourably: state-of-the-art systems can no longer be characterized. Quantum compressed sensing mitigates this problem by reconstructing states from incomplete data. Here we present an experimental implementation of compressed tomography of a seven-qubit system-a topological colour code prepared in a trapped ion architecture. We are in the highly incomplete-127 Pauli basis measurement settings-and highly noisy-100 repetitions each-regime. Originally, compressed sensing was advocated for states with few non-zero eigenvalues. We argue that low-rank estimates are appropriate in general since statistical noise enables reliable reconstruction of only the leading eigenvectors. The remaining eigenvectors behave consistently with a random-matrix model that carries no information about the true state.
具有良好控制的量子设备及其不断增加的系统规模面临着一个新的障碍,阻碍了量子技术的进一步发展。量子层析术——量子设备状态和过程的重建——的努力进展不顺利:最先进的系统不再能够被描述。量子压缩感知通过从不完全数据中重建状态来缓解这个问题。在这里,我们展示了一种七量子比特系统的压缩层析实验实现——一种在囚禁离子结构中制备的拓扑颜色码。我们处于高度不完全的-127 个 Pauli 基测量设置和高度嘈杂的-100 次重复每个-状态。最初,压缩感知被提倡用于具有少数非零特征值的状态。我们认为,低秩估计通常是合适的,因为统计噪声只能可靠地重建主导特征向量。其余的特征向量与一个随机矩阵模型一致,该模型不携带关于真实状态的信息。