Fakultät Physik, Technische Universität Dortmund, D-44221 Dortmund, Germany.
Phys Rev Lett. 2011 Dec 2;107(23):230501. doi: 10.1103/PhysRevLett.107.230501. Epub 2011 Nov 30.
Decoherence is one of the most important obstacles that must be overcome in quantum information processing. It depends on the qubit-environment coupling strength, but also on the spectral composition of the noise generated by the environment. If the spectral density is known, fighting the effect of decoherence can be made more effective. Applying sequences of inversion pulses to the qubit system, we developed a method for dynamical decoupling noise spectroscopy. We generate effective filter functions that probe the environmental spectral density without requiring assumptions about its shape. Comparing different pulse sequences, we recover the complete spectral density function and distinguish different contributions to the overall decoherence.
退相干是量子信息处理中必须克服的最重要障碍之一。它不仅取决于量子位与环境的耦合强度,还取决于环境产生的噪声的光谱组成。如果知道了光谱密度,就可以更有效地对抗退相干的影响。我们通过对量子位系统应用反转脉冲序列,开发了一种动态去耦噪声光谱学方法。我们生成有效的滤波器函数来探测环境的光谱密度,而无需对其形状做出假设。通过比较不同的脉冲序列,我们恢复了完整的光谱密度函数,并区分了对整体退相干的不同贡献。