近日，奥地利因斯布鲁克大学的P.Zoller及其研究小组取得一项新进展。经过不懈努力，他们用可编程中性原子阵列进行费米子量子处理。相关研究成果已于2023年8月22日在国际知名学术期刊《美国科学院院刊》上发表。
在这项工作中，研究人员提出了一个费米子量子处理器，其中费米子模型在费米子寄存器中进行局部编码，并使用费米子门以硬件效率的方式进行模拟。他们特别考虑了可编程镊子阵列中的费米原子，并开发了不同的协议来实现非局域门，保证了硬件层面的费米统计。他们使用这个门集，连同里德伯介导的相互作用门，为数字和变分量子模拟算法找到有效的电路分解，并给出了分子能量估计的图示。
最后，他们考虑了一个联合费米-量子比特架构，其中原子的运动自由度和内部自由度都被利用来，有效地实现量子相位估计以及模拟晶格规范理论动力学。
据悉，模拟多体费米子系统的性质是与材料科学、量子化学和粒子物理相关的一个突出的计算挑战。尽管基于量子比特的量子计算机可能比传统设备更有效地解决这个问题，但编码非局部费米子统计会带来所需资源的开销，限制了它们在近期架构中的适用性。
附：英文原文
Title: Fermionic quantum processing with programmable neutral atom arrays
Author: González-Cuadra, D., Bluvstein, D., Kalinowski, M., Kaubruegger, R., Maskara, N., Naldesi, P., Zache, T. V., Kaufman, A. M., Lukin, M. D., Pichler, H., Vermersch, B., Ye, Jun, Zoller, P.
Issue&Volume: 2023-8-22
Abstract: Simulating the properties of many-body fermionic systems is an outstanding computational challenge relevant to material science, quantum chemistry, and particle physics.Although qubit-based quantum computers can potentially tackle this problem more efficiently than classical devices, encoding nonlocal fermionic statistics introduces an overhead in the required resources, limiting their applicability on near-term architectures. In this work, we present a fermionic quantum processor, where fermionic models are locally encoded in a fermionic register and simulated in a hardware-efficient manner using fermionic gates. We consider in particular fermionic atoms in programmable tweezer arrays and develop different protocols to implement nonlocal gates, guaranteeing Fermi statistics at the hardware level. We use this gate set, together with Rydberg-mediated interaction gates, to find efficient circuit decompositions for digital and variational quantum simulation algorithms, illustrated here for molecular energy estimation. Finally, we consider a combined fermion-qubit architecture, where both the motional and internal degrees of freedom of the atoms are harnessed to efficiently implement quantum phase estimation as well as to simulate lattice gauge theory dynamics.
DOI: 10.1073/pnas.2304294120
Source: https://www.pnas.org/doi/10.1073/pnas.2304294120