论文标题
用于量子计算的动力自我能量映射（DSEM）
Dynamical Self-energy Mapping (DSEM) for quantum computing
论文作者
论文摘要
对于嘈杂的中间尺度量子（NISQ）设备，只有一个中等数量的具有有限连贯性的Qubits，因此仅启用浅电路和当前执行的量子计算中的几个时间演变步骤。在这里，我们介绍了如何通过使用经典的Quantum-Quantum杂种算法在NISQ设备上绕过这一挑战，使我们能够产生稀疏的哈密顿量，该稀疏的哈密顿式仅包含$ \ nathcal {o}（o}（o）（n^2）$在高斯节上与$ \ Mathian相比，n Stresande ham canterian $ \ ntartial n Stratemian^o^o^o^4}（^4） $ n $是系统中的轨道数量。这种混合动力的经典部分需要稀疏，虚拟的哈密顿量的参数化，以使其恢复原始分子系统的自我能源。然后，量子机使用这种虚拟的哈密顿量来计算系统的自我能源。我们表明，与涉及全汉密尔顿的模拟相比，开发的混合算法对于小分子测试用例可产生非常好的总能量，同时将量子回路的深度降低至少一个数量级。
For noisy intermediate-scale quantum (NISQ) devices only a moderate number of qubits with a limited coherence is available thus enabling only shallow circuits and a few time evolution steps in the currently performed quantum computations. Here, we present how to bypass this challenge in practical molecular chemistry simulations on NISQ devices by employing a classical-quantum hybrid algorithm allowing us to produce a sparse Hamiltonian which contains only $\mathcal{O}(n^2)$ terms in a Gaussian orbital basis when compared to the $\mathcal{O}(n^4)$ terms of a standard Hamiltonian, where $n$ is the number of orbitals in the system. Classical part of this hybrid entails parameterization of the sparse, fictitious Hamiltonian in such a way that it recovers the self-energy of the original molecular system. Quantum machine then uses this fictitious Hamiltonian to calculate the self-energy of the system. We show that the developed hybrid algorithm yields very good total energies for small molecular test cases while reducing the depth of the quantum circuit by at least an order of magnitude when compared with simulations involving a full Hamiltonian.
