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arXiv 2404.18878quant-phcond-mat.str-elphysics.chem-ph

自旋耦合即所需:在量子计算机上编码分子中的强电子关联

Spin coupling is all you need: Encoding strong electron correlation in molecules on quantum computers

Daniel Marti-Dafcik, Hugh G. A. Burton, David P. Tew

AI总结:

本文提出在量子计算机上通过自旋耦合初始态直接编码强关联分子系统的纠缠结构,避免指数级行列式开销,并提供高效制备电路,显著降低量子相位估计等算法的运行时间,为可扩展量子模拟奠定关键基础。

摘要:

量子算法求解特征值问题(如计算哈密顿量谱)的性能强烈依赖于初始波函数与目标特征向量的重叠。在斯莱特行列式基组中,包含$N$个强关联电子的系统其能量本征态的表示所需行列式数量随$N$呈指数增长。在经典处理器上,这限制了模拟仅限于$N$较小的系统。在此,我们证明量子计算机能够通过直接以自旋耦合初始态的形式编码主导纠缠结构,从而高效模拟强关联分子系统。这避免了昂贵的经典或量子态制备启发式方法,转而利用波函数中的对称性。我们提供了量子电路,用于确定性制备一族自旋本征函数,其包含${N \choose N/2}$个斯莱特行列式,电路深度为$\mathcal{O}(N)$,并使用$\mathcal{O}(N^2)$个局部门。将它们用作量子算法中高度纠缠的初始态,可将量子相位估计及相关容错方法的总运行时间减少数个数量级。此外,我们评估了将自旋耦合波函数作为若干启发式量子算法的初始态的应用,包括变分量子本征求解器、绝热态制备以及不同版本的量子子空间对角化(QSD),包括基于实时演化态的QSD。我们还提出了一种新颖的QSD算法,该算法利用通过自适应量子本征求解器获得的状态。对于所有算法,我们证明了使用自旋耦合初始态能大幅减少模拟强关联基态和激发态所需的量子资源。我们的工作为经典计算上具有挑战性的电子系统的可扩展量子模拟提供了关键组成部分。

英文摘要:

The performance of quantum algorithms for eigenvalue problems, such as computing Hamiltonian spectra, depends strongly on the overlap of the initial wavefunction and the target eigenvector. In a basis of Slater determinants, the representation of energy eigenstates of systems with $N$ strongly correlated electrons requires a number of determinants that scales exponentially with $N$. On classical processors, this restricts simulations to systems where $N$ is small. Here, we show that quantum computers can efficiently simulate strongly correlated molecular systems by directly encoding the dominant entanglement structure in the form of spin-coupled initial states. This avoids resorting to expensive classical or quantum state preparation heuristics and instead exploits symmetries in the wavefunction. We provide quantum circuits for deterministic preparation of a family of spin eigenfunctions with ${N \choose N/2}$ Slater determinants with depth $\mathcal{O}(N)$ and $\mathcal{O}(N^2)$ local gates. Their use as highly entangled initial states in quantum algorithms reduces the total runtime of quantum phase estimation and related fault-tolerant methods by orders of magnitude. Furthermore, we assess the application of spin-coupled wavefunctions as initial states for several heuristic quantum algorithms, namely the variational quantum eigensolver, adiabatic state preparation, and different versions of quantum subspace diagonalization (QSD) including QSD based on real-time-evolved states. We also propose a novel QSD algorithm that exploits states obtained through adaptive quantum eigensolvers. For all algorithms, we demonstrate that using spin-coupled initial states drastically reduces the quantum resources required to simulate strongly correlated ground and excited states. Our work provides a crucial component for enabling scalable quantum simulation of classically challenging electronic systems.

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