Chan Hans Hon Sang, Fitzpatrick Nathan, Segarra-Martí Javier, Bearpark Michael J, Tew David P
Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, UK.
Cambridge Quantum Computing Ltd, 9a Bridge Street, Cambridge CB2 1UB, UK.
Phys Chem Chem Phys. 2021 Dec 1;23(46):26438-26450. doi: 10.1039/d1cp02227j.
electronic excited state calculations are necessary for the quantitative study of photochemical reactions, but their accurate computation on classical computers is plagued by prohibitive resource scaling. The Variational Quantum Deflation (VQD) is an extension of the quantum-classical Variational Quantum Eigensolver (VQE) algorithm for calculating electronic excited state energies, and has the potential to address some of these scaling challenges using quantum computers. However, quantum computers available in the near term can only support a limited number of quantum circuit operations, so reducing the quantum computational cost in VQD methods is critical to their realisation. In this work, we investigate the use of adaptive quantum circuit growth (ADAPT-VQE) in excited state VQD calculations, a strategy that has been successful previously in reducing the resources required for ground state energy VQE calculations. We also invoke spin restrictions to separate the recovery of eigenstates with different spin symmetry to reduce the number of calculations and accumulation of errors in computing excited states. We created a quantum eigensolver emulation package - Quantum Eigensolver Building on Achievements of Both quantum computing and quantum chemistry (QEBAB) - for testing the proposed adaptive procedure against two existing VQD methods that use fixed-length quantum circuits: UCCGSD-VQD and -UpCCGSD-VQD. For a lithium hydride test case we found that the spin-restricted adaptive growth variant of VQD uses the most compact circuits out of the tested methods by far, consistently recovers adequate electron correlation energy for different nuclear geometries and eigenstates while isolating the singlet and triplet manifold. This work is a further step towards developing techniques which improve the efficiency of hybrid quantum algorithms for excited state quantum chemistry, opening up the possibility of exploiting real quantum computers for electronic excited state calculations sooner than previously anticipated.
电子激发态计算对于光化学反应的定量研究是必要的,但在经典计算机上进行精确计算时,会受到资源扩展性过高的困扰。变分量子消去法(VQD)是用于计算电子激发态能量的量子 - 经典变分量子本征求解器(VQE)算法的扩展,有潜力利用量子计算机应对其中一些扩展性挑战。然而,近期可用的量子计算机仅能支持有限数量的量子电路操作,因此降低VQD方法中的量子计算成本对于其实现至关重要。在这项工作中,我们研究了在激发态VQD计算中使用自适应量子电路增长(ADAPT - VQE),这一策略先前在降低基态能量VQE计算所需资源方面已取得成功。我们还引入自旋限制来分离具有不同自旋对称性的本征态的恢复,以减少计算激发态时的计算次数和误差积累。我们创建了一个量子本征求解器仿真包——基于量子计算和量子化学成就构建的量子本征求解器(QEBAB)——用于针对两种使用固定长度量子电路的现有VQD方法:UCCGSD - VQD和 - UpCCGSD - VQD,测试所提出的自适应过程。对于氢化锂测试案例,我们发现VQD的自旋限制自适应增长变体在所有测试方法中使用的电路最为紧凑,能始终为不同核几何结构和本征态恢复足够的电子关联能,同时分离单重态和三重态流形。这项工作朝着开发提高激发态量子化学混合量子算法效率的技术又迈进了一步,为比先前预期更早地利用真实量子计算机进行电子激发态计算开辟了可能性。