Toward Practical Quantum Embedding Simulation of Realistic Chemical Systems on Near-term Quantum Computers

Modelling Carbon Capture on Metal-Organic Frameworks with Quantum Computing

“…However, despite these previous works 40 , our results show that the predicted dissociation behavior is highly dependent on the adopted fragmentation strategy. While quantitative differences between different DMET fragmentations of the same system have been reported recently 41,46 , our work shows that different fragmentations can result in qualitative differences in the predicted behavior of the total system, even leading to differing predictions as to whether a chemical complex is bound or unbound.…”

“…To go a step further, we investigate consequences of using the 1-shot version of DMET, where a global chemical potential µ global is optimised such that the sum of fragment electron numbers matches the total number of electrons of the system, with no other parameters in the cost function of the DMET algorithm (details provided in Supplementary Information). While such an approach leads to less variational flexibility, it benefits from higher efficiency and is commonly used in quantum computational applications [46][47][48] . Since the 1-shot DMET algorithm attempts to optimise a single global chemical potential, it stands to reason that unphysical dissociation in Fig.…”

Efficient quantum imaginary time evolution by drifting real time evolution: an approach with low gate and measurement complexity

“…For example, it can provide a trial state or an initial state in other quantum algorithms, such as in the auxiliary-field quantum Monte Carlo [39], ground and excited states preparation [40][41][42], dynamics simulation [43,44], etc. It can also be treated as a quantum solver in the quantum embedding theory, such as density matrix embedding theory [45][46][47][48], hybrid quantumclassical tensor networks [49], etc.…”

The Variational Quantum Eigensolver: a review of methods and best practices

“…Integration of DMET with a VQE for the correlated subspace solver has been the subject of several publications [620][621][622][623][624], and has been implemented on quantum computers with proof of principles for relevant applications such as protein-ligand interactions for drug design [122] (with an alternative method based on perturbation theory proposed in Ref. [121]).…”