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The Japan Society of Applied Physics

Improvements of quantum chemical calculations with quantum computers

Takumi Kato, Koji Okuwaki, Yuji Mochizuki, Kenji Sugisaki, Yuichiro Minato

Published Jul 10, 2019• 0 citations
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Easy and effective usage of computational resources is crucial for scientific calculations. Following our recent work of machine-learning (ML) assisted scheduling optimization [J. Comput. Chem. 2023, 44, 1174], we further propose (1) the improved ML models for the better predictions of computational loads, and as such, more elaborate load-balancing calculations can be expected; (2) the idea of coded computation, that is, the integration of gradient coding, in order to introduce fault tolerance during the distributed calculations; and (3) their applications together with re-normalized exciton model with time-dependent density functional theory (REM-TDDFT) for calculating the excited states. Illustrated benchmark calculations include P38 protein, and solvent model with one or several excitable centers. The results show that the improved ML-assisted coded calculations can further improve the load-balancing and cluster utilization, owing primarily profit in fault tolerance that aims at the automated quantum chemical calculations for both ground and excited states.
Circuit depth reduction is of critical importance for quantum chemistry simulations on current and near term quantum computers. This issue is tackled by introducing a chemically aware strategy for the unitary coupled cluster ansatz. The objective is to use the chemical description of a system to aid in the synthesis of a quantum circuit. We combine this approach with two flavors of symmetry verification for the reduction of experimental noise. These methods enable the use of Quantinuum's System Model H1 ion trap quantum computer for a 6-qubit quantum subspace expansion calculation. We present (i) calculations to obtain methane's optical spectra; (ii) an atmospheric gas reaction simulation involving [CH3⋅-H-OH]‡. Using our chemically aware unitary coupled cluster state-preparation strategy in tandem with state of the art symmetry verification methods, we improve device yield for CH4 at 6 qubits. This is demonstrated by a 90% improvement in two-qubit gate count and a reduction in relative error to 0.2% for electronic energy calculated on System Model H1.
A major milestone of quantum error correction is to achieve the fault-tolerance threshold beyond which quantum computers can be made arbitrarily accurate. This requires extraordinary resources and engineering efforts. We show that, even without achieving full fault tolerance, quantum error detection is already useful on the current generation of quantum hardware. We demonstrate this experimentally by executing an end-to-end chemical calculation for the hydrogen molecule encoded in the [[4, 2, 2]] quantum error-detecting code. The encoded calculation with logical qubits significantly improves the accuracy of the molecular ground-state energy.