ArticleChemical science2022
Toward practical quantum embedding simulation of realistic chemical systems on near-term quantum computers.
Article in Chemical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Molecular Quantum Computations on a Protein.Journal of chemical theory and computation · 2026Article
- Quantum-classical hybrid computation of electron transfer in a cryptochrome proteinChemical science · 2026Article
- Harnessing Quantum Computing for Energy Materials: Opportunities and Challenges.ACS energy letters · 2026Review
- Improving the Runtime of Quantum Phase Estimation for Chemistry through Basis Set Optimization.Journal of chemical theory and computation · 2025Article
- How Well Can Quantum Embedding Method Predict the Reaction Profiles for Hydrogenation of Small Li Clusters?Nanomaterials (Basel, Switzerland) · 2024Article
- A hybrid quantum computing pipeline for real world drug discovery.Scientific reports · 2024Article
- A general framework for active space embedding methods with applications in quantum computing.npj computational materials · 2024Article
- Aromaticity Reversal Induced by Vibrations in Cyclo[16]carbon.Journal of the American Chemical Society · 2023Article
- Effective Reconstruction of Expectation Values from Ab Initio Quantum Embedding.Journal of chemical theory and computation · 2023Article
- Multiscale quantum algorithms for quantum chemistry.Chemical science · 2023Article
- Towards practical and massively parallel quantum computing emulation for quantum chemistry.NPJ quantum information · 2023Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantum computing has recently exhibited great potential in predicting chemical properties for various applications in drug discovery, material design, and catalyst optimization. Progress has been made in simulating small molecules, such as LiH and hydrogen chains of up to 12 qubits, by using quantum algorithms such as variational quantum eigensolver (VQE). Yet, originating from the limitations of the size and the fidelity of near-term quantum hardware, the accurate simulation of large realistic molecules remains a challenge. Here, integrating an adaptive energy sorting strategy and a classical computational method-the density matrix embedding theory, which respectively reduces the circuit depth and the problem size, we present a means to circumvent the limitations and demonstrate the potential of near-term quantum computers toward solving real chemical problems. We numerically test the method for the hydrogenation reaction of C
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