ArticleJournal of chemical theory and computation2022
Localized Quantum Chemistry on Quantum Computers.
Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Localized sample-based quantum diagonalization for strongly correlated chemistry.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Quantum-classical hybrid computation of electron transfer in a cryptochrome proteinChemical science · 2026Article
- Thermal Weight Determination and Interstate Coupling in State-Averaged ADAPT-VQE.Journal of chemical theory and computation · 2025Article
- FragPT2: Multifragment Wave Function Embedding with Perturbative Interactions.Journal of chemical theory and computation · 2025Article
- 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
- DFT and TD-DFT study of hydrogen bonded complexes of aspartic acid and n water (n = 1 and 2).Journal of molecular modeling · 2023Article
- Perspective on the Current State-of-the-Art of Quantum Computing for Drug Discovery Applications.Journal of chemical theory and computation · 2022Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantum chemistry calculations of large, strongly correlated systems are typically limited by the computation cost that scales exponentially with the size of the system. Quantum algorithms, designed specifically for quantum computers, can alleviate this, but the resources required are still too large for today's quantum devices. Here, we present a quantum algorithm that combines a localization of multireference wave functions of chemical systems with quantum phase estimation (QPE) and variational unitary coupled cluster singles and doubles (UCCSD) to compute their ground-state energy. Our algorithm, termed "local active space unitary coupled cluster" (LAS-UCC), scales linearly with the system size for certain geometries, providing a polynomial reduction in the total number of gates compared with QPE, while providing accuracy above that of the variational quantum eigensolver using the UCCSD ansatz and also above that of the classical local active space self-consistent field. The accuracy of LAS-UCC is demonstrated by dissociating (H
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