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Towards quantum-centric simulations of extended molecules: sample-based quantum diagonalization enhanced with density matrix embedding theory

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arxiv 2411.09861 v2 pith:4NLKHXJB submitted 2024-11-15 quant-ph

classification quant-ph
keywords quantumsimulationscalculationscomputingembeddingmoleculesaccuratelyactive
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Computing ground-state properties of molecules is a promising application for quantum computers operating in concert with classical high-performance computing resources. Quantum embedding methods are a family of algorithms particularly suited to these computational platforms: they combine high-level calculations on active regions of a molecule with low-level calculations on the surrounding environment, thereby avoiding expensive high-level full-molecule calculations and allowing to distribute computational cost across multiple and heterogeneous computing units. Here, we present the first density matrix embedding theory (DMET) simulations performed in combination with the sample-based quantum diagonalization (SQD) method. We employ the DMET-SQD formalism to compute the ground-state energy of a ring of 18 hydrogen atoms, and the relative energies of the chair, half-chair, twist-boat, and boat conformers of cyclohexane. The full-molecule 41- and 89-qubit simulations are decomposed into 27- and 32-qubit active-region simulations, that we carry out on the ibm_cleveland device, obtaining results in agreement with reference classical methods. Our DMET-SQD calculations mark a tangible progress in the size of active regions that can be accurately tackled by near-term quantum computers, and are an early demonstration of the potential for quantum-centric simulations to accurately treat the electronic structure of large molecules, with the ultimate goal of tackling systems such as peptides and proteins.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Quantum Simulation of Ligand-like Molecules through Sample-based Quantum Diagonalization in Density Matrix Embedding Framework

    quant-ph 2025-11 unverdicted novelty 6.0 of 10

    Using DMET to fragment molecules and SQD to solve the fragments on IBM hardware, the authors report ground-state energies for eight ligand-like molecules that agree with DMET-FCI to within about 10⁻⁶ Hartree.

  2. Quantum-Centric Alchemical Free Energy Calculations

    physics.chem-ph 2025-06 conditional novelty 6.0 of 10

    A new interface connects AMBER/QUICK with FCI and quantum-centric SQD solvers, enabling alchemical free energy corrections and the first use of SQD nuclear gradients.

  3. Quantum Assisted Ghost Gutzwiller Ansatz

    quant-ph 2025-06 conditional novelty 5.0 of 10

    A quantum-assisted ghost Gutzwiller ansatz, using QSCI with LUCJ states and circuit cutting on 24-qubit IQM hardware, captures the Mott transition in the Bethe lattice Hubbard model with only about 1% of the CI basis states.

  4. Machine-Learned Compact Subspace Generation for Quantum Selected Configuration Interaction within Density Matrix Embedding Framework

    quant-ph 2026-07 conditional novelty 4.0 of 10

    An RBM-guided selected-CI solver inside DMET reaches the DMET-CASCI energy within 1.6 mHa using ~4% of the symmetry-valid configuration subspace on an 11-fragment protein–ligand model.

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