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Accurate quantum-centric simulations of supramolecular interactions

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arxiv 2410.09209 v2 pith:N2XDBG7M submitted 2024-10-11 quant-ph

Danil Kaliakin , Akhil Shajan , Javier Robledo Moreno , Zhen Li , Abhishek Mitra , Mario Motta , Caleb Johnson , Abdullah Ash Saki
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Susanta Das Iskandar Sitdikov Antonio Mezzacapo Kenneth M. Merz Jr
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keywords interactionsquantumsimulationsaccurateapproachchemicalhydrophobicmethods
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We present the first quantum-centric simulations of noncovalent interactions using a supramolecular approach. We simulate the potential energy surfaces (PES) of the water and methane dimers, featuring hydrophilic and hydrophobic interactions, respectively, with a sample-based quantum diagonalization (SQD) approach. Our simulations on quantum processors, using 27- and 36-qubit circuits, are in remarkable agreement with classical methods, deviating from complete active space configuration interaction (CASCI) and coupled-cluster singles, doubles, and perturbative triples (CCSD(T)) within 1 kcal/mol in the equilibrium regions of the PES. Finally, we test the capacity limits of the quantum methods for capturing hydrophobic interactions with an experiment on 54 qubits. These results mark significant progress in the application of quantum computing to chemical problems, paving the way for more accurate modeling of noncovalent interactions in complex systems critical to the biological, chemical and pharmaceutical sciences.

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Cited by 5 Pith papers

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

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

    quant-ph 2024-11 conditional novelty 7.0 of 10

    The first implementation of density matrix embedding theory with sample-based quantum diagonalization is demonstrated on quantum hardware for an 18-hydrogen ring and cyclohexane, yielding energies close to classical r...

  2. Resource-efficient Quantum Algorithms for Selected Hamiltonian Subspace Diagonalization

    quant-ph 2026-03 conditional novelty 6.0 of 10

    A first-quantized CI-matrix QSCI variant reduces qubit count to O(log N) and gives accuracy on N2/naphthalene comparable to sample-based quantum diagonalization.

  3. 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.

  4. Polynomially efficient quantum enabled variational Monte Carlo for training neural-network quantum states for physico-chemical applications

    quant-ph 2024-12 conditional novelty 6.0 of 10

    A variational Monte Carlo algorithm that trains a restricted Boltzmann machine quantum state by sampling a fitted Ising surrogate with a Trotterized quantum circuit, demonstrated on small spin and molecular systems.

  5. Implicit solvent sample-based quantum diagonalization

    quant-ph 2025-02 conditional novelty 5.0 of 10

    SQD with IEF-PCM solvation reproduces CASCI IEF-PCM energies for four small molecules on IBM quantum hardware.

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