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Heat-bath Configuration Interaction: An efficient selected CI algorithm inspired by heat-bath sampling

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arxiv 1606.07453 v1 pith:2ZQPZO3D submitted 2016-06-23 physics.chem-ph cond-mat.str-elquant-ph

classification physics.chem-phcond-mat.str-elquant-ph
keywords algorithmconfigurationheat-bathinteractionaccuracybasisdeterminantsdimer
verification ladder T0 review T1 audit T2 compute T3 formal
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We introduce a new selected configuration interaction plus perturbation theory algorithm that is based on a deterministic analog of our recent efficient heat-bath sampling algorithm. This Heat-bath Configuration Interaction (HCI) algorithm makes use of two parameters that control the tradeoff between speed and accuracy, one which controls the selection of determinants to add to a variational wavefunction, and one which controls the the selection of determinants used to compute the perturbative correction to the variational energy. We show that HCI provides an accurate treatment of both static and dynamic correlation by computing the potential energy curve of the multireference carbon dimer in the cc-pVDZ basis. We then demonstrate the speed and accuracy of HCI by recovering the full configuration interaction energy of both the carbon dimer in the cc-pVTZ basis and the strongly-correlated chromium dimer in the Ahlrichs VDZ basis, correlating all electrons, to an accuracy of better than 1 mHa, in just a few minutes on a single core. These systems have full variational spaces of 3x10^14 and 2x10^22 determinants respectively.

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

  1. Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier

    quant-ph 2026-08 conditional novelty 6.0 of 10

    A critical review plus small exact-FCI experiments concludes that sample-based quantum diagonalization has not beaten classical selected CI and maps where, if anywhere, a quantum or generative advantage could survive.

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