Fermionic Orbital Optimization in Tensor Network States

2015/04/30 by Christian Krumnow, C. Krumnow, L. Veis +5 · 1 citation
Chemistry · Mathematics · Physics and Astronomy · #Advanced NMR Techniques and Applications #Atomic orbital #Basis (linear algebra) #Chemistry #Computer science #Context (archaeology) #Degrees of freedom (physics and chemistry) #Electron #Geometry #Mathematics #Matrix (chemical analysis) #Matrix multiplication #Matrix product state #Physics #Physics of Superconductivity and Magnetism #Pure mathematics #Quantum #Quantum many-body systems #Quantum mechanics #Statistical physics #Tensor (intrinsic definition) #Tensor product #Theoretical physics #cond-mat.str-el #physics.chem-ph #quant-ph

paper · pdf · doi:10.1103/physrevlett.117.210402

published as Phys. Rev. Lett. 117, 210402 (2016) · 9 pages, 9 figures, added substantial material to signify improved numerical performance

arxiv created 2016/06/16 · openalex publication_date 2016/11/18 · arxiv updated 2016/11/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Tensor network states and specifically matrix-product states have proven to be a powerful tool for simulating ground states of strongly correlated spin models. Recently, they have also been applied to interacting fermionic problems, specifically in the context of quantum chemistry. A new freedom arising in such nonlocal fermionic systems is the choice of orbitals, it being far from clear what choice of fermionic orbitals to make. In this Letter, we propose a way to overcome this challenge. We suggest a method intertwining the optimization over matrix product states with suitable fermionic Gaussian mode transformations. The described algorithm generalizes basis changes in the spirit of the Hartree-Fock method to matrix-product states, and provides a black box tool for basis optimization in tensor network methods.

Citations

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• かがわ遠隔医療ネットワークから日本版EHRの実現へ (総特集 ITによる医療現場の具体的変革)
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• Improving Vocabulary Knowledge and Reading Attitudes in 4th Grade Students Through Direct Vocabulary Instruction.

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