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arxiv: 1808.02625 · v2 · pith:7EWPDAZKnew · submitted 2018-08-08 · ⚛️ physics.comp-ph · quant-ph

Low rank representations for quantum simulation of electronic structure

classification ⚛️ physics.comp-ph quant-ph
keywords mathcalcomplexitygatehamiltoniantrotterquantumsimulationbasis
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The quantum simulation of quantum chemistry is a promising application of quantum computers. However, for N molecular orbitals, the $\mathcal{O}(N^4)$ gate complexity of performing Hamiltonian and unitary Coupled Cluster Trotter steps makes simulation based on such primitives challenging. We substantially reduce the gate complexity of such primitives through a two-step low-rank factorization of the Hamiltonian and cluster operator, accompanied by truncation of small terms. Using truncations that incur errors below chemical accuracy, we are able to perform Trotter steps of the arbitrary basis electronic structure Hamiltonian with $\mathcal{O}(N^3)$ gate complexity in small simulations, which reduces to $\mathcal{O}(N^2 \log N)$ gate complexity in the asymptotic regime, while our unitary Coupled Cluster Trotter step has $\mathcal{O}(N^3)$ gate complexity as a function of increasing basis size for a given molecule. In the case of the Hamiltonian Trotter step, these circuits have $\mathcal{O}(N^2)$ depth on a linearly connected array, an improvement over the $\mathcal{O}(N^3)$ scaling assuming no truncation. As a practical example, we show that a chemically accurate Hamiltonian Trotter step for a 50 qubit molecular simulation can be carried out in the molecular orbital basis with as few as 4,000 layers of parallel nearest-neighbor two-qubit gates, consisting of fewer than 100,000 non-Clifford rotations. We also apply our algorithm to iron-sulfur clusters relevant for elucidating the mode of action of metalloenzymes.

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

  1. Distribution Complexity of Electronic Structure Simulations on Quantum Supercomputers

    quant-ph 2026-06 unverdicted novelty 5.0

    An algorithm is presented for estimating distribution complexity of electronic structure Hamiltonians, with O(N^3) entanglement estimation per fragment and quadratic/exponential reductions in distribution cost for qua...