Optimizing sparse fermionic Hamiltonians

Journal Article (2023)
Author(s)

Yaroslav Herasymenko (Centrum Wiskunde & Informatica (CWI), TU Delft - QCD/Terhal Group, TU Delft - QuTech Advanced Research Centre)

Maarten Stroeks (TU Delft - QCD/Terhal Group, TU Delft - QuTech Advanced Research Centre)

Jonas Helsen (Centrum Wiskunde & Informatica (CWI))

B. M. Terhal (TU Delft - QCD/Terhal Group, TU Delft - Quantum Computing, TU Delft - QuTech Advanced Research Centre)

Research Group
QCD/Terhal Group
Copyright
© 2023 Y.R. Herasymenko, M.E.H.M. Stroeks, Jonas Helsen, B.M. Terhal
DOI related publication
https://doi.org/10.22331/q-2023-08-10-1081
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Y.R. Herasymenko, M.E.H.M. Stroeks, Jonas Helsen, B.M. Terhal
Research Group
QCD/Terhal Group
Volume number
7
Pages (from-to)
1081
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Abstract

We consider the problem of approximating the ground state energy of a fermionic Hamiltonian using a Gaussian state. In sharp contrast to the dense case [1, 2], we prove that strictly q-local sparse fermionic Hamiltonians have a constant Gaussian approximation ratio; the result holds for any connectivity and interaction strengths. Sparsity means that each fermion participates in a bounded number of interactions, and strictly q-local means that each term involves exactly q fermionic (Majorana) operators. We extend our proof to give a constant Gaussian approximation ratio for sparse fermionic Hamiltonians with both quartic and quadratic terms. With additional work, we also prove a constant Gaussian approximation ratio for the so-called sparse SYK model with strictly 4-local interactions (sparse SYK-4 model). In each setting we show that the Gaussian state can be efficiently determined. Finally, we prove that the O(n1/2) Gaussian approximation ratio for the normal (dense) SYK-4 model extends to SYK-q for even q > 4, with an approximation ratio of O(n1/2−q/4). Our results identify non-sparseness as the prime reason that the SYK-4 model can fail to have a constant approximation ratio [1, 2].

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