Approximation algorithms for quantum many-body problems

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Abstract

We discuss classical algorithms for approximating the largest eigenvalue of quantum spin and fermionic Hamiltonians based on semidefinite programming relaxation methods. First, we consider traceless 2-local Hamiltonians H describing a system of n qubits. We give an efficient algorithm that outputs a separable state whose energy is at least λ max /O(log n), where λ max is the maximum eigenvalue of H. We also give a simplified proof of a theorem due to Lieb that establishes the existence of a separable state with energy at least λ max /9. Second, we consider a system of n fermionic modes and traceless Hamiltonians composed of quadratic and quartic fermionic operators. We give an efficient algorithm that outputs a fermionic Gaussian state whose energy is at least λ max /O(n log n). Finally, we show that Gaussian states can vastly outperform Slater determinant states commonly used in the Hartree-Fock method. We give a simple family of Hamiltonians for which Gaussian states and Slater determinants approximate λ max within a fraction 1 − O(n −1 ) and O(n −1 ), respectively.

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Bravyi, S., Gosset, D., König, R., & Temme, K. (2019). Approximation algorithms for quantum many-body problems. Journal of Mathematical Physics, 60(3). https://doi.org/10.1063/1.5085428

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