Quantum Advantage with Noisy Shallow Circuits in 3D
Sergey Bravyi, David Gosset, et al.
FOCS 2019
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.
Sergey Bravyi, David Gosset, et al.
FOCS 2019
Sergey Bravyi, Dan Browne, et al.
Quantum
Theodore Yoder, Sergey Bravyi, et al.
APS March Meeting 2024
Sergey Bravyi, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory