Explicitly correlated ground states with a feedback-free variational hybrid algorithm
quant-ph, cond-mat.str-el
Submitted: 2026-10-13
Updated: 2026-10-13
License: http://creativecommons.org/licenses/by/4.0/
The gist: Explicitly correlated methods, which represent dominant short-range correlations by a diagonal Jastrow-type correlator, are designed to accurately describe systems of strongly correlated electrons,
Abstract
Explicitly correlated methods, which represent dominant short-range correlations by a diagonal Jastrow-type correlator, are designed to accurately describe systems of strongly correlated electrons, such as the fully periodic 2D Fermi--Hubbard model. However, as the reference state is compact in momentum space whereas the correlator acts naturally in real space, there is a fundamental mismatch of bases that classical algorithms resolve only by restricting the reference or the correlator. Here we propose a hybrid algorithm in which a quantum processor prepares a low-entanglement momentum-space matrix product state (MPS), precomputed classically by the transcorrelated method at the cost of a nonvariational energy, rotates it to real space, and measures in bases fixed by the Hamiltonian. Because the measurement bases are independent of the correlator, the correlator can be variationally optimized entirely in classical post-processing with no quantum-classical feedback loop. We demonstrate our algorithm on 32 qubits of Quantinuum's H2-2 with a bond-dimension-4 MPS for the half-filled 4 times 4 lattice and achieve a relative ground-state energy error of 16 plus or minus 4% after postselection, reduced to 3.5 plus or minus 0.5% by calibration using low-order moments from the MPS. Compared with other feedback-free hybrid algorithms, even under generous assumptions, our method requires fewer samples than quantum-selected configuration interaction and fewer two-qubit gates than quantum Krylov methods.
Sources
- Improving the accuracy of quantum computational chemistry using the transcorrelated method
- Solving the Hubbard model with Neural Quantum States
- Quantum Filter Diagonalization: Quantum Eigendecomposition without Full Quantum Phase Estimation
- Fermionic dynamics on a trapped-ion quantum computer beyond exact classical simulation
- Superconducting pairing correlations on a trapped-ion quantum computer
- Faster matrix product state preparation by exploiting symmetry-induced block-sparsity
- A Critical Assessment of the Sample-Based Quantum Diagonalization for Heisenberg and Hubbard Models
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