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All instances / Heisenberg

Heisenberg square 4x4

Exact energy and best values (rules §6)

exact -0.7017802 ED
Wu et al. (2024) · the instance is solved
best variational -0.7017449 VQE
Wu et al. (2024) · the lowest unflagged variational energy, a strict variational bound

Energies as E/N (S.S). Classes are different claims and are not ranked against each other.

The Hamiltonian

H = ∑⟨ij⟩ σi·σj

Nearest-neighbour Heisenberg antiferromagnet, J = 1, written with Pauli matrices.

lattice
square
sites
16
boundary
periodic
energies
3

Stored as a total energy; quoted here as E/N (S.S), which is what the papers report (how the conversion works).

Every published energy

Grouped by what the number is. The exact energy comes first where there is one; in every other group the lowest unflagged energy is its best value, and each row's distance is to that best (rules §6).

Numerically exact (1)

Exact diagonalization, an exact solution, or sign-problem-free QMC where that is established. An exact energy is shown first, before the best of each other class. QMC is exact only within its error bar, which it must state, and reads exact (stochastic); an exact diagonalization outranks it. For a diagonalization resolved by symmetry sector only the ground state's sector is listed; the lowest energies of the other sectors are the instance's spectrum, in its JSON, and are not shown as the exact energy.

E/N (S.S)distance to class bestσVar(E)V-score methodsourcecodeyearcomment
-0.7017802exact 0 n/a n/a n/a ED
VarBench reference run
Wu et al. (2024) run script 2024

Strict variational upper bounds (2)

Energies that a variational state reached (VMC, DMRG and MPS at finite bond dimension, PEPS, NQS, VQE). Each is an upper bound on the ground-state energy.

E/N (S.S)distance to class bestσVar(E)V-score methodsourcecodeyearcomment
-0.7017449best variational 0 n/a 1.06e-1 8.4e-4 VQE
VarBench reference run
Wu et al. (2024) run script 2024
-0.7017252 2.0e-5 n/a 1.60e-1 1.3e-3 VQE
VarBench reference run
Wu et al. (2024) run script 2024

How these numbers were read

Where each number below was read, and how it was checked.

-0.7017802, ED

Checked 2026-09-29 · QMBL ED cost run checks/cost/ed/results/Heisenberg--square_16_P.json (checks/cost/ed/run_ed.py: NetKet 3.22.4 operator, sparse CSR built in blocks, SciPy eigsh/ARPACK k=1 SA; commit 716e043); results file read locally, no rerun

Reported as. energy -44.91393283371538 (stored_exact -44.9139328, relative_difference 7.51e-10, reproduces_stored true)

|reproduced - stored| = 3.37e-8 (relative 7.51e-10); within 1e-9 relative. Sector total Sz = 0, dimension 12870, 61 Lanczos steps (the file states no residual). The stored value is the source's own ED (varbench@2024-10-22), so two codes agree; a third code, E1's node Lanczos (qmbl-runs/qmbl-verify/out/E1-exact-recompute/results/Heisenberg__square_16_P.json), gives -44.91393283371616 (7.82e-13 from the cost run). Also read by VB3-varbench-code-heisenberg#38 (scope config: vendor/varbench/Heisenberg/square_16_P.md (snapshot 390a21e), row 'Exact diagonalization'; linked scripts/Heisenberg/square_16_P/vqe.sh).

-0.7017449, VQE

Checked 2026-09-29 · VarBench snapshot 390a21e (vendor/varbench) and full upstream history (varbench-history, git log --follow on the file, every version); varbench/methods ed31bb0 run script and program read as text; no output log or result file exists in the methods repo for any Heisenberg row

Reported as. | -44.9116731 | | 0.1064 | 16 | 0 | VQE + symm. circuit (64 pars., exact grad, statevector) | [code](https://github.com/varbench/methods/blob/main/scripts/Heisenberg/square_16_P/vqe.sh) |

Best variational bound on the solved instance. vqe.sh: --j2=0.0 --lattice=square4x4 -> HeisenbergSquare, NN bonds of the periodic 4x4 lattice, H = sum 2 P_ij - N_bonds = sigma.sigma (hamiltonians.py lines 26-27, 170-229), Sz = 0, then --symmetry=1 (projection onto the eigenvalue-1 sector of the listed generators). The logged energy is the exact statevector expectation of the normalised projected state (observables.py lines 196-199, '{:.7f}' line 237): deterministic, so sigma null is right. 'exact grad' is the default 2^36 shots per gradient term (main.py line 13), effectively exact. 0.00226 above the exact energy. Which iteration VarBench took is not stated; every logged line is a strict bound. Entered 2022-11-11 (N. Astrakhantsev), never changed.

-0.7017252, VQE

Checked 2026-09-29 · VarBench snapshot 390a21e (vendor/varbench) and full upstream history (varbench-history, git log --follow on the file, every version); varbench/methods ed31bb0 run script and program read as text; no output log or result file exists in the methods repo for any Heisenberg row

Reported as. | -44.9104126 | | 0.1599 | 16 | 0 | VQE + symm. circuit (64 pars., 2^14 samples/grad) | [code](https://github.com/varbench/methods/blob/main/scripts/Heisenberg/square_16_P/vqe_noisy.sh) |

vqe_noisy.sh: same Hamiltonian and projection with --log2samples=14. The logged energy is still the exact statevector expectation of the projected state (observables.py lines 196-199: state = self.circuit(noisy=False); circuits.py __call__ returns the noiseless state), so the 2^14 shots enter only the gradient and metric estimates; the energy carries no statistical error (see the ambiguous entry on eligibility). 0.00352 above the exact energy and 0.00126 above the exact-grad variant, so nothing changes on this instance. Entered 2022-11-11 (N. Astrakhantsev), never changed; linked 5285adc (2024-08-12).

Coverage

Newest published number here: 2024. Literature last checked 2026-09-15 (table harvest of cached arXiv sources (match_tables.mjs --all), every matched paper read for this instance): 5 papers read, 0 of them with an energy on this page.

This instance as data

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