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Exact & formalOperatorsFermionic Hamiltonians

Fermi-Hubbard dimer operator (Jordan-Wigner encoded)

The two-site Fermi-Hubbard dimer Hamiltonian, mapped to qubits via the Jordan-Wigner transformation: nearest-neighbor hopping competing with on-site Coulomb repulsion.

hubbard modelfermionic simulationjordan-wignerstrongly correlated electrons

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The Hubbard model is the minimal Hamiltonian containing both itinerant kinetic energy and strong local correlation, making it the standard target for quantum simulation of strongly correlated electron physics — including, in its 2D form, proposed connections to high-temperature superconductivity.

Circuit & simulation
Half-filling ground sector (N=2)100%
What this takes and returns
TakesNothingWhat joins here

No input port, deliberately. You measure a state with this entry; you do not apply it and pass a register on.

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ReturnsNothingWhat joins here

No output port, deliberately. An observable is measured with, never applied, so there is no register to hand on.

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Not a stage. You measure a state with this; you do not apply it and pass a register on. It has a width and deliberately no ports. See all 60 →

Where the map uses this

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Hamiltonian you can query 4 of 33 processes

How it works

The single-band Fermi-Hubbard model on a lattice with hopping tt and on-site interaction UU is

H=ti,j,σ(ciσcjσ+cjσciσ)+Uinini,niσ=ciσciσ.H = -t\sum_{\langle i,j\rangle,\sigma} \big(c^\dagger_{i\sigma} c_{j\sigma} + c^\dagger_{j\sigma} c_{i\sigma}\big) + U\sum_i n_{i\uparrow} n_{i\downarrow}, \qquad n_{i\sigma} = c^\dagger_{i\sigma}c_{i\sigma}.

Two-site dimer. With 2 sites and 2 spins there are 4 fermionic modes (1,1,2,2)(1{\uparrow},1{\downarrow},2{\uparrow},2{\downarrow}), mapped to 4 qubits. Using the Jordan-Wigner transform with mode ordering 1,1,2,21{\uparrow},1{\downarrow},2{\uparrow},2{\downarrow},

ck=(l<kZl)XkiYk2,ck=(l<kZl)Xk+iYk2,c^\dagger_k = \Big(\prod_{l<k} Z_l\Big)\frac{X_k - iY_k}{2}, \qquad c_k = \Big(\prod_{l<k} Z_l\Big)\frac{X_k + iY_k}{2},

so a hopping term ckck+1+h.c.c^\dagger_k c_{k+1} + \text{h.c.} becomes 12(XkXk+1+YkYk+1)\tfrac12(X_kX_{k+1}+Y_kY_{k+1}) acting on adjacent-index modes (with an extra ZZ-string factor if the modes are not adjacent in the chosen ordering), and each density term niσ=12(IZiσ)n_{i\sigma} = \tfrac12(I - Z_{i\sigma}) is diagonal.

Particle-number conservation. Both the hopping and interaction terms conserve total fermion number N=iσniσN=\sum_{i\sigma} n_{i\sigma}: hopping moves a fermion between sites without creating or destroying one, and the interaction term is purely diagonal in occupation. Consequently [H,N]=0[H, N] = 0, which block-diagonalizes the Hamiltonian by total filling and is the symmetry sector structure any correct encoding must reproduce.

Physical content. For U/t0U/t \to 0 the model reduces to free fermions hopping on the lattice (band physics); for U/tU/t \to \infty double occupancy is forbidden and, at half filling, the low-energy physics maps onto the antiferromagnetic Heisenberg model via a Schrieffer-Wolff-type superexchange argument (Jeff=4t2/UJ_{\text{eff}} = 4t^2/U) — directly connecting this operator to the Heisenberg XXZ operator elsewhere in this catalog. The model is believed (though not proven in 2D) to host a dd-wave superconducting regime near intermediate coupling, which is the primary reason it remains a central target for near-term quantum simulation.

Implementation
Native
fermi_hubbard_operator.py
import numpy as np
from qiskit.quantum_info import SparsePauliOp

def hubbard_dimer(t: float, U: float) -> SparsePauliOp:
    # Mode order: 0=1up, 1=1down, 2=2up, 3=2down
    n = 4
    terms, coeffs = [], []
    # Hopping 1up-2up (modes 0,2) and 1down-2down (modes 1,3), with Z-string for JW
    for (a, b) in [(0, 2), (1, 3)]:
        for pauli, coeff in (("X", -t / 2), ("Y", -t / 2)):
            s = ["I"] * n
            s[a], s[b] = pauli, pauli
            for k in range(a + 1, b):
                s[k] = "Z"
            terms.append("".join(reversed(s)))
            coeffs.append(coeff)
    # On-site interaction U * n_i_up * n_i_down = U/4 * (I-Z_up)(I-Z_down),
    # expanded directly as Pauli strings.
    for (up, down) in [(0, 1), (2, 3)]:
        s0 = ["I"] * n
        terms.append("".join(reversed(s0))); coeffs.append(U / 4)
        s1 = ["I"] * n; s1[up] = "Z"
        terms.append("".join(reversed(s1))); coeffs.append(-U / 4)
        s2 = ["I"] * n; s2[down] = "Z"
        terms.append("".join(reversed(s2))); coeffs.append(-U / 4)
        s3 = ["I"] * n; s3[up], s3[down] = "Z", "Z"
        terms.append("".join(reversed(s3))); coeffs.append(U / 4)
    return SparsePauliOp(terms, coeffs).simplify()

H = hubbard_dimer(t=1.0, U=4.0)
N_op = SparsePauliOp(["".join(reversed(["Z" if k == i else "I" for k in range(4)])) for i in range(4)],
                      [-0.5] * 4) + SparsePauliOp("IIII", [2.0])
commutator = H.to_matrix() @ N_op.to_matrix() - N_op.to_matrix() @ H.to_matrix()
print("max |[H, N]| =", np.abs(commutator).max())  # ~0, confirming particle-number conservation

RESULT = {"max_commutator_norm": float(np.abs(commutator).max()), "conserves_particle_number": bool(np.abs(commutator).max() < 1e-9)}
Quantum vs classical

Classical baseline

Use a classical state-vector or matrix simulation at the same width, precision, and measurement objective.

Quantum claim

The quantum record demonstrates a state or operator behavior; it does not make classical simulation or communication costs disappear.

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Literature & references
Electron correlations in narrow energy bands1963 · J. Hubbard

Original paper introducing the Hubbard model of competing itinerant hopping and on-site Coulomb repulsion.

doi.org/10.1098/rspa.1963.0204
Strategies for solving the Fermi-Hubbard model on near-term quantum computers2019 · Chris Cade, Lana Mineh, Ashley Montanaro, Stasja Stanisic

Analyzes Jordan-Wigner-encoded Hubbard Hamiltonians and their resource requirements for near-term quantum simulation.

arxiv.org/abs/1912.06007