Operators · Spin Hamiltonians
Transverse-field Ising model operator
The transverse-field Ising model (TFIM): the standard minimal Hamiltonian exhibiting a quantum (zero-temperature) phase transition driven by competing Z-Z order and X-field disorder.
Exact & formalUpdated
4 steps across 4 wires. Hover a step, or press play to go through them in order.
Expected outcomes
- h < J: ferromagnetic order50%
- h > J: paramagnetic50%
- Steps4
- Wires4
- Sites4 (chain)
- Terms3 ZZ + 4 X
- Critical pointh = J (self-dual)
- Papers2
Adding a transverse field to the classical Ising chain turns a purely statistical-mechanics model into the paradigmatic example of a quantum phase transition — one driven by the Heisenberg uncertainty between competing non-commuting terms rather than by thermal fluctuations.
TakesNothingWhat joins here
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ReturnsNothingWhat joins here
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Nothing in the Atlas meets this end.
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 →
The transverse-field Ising model (TFIM) on a chain of sites is
Genuinely quantum. Unlike the classical Ising operator, because and anticommute: . The transverse field therefore drives real transitions between computational-basis states, and cannot be diagonalized simply by inspection.
Exact solvability. Via a Jordan–Wigner transformation, the 1D TFIM maps exactly onto free fermions, giving the closed-form dispersion relation (periodic chain, )
so ground-state energies and gaps are known in closed form at every system size — the reason this model is the standard exact benchmark for VQE, Trotterized time evolution, and quantum annealing schedules.
Quantum phase transition. At zero temperature, tuning drives a transition at the self-dual point between a ferromagnetically ordered phase (, spontaneous symmetry breaking of the global spin-flip ) and a paramagnetic phase (, field-aligned along X). The transition is continuous, with the gap closing as — the paradigmatic example distinguishing a quantum phase transition (driven by at ) from the thermal transition of the classical 2D Ising model, to which the 1D TFIM's partition function is related by a quantum-classical mapping.
Use in the catalog. This operator sits directly above the classical Ising Hamiltonian and the XXZ chain in the family of exactly-characterizable spin models: setting recovers the classical diagonal operator, and the model's non-commuting structure is exactly what a Trotter-based Hamiltonian simulation or a VQE ansatz must reproduce.
TakesNothingWhat joins here
No input port, deliberately. You measure a state with this entry; you do not apply it and pass a register on.
Nothing in the Atlas meets this end.
ReturnsNothingWhat joins here
No output port, deliberately. An observable is measured with, never applied, so there is no register to hand on.
Nothing in the Atlas meets this end.
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 →
- Sites
- 4 (chain)
- Terms
- 3 ZZ + 4 X
- Critical point
- h = J (self-dual)
- Hamiltonian
- H = -JΣZᵢZᵢ₊₁ - hΣXᵢ
- Commutation
- [H, Zᵢ] ≠ 0
- Symmetry
- Z₂ (global spin flip ΠXᵢ)
ZZon Z₀, Z₁ZZon Z₁, Z₂ZZon Z₂, Z₃X fieldon Z₀, Z₁, Z₂, Z₃
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.
How to compare
Compare fidelity, samples, gate depth, noise, memory, and the cost of preparing and reading the state.
Nobody has reviewed this record for gaps yet.
import numpy as np
from qiskit.quantum_info import SparsePauliOp
def tfim_hamiltonian(n: int, J: float, h: float) -> SparsePauliOp:
terms, coeffs = [], []
for i in range(n - 1):
s = ["I"] * n
s[i], s[i + 1] = "Z", "Z"
terms.append("".join(reversed(s)))
coeffs.append(-J)
for i in range(n):
s = ["I"] * n
s[i] = "X"
terms.append("".join(reversed(s)))
coeffs.append(-h)
return SparsePauliOp(terms, coeffs)
n = 4
H_crit = tfim_hamiltonian(n, J=1.0, h=1.0) # self-dual critical point
Z0 = SparsePauliOp("IIIZ")
commutator = H_crit.to_matrix() @ Z0.to_matrix() - Z0.to_matrix() @ H_crit.to_matrix()
print("max |[H, Z0]| =", np.abs(commutator).max()) # nonzero: genuine quantum dynamics
eigvals = np.linalg.eigvalsh(H_crit.to_matrix())
print("Ground energy:", eigvals[0])
RESULT = {"ground_energy": float(eigvals[0]), "max_commutator_norm": float(np.abs(commutator).max())}
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Hamiltonian you can query 6 of 34 processes
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Related entries
- Classical Ising Hamiltonian operator
Operators
- Heisenberg XXZ spin-chain operator
Operators
- Single-qubit thermal (Gibbs) state
Operators
References
- The one-dimensional Ising model with a transverse field
P. Pfeuty · 1970
Original exact solution of the TFIM via Jordan-Wigner fermionization, giving the dispersion relation used in this entry.
- Quantum Phase Transitions
S. Sachdev · 2011
Standard textbook treatment of the TFIM as the canonical example of a quantum (zero-temperature) phase transition.