Introduces and reviews the N00N-state formalism connecting quantum optical interferometry to quantum-information notation, including the Heisenberg-limited phase-scaling result used here.
arxiv.org/abs/quant-ph/0202133 ↗NOON state (two-mode, N=2)
The NOON state (|N,0⟩+|0,N⟩)/√2: a two-mode entangled state with all N particles in one mode or the other, the standard resource for Heisenberg-limited interferometric phase estimation.
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Classical (coherent-state) interferometry estimates a phase φ with uncertainty scaling as 1/√N in the number of probe particles — the standard quantum limit or shot-noise limit. NOON states were introduced to reach the fundamentally better 1/N Heisenberg scaling by concentrating N particles into a single maximally path-entangled superposition rather than spreading them across N independent particles.
Circuit & simulation
What this takes and returns
TakesNothingWhat joins here
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Returns1 qubitWhat joins here
Returns a 1-qubit register a next stage can take. This is the end that joins.
14 entries meet this end. Named below.
Prepares a state. Nothing goes in, and what comes out is a register another stage can take. See all 12 →
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State you can prepare 5 of 33 processes
- Quantum linear solve hands one back
- Prepare an input state hands one back
- Amplify a success branch hands one back
- Estimate an observable takes one
- Minimise the objective over the parameters hands one back
How it works
The N00N state on two bosonic modes with total particles is
an equal superposition of "all particles in mode " and "all particles in mode ." Because this superposition lives entirely within the two-dimensional subspace spanned by , it can be tracked with a single effective qubit for circuit-level bookkeeping: , , giving , formally identical to the Hadamard-basis state elsewhere in this catalog. This embedding is exact for tracking amplitudes and relative phase within the N00N manifold, but it does not capture the full bosonic Fock space or the nonlinear-optical resources (or heralded multi-photon interference) actually required to generate physically for ; the case alone is producible with linear optics via Hong–Ou–Mandel-style two-photon bunching at a 50:50 beamsplitter fed with one photon per input port.
Phase sensitivity. Passing mode through a phase shift (relative to ) evolves the state to
since each of the particles picks up phase independently, giving total — an -fold compression of the interference fringe compared to a single-particle probe, where the fringe would oscillate as rather than . Standard phase-estimation error propagation gives for an ideal N00N-state measurement (the Heisenberg limit), compared to for independent uncorrelated probes at the same total resource count (the standard quantum limit) — the quadratic advantage in that motivates using entangled probe states for quantum-enhanced sensing.
Fragility. The metrological advantage is purchased at a steep cost in robustness: losing even a single one of the particles collapses the coherence between the and branches entirely (an environment that "sees" which branch the lost particle came from performs a which-path measurement), so N00N-state sensitivity degrades catastrophically under loss, unlike less fragile metrological resource states such as spin-squeezed or Dicke states. This tradeoff between Heisenberg-limited scaling and loss-sensitivity is the central practical constraint on N00N-state interferometry.
Where this shows up. N00N states are the textbook example motivating quantum-enhanced interferometry and quantum radar/lidar proposals, and the case connects directly to two-photon Hong–Ou–Mandel interference — the same bosonic bunching effect that underlies photonic SWAP-test and boson-sampling architectures.
Implementation
import numpy as np
from qiskit import QuantumCircuit
from qiskit.quantum_info import Statevector
def noon_qubit_embedding(N: int, phi: float = 0.0) -> QuantumCircuit:
# Effective 2-level embedding: |0> == |N,0>, |1> == |0,N>.
qc = QuantumCircuit(1)
qc.h(0) # (|N,0> + |0,N>) / sqrt(2)
qc.rz(N * phi, 0) # N-fold phase accumulation e^{i N phi}
return qc
N = 2
sv0 = Statevector.from_instruction(noon_qubit_embedding(N, phi=0.0))
print("Amplitudes at phi=0:", sv0.data) # equal superposition
phi = np.pi / (2 * N)
sv = Statevector.from_instruction(noon_qubit_embedding(N, phi))
relative_phase = np.angle(sv.data[1]) - np.angle(sv.data[0])
print(f"Relative phase at phi={phi:.4f}: {relative_phase:.4f} (expected N*phi = {N * phi:.4f})")
FINAL_CIRCUIT = noon_qubit_embedding(N, phi)
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.
Declared gaps
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