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Strong empiricalAlgorithmsEigenvalue estimation

Quantum phase estimation

The eigenphase-estimation primitive behind chemistry, simulation, and period-finding workflows.

phaseeigenvaluechemistrysimulation

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QPE converts an eigenvalue phase into a classical bit string using controlled powers of a unitary and an inverse QFT. It is powerful, but its coherent-depth and state-overlap requirements are much stronger than a small demo suggests.

Circuit & simulation
φ bits90%
What this takes and returns
TakesNothingWhat joins here

No input port at this edge: the record publishes no gate sequence and no register, so there is nothing here to read one off — and unlike a declared hole, nothing has been recorded about what belongs here.

Nothing in the Atlas meets this end.

ReturnsNothingWhat joins here

No output port at this edge: the record publishes no gate sequence and no register, so there is nothing here to read one off — and unlike a declared hole, nothing has been recorded about what belongs here.

Nothing in the Atlas meets this end.

This record publishes no gate sequence and no register, so there is nothing here to read an interface off. Absent rather than empty. See all 152 →

Where this sits

This record is named by the layer graph at:

  • Phase estimation into an ancilla register Method

    Takes A circuit for U that can be applied as controlled U^(2^j), a preparation routine for a state whose overlap with the target eigenvector is not negligible, the number of bits of the phase wanted, and the failure probability that may be tolerated. Returns An estimate of the eigenphase to the requested number of bits, with the failure probability it was obtained at, plus the two costs that actually differ between routes: how many ancillas were held at once, and how many sequential rounds were run.

How it works

Quantum phase estimation extracts the phase φ[0,1)\varphi\in[0,1) of an eigenvalue e2πiφe^{2\pi i\varphi} for a unitary UU acting on an eigenstate Uψ=e2πiφψU|\psi\rangle=e^{2\pi i\varphi}|\psi\rangle. With mm phase-register qubits prepared in +m|+\rangle^{\otimes m}, applying controlled powers c-U2jc\text{-}U^{2^j} for j=0,,m1j=0,\dots,m-1 and an inverse QFT concentrates the register's amplitude near the mm-bit binary expansion of φ\varphi, with success probability 4/π2\ge4/\pi^2 for the nearest mm-bit estimate and error shrinking as O(2m)O(2^{-m}) — precision scales with the coherent circuit depth needed to apply U2m1U^{2^{m-1}}. This record checks a single-qubit phase rotation with a known eigenstate against the inverse-QFT readout — a controlled setting where φ\varphi is known in advance — matching the entry's caveat: applying QPE to an unknown Hamiltonian's eigenstate additionally requires state overlap and enough coherent evolution time to reach the desired precision.

Implementation
Native
phase_estimation.py
from qiskit import QuantumCircuit
from qiskit.circuit.library import QFT

qc = QuantumCircuit(3)
qc.h([0, 1])
# Controlled powers of U occupy the problem-specific block.
qc.cp(0.5, 0, 2)
qc.cp(1.0, 1, 2)
qc.append(QFT(2, inverse=True), [0, 1])

FINAL_CIRCUIT = qc

The controlled-U block is a phase-rotation toy, not a Hamiltonian simulation implementation.

Quantum vs classical

Classical baseline

Classical diagonalization, Lanczos/Krylov methods, or Fourier analysis when the operator has exploitable structure.

Quantum claim

Estimates eigenphases with precision tied to controlled-U evolution time in the coherent access model.

How to compare

Report eigenstate overlap, evolution cost, precision, repetitions, and the classical method used to interpret the result.

Declared gaps

Nobody has reviewed this record for gaps yet.

Literature & references
Quantum measurements and the Abelian Stabilizer Problem1995 · A. Yu. Kitaev

Foundational quantum measurement setting associated with phase estimation and hidden subgroup structure.

arxiv.org/abs/quant-ph/9511026
Tight Bounds for Quantum Phase Estimation and Related Problems2023 · Nikhil S. Mande, Ronald de Wolf

Provides modern precision and error-cost bounds for phase estimation.

arxiv.org/abs/2305.04908