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Quantum Fourier transform

The quantum Fourier transform is a quantum circuit implementing the discrete Fourier transform on the amplitudes of a quantum state.

How 2 Manning books explain it

Building Quantum Software with Python

The quantum Fourier transform is a quantum algorithm that applies the Fourier transform to amplitudes of a quantum state, converting encoded phase relationships into measurable amplitude patterns.

How it is used
Converts phase-encoded periodic information into measurable magnitude patterns and prepares useful quantum-state distributions.
How deep it goes
Works from a one-qubit Hadamard example through Fourier bases and executable QFT/IQFT circuits, while deferring a rigorous equivalence proof.
Examples
Uses a π/3 single-qubit phase encoding, Fourier-basis state vectors, four-qubit QFT circuits, and phased discrete sinc states.
What you can do after
Build it from scratch as QFT and IQFT circuits using Hadamard gates, controlled phase rotations, and optional register swaps.

Read how Building Quantum Software with Python explains quantum Fourier transform →

Quantum Programming in Depth

The quantum Fourier transform is the quantum analogue of the discrete Fourier transform, mapping amplitudes between computational bases.

How it is used
Supports phase estimation by transforming amplitude-encoded information into phase-encoded information.
How deep it goes
Defines one- and two-qubit behavior but stops short of the general form and arbitrary-qubit implementation.
Examples
Uses the one-qubit Hadamard gate and one- or two-bit phase-precision scenarios as concrete cases.
What you can do after
Apply QFT as a phase-estimation building block while recognizing its classical input-output overhead.

Read how Quantum Programming in Depth explains quantum Fourier transform →

Related concepts

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