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Amplitude amplification : ウィキペディア英語版
Amplitude amplification
Amplitude amplification is a technique in quantum computing which generalizes the idea behind
the Grover's search algorithm, and gives rise to a family of
quantum algorithms.
It was discovered by Gilles Brassard and
Peter Høyer in 1997,


and independently rediscovered by Lov Grover in 1998.


In a quantum computer, amplitude amplification can be used to obtain a
quadratic speedup over several classical algorithms.
== Algorithm ==

The derivation presented here roughly follows the one given in
.〔

Assume we have an N-dimensional Hilbert space \mathcal
representing the state space of our quantum system, spanned by the
orthonormal computational basis states B := \_^.
Furthermore assume we have a Hermitian projection operator P: \mathcal \to \mathcal.
Alternatively, P may be given in terms of a
Boolean oracle function
\chi:\mathbb \to \
and an orthonormal operational basis
B__^,
in which case
:P := \sum_ |\omega_k \rangle \langle \omega_k|.
P can be used to partition
\mathcal into a direct sum of two mutually orthogonal subspaces,
the ''good'' subspace \mathcal_1 and
the ''bad'' subspace \mathcal_0:
:
\begin
\mathcal_1 &:= \text\; P &= \operatorname\,\\
\mathcal_0 &:= \text \; P &= \operatorname\.
\end

Given a normalized state vector |\psi\rangle \in \mathcal which has nonzero overlap with both subspaces, we can
uniquely decompose it as
:|\psi\rangle = \sin(\theta) |\psi_1\rangle +\cos(\theta) |\psi_0\rangle,
where \theta = \arcsin\left( \left| P |\psi\rangle \right| \right) \in (\pi/2 ),
and
|\psi_1\rangle and |\psi_0\rangle are the
normalized projections of |\psi\rangle into the
subspaces \mathcal_1 and \mathcal_0,
respectively.
This decomposition defines a two-dimensional subspace
\mathcal_\psi, spanned by the vectors
|\psi_0\rangle and |\psi_1\rangle.

The probability of finding the system in a ''good'' state when measured
is \sin^2(\theta).
Define a unitary operator
Q(\psi, P) := -S_\psi S_P \,\!,
where
:
\begin
S_\psi &= I -2|\psi\rangle \langle\psi|\quad \text\\
S_P &= I -2 P.
\end

S_P flips the phase of the states in the ''good'' subspace, whereas
S_\psi flips the phase of the initial state |\psi\rangle.
The action of this operator on \mathcal_\psi is given by
:Q |\psi_0\rangle = -S_\psi |\psi_0\rangle = (2\cos^2(\theta)-1)|\psi_0\rangle +2 \sin(\theta) \cos(\theta) |\psi_1\rangle and
:Q |\psi_1\rangle = S_\psi |\psi_1\rangle = -2 \sin(\theta) \cos(\theta) |\psi_0\rangle +(1-2\sin^2(\theta))|\psi_1\rangle.
Thus in the \mathcal_\psi subspace Q
corresponds to a rotation by the angle 2\theta\,\!:
:Q = \begin
\cos(2\theta) & \sin(2\theta)\\
-\sin(2\theta) & \cos(2\theta)
\end.

Applying Q n times on the state
|\psi\rangle
gives
:Q^n |\psi\rangle = \cos((2n+1) \theta) |\psi_0\rangle +\sin((2n+1)\theta) |\psi_1\rangle,
rotating the state between the ''good'' and ''bad'' subspaces.
After n iterations the probability of finding the
system in a ''good'' state is \sin^2((2n+1)\theta)\,\!.

The probability is maximized if we choose
:n = \left\lfloor\frac\right\rfloor.
Up until this point each iteration increases the amplitude of the ''good'' states, hence
the name of the technique.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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