# Phase Estimation Algorithm¶

## Overview¶

The phase estimation algorithm is a quantum subroutine useful for finding the eigenvalue corresponding to an eigenvector $$u$$ of some unitary operator. It is the starting point for many other algorithms and relies on the inverse quantum Fourier transform. More details can be found in references .

## Example¶

First, connect to the QVM.

import pyquil.api as api

qvm = api.QVMConnection()


Now we encode a phase into the unitary operator U.

import numpy as np

phase = 0.75
phase_factor = np.exp(1.0j * 2 * np.pi * phase)
U = np.array([[phase_factor, 0],
[0, -1*phase_factor]])


Then, we feed this operator into the phase_estimation module. Here, we ask for 4 bits of precision.

from grove.alpha.phaseestimation.phase_estimation import phase_estimation

precision = 4
p = phase_estimation(U, precision)


Now, we run the program and check our output.

output = qvm.run(p, range(precision))
wavefunction = qvm.wavefunction(p)

print(output)
print(wavefunction)


This should print the following:

[[0, 0, 1, 1]]
(1+0j)|01100>


Note that .75, written as a binary fraction of precision 4, is 0.1100. Thus, we have recovered the phase encoded into our unitary operator.

## Source Code Docs¶

Here you can find documentation for the different submodules in phaseestimation.

### grove.phaseestimation.phase_estimation¶

grove.alpha.phaseestimation.phase_estimation.controlled(m)

Make a one-qubit-controlled version of a matrix.

Parameters: m – (numpy.ndarray) A matrix. A controlled version of that matrix.
grove.alpha.phaseestimation.phase_estimation.phase_estimation(U, accuracy, reg_offset=0)

Generate a circuit for quantum phase estimation.

Parameters: U – (numpy.ndarray) A unitary matrix. accuracy – (int) Number of bits of accuracy desired. reg_offset – (int) Where to start writing measurements (default 0). A Quil program to perform phase estimation.

References

  Nielsen, Michael A., and Isaac L. Chuang. Quantum Computation and Quantum Information. Cambridge University Press, 2010.