--- title: "Addition by Fourier transform" author: "Carsten Urbach" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Addition by Fourier transform} %\VignetteEngine{knitr::rmarkdown} \usepackage[utf8]{inputenc} bibliography: bibliography.bib link-citation: true reference-section-title: References --- ```{r echo=FALSE} library(knitr) library(qsimulatR) knitr::opts_chunk$set(fig.align='center', comment='') ``` This corresponds to problem 5.6 in Nielsen & Chuang. The original paper is [@draper2000addition]. Which quantum circuit can be used to perform the computation \[ |x\rangle\quad\to\quad |x + y \mod 2^n\rangle \] with $0\leq x < 2^n$ and a constant **integer** $y$. We exploit the general idea \[ x+y = \log\left(\mathrm{e}^x\mathrm{e}^y\right) \] where the exponentiation is de facto performed by a Fourier trafo and the logarithm by the inverse trafo. Fourier transforming the state $|x\rangle$ with $n$ bits, leads to the following product representation \[ |x\rangle\ = |x_n x_{n-1} \ldots x_1\rangle\ \to\ \frac{1}{2^n}(|0\rangle + e^{2\pi i 0.x_1}|1\rangle)(|0\rangle + e^{2\pi i 0.x_2x_1}|1\rangle)\cdots (|0\rangle + e^{2\pi i 0.x_n\ldots x_1}|1\rangle) \] where we use the notation \[ x = x_1 2^0 + x_2 2^1 + \ldots + x_n 2^{n-1} \] and \[ 0.x_l \ldots x_1\ \equiv\ \frac{x_l}{2} + \frac{x_{l-1}}{2^{2}} + \ldots + \frac{x_1}{2^{l}}\,. \] Now, we apply a phase shift $R_\theta(\theta)$ to each qubit \[ R_z\ \equiv\ \begin{pmatrix} 1 & 0\\ 0 & \exp(i\theta)\\ \end{pmatrix}\,. \] We apply $R_\theta$ with $\theta_j = 2\pi y/2^{n-(j-1)}$ to qubit $j$ where $1\leq j\leq n$. For $y$ we can also write \[ y\ =\ y_1 2^0 + y_2 2^1 + \ldots + y_n 2^{n-1}\,. \] Thus, \[ \exp(2\pi i y/2^{n-j+1}) = \prod_{k=0}^{n-1} \exp(2\pi i y_{k+1} 2^{j-1-n+k})\,. \] Since $\exp(2\pi i y_k l) = 1$ for positive integer $l$, this reduces to (recall $y_k\in\{0,1\}$) \[ \exp(2\pi i y/2^{n-j+1}) = \prod_{k=0}^{n-j} \exp(2\pi i y_{k+1} 2^{j-1-n+k})\,. \] The $n$th qubit gets multiplied with $\exp(i\theta_n)$ with $\theta_n = 2\pi y /2^{1}$. Thus, we need to compute \[ \exp(2\pi i x_1/2)\cdot \exp(2\pi i y_1/2) = \exp(2\pi i (x_1 + y_1) /2)\,. \] Similarly, for the $j$th qubit one gets \[ \exp(2\pi i (x_1/2^{n-j+1} + x_2/2^{n-j} + ...))\cdot \exp(2\pi i (y_1/2^{n-j+1} + y_2/2^{n-j} + ...)) = \exp(2\pi i ((x_1 + y_1) /2^{n-j+1} + (x_2 + y_2)/2^{n-j} + ...)) \] which implements the addition $\mod n$ operation in this binary fraction. Now apply the inverse Fourier trafo and it is easy to see that this transforms back to the state $|x+y\mod n\rangle$. For the practical implementation we first need the phase shift operators, which is up to a phase identical to $R_z$: ```{r} Rtheta <- function(bit, theta=0.) { return(methods::new("sqgate", bit=as.integer(bit), M=array(as.complex(c(1, 0, 0, exp(1i*theta))), dim=c(2,2)), type="Rt")) } ``` With this one can write the desired function on state $x$. ```{r} addbyqft <- function(x, y) { n <- x@nbits z <- qsimulatR::qft(x) for(j in c(1:n)) { z <- Rtheta(bit=j, theta = 2*pi*y/2^(n-j+1)) * z } z <- qft(z, inverse=TRUE) return(invisible(z)) } ``` Examples ```{r} x <- qstate(5, basis=as.character(seq(0, 2^5-1))) x z <- addbyqft(x, 3) z z <- addbyqft(z, 5) z z <- addbyqft(z, 30) z ```