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Dual numbers and hyperdual space

Dual number theory

Dual numbers are a type of complex numbers. The ubiquitous set of complex numbers, \(\mathbb{C}\), may be defined as follows, where \(i\) is the imaginary number:

\[\begin{equation} \mathbb{C}=\mathbb{R}[i]=\{z=a+bi~|~(a,b)\in\mathbb{R}^2,i^2=-1\} \end{equation}\]

Similarly, we may define the set of dual numbers as follows, where \(\epsilon\) is the dual number:

\[\begin{equation} \mathbb{D}=\mathbb{R}[\epsilon]=\{z=a+b\epsilon~|~(a,b)\in\mathbb{R}^2,\epsilon^2=0 \text{~and~} \epsilon \neq 0\} \end{equation}\]

Moreover, for \(z=a+b\epsilon\) where \(z\in\mathbb{D},~(a,b)\in\mathbb{R}\), let us define the \(real\) and \(dual\) parts of a dual number such as

\[\begin{equation} \begin{cases} real(z) = a\\ dual(z) = b \end{cases} \end{equation}\]

An auto-differentiation property emerges from the addition of this nilpotent element, as is obvious from a Taylor series expansion. Evidently, this result is only valid for values of \(a\) where the function is differentiable.

\[\begin{equation} \begin{aligned} f:\mathbb{D}\rightarrow\mathbb{D}~, (a,b)\in\mathbb{R}^2 &\\ f(a+b\varepsilon) &=\sum_{n=0}^{\infty} {\frac{f^{(n)} (a)b^n \varepsilon^n}{n!}} \\ &= f(a)+b\frac{df(a)}{da}\varepsilon \\ & \begin{cases} real(f(a+b\epsilon)) = f(a)\\ dual(f(a+b\epsilon)) = b\frac{df(a)}{da} \end{cases} \end{aligned} \end{equation}\]

By choosing \(b=1\), the first derivative comes out for free by simply evaluating the function \(f\).

Hyperdual spaces

We can further extend the dual numbers to a hyperdual space. Let us define a hyperdual space of size 2 as follows, where \(\epsilon_j\) is the \(j\)-th dual number:

\[\begin{equation} \mathbb{D}^2=\mathbb{R}[\epsilon_x, \epsilon_y]=\{z=a+b\epsilon_x+c\epsilon_y+d\epsilon_x\epsilon_y~|~(a,b,c,d)\in\mathbb{R}^4,\epsilon_\gamma^2=0,~\epsilon_\gamma \neq 0,~\gamma\in\{x,y\},~\epsilon_x\epsilon_y \neq 0\} \end{equation}\]

This mathematical tool enables auto-differentiation of multi-variate functions as follows, where \(dual_\gamma\) corresponds to the \(\gamma\)-th dual number, i.e. the number associated with \(\epsilon_\gamma\).

\[\begin{equation} \label{dnintro} \begin{aligned} f:\mathbb{D}^2\rightarrow\mathbb{D}^2,~(x,y)\in\mathbb{R}^2 &\\ & \begin{cases} real(f(x+\epsilon_x,~y+\epsilon_y)) = f(x,y)\\ dual_x(f(x+\epsilon_x,~y+\epsilon_y)) = \frac{\partial}{\partial x}f(x,y) \\ dual_y(f(x+\epsilon_x,~y+\epsilon_y)) = \frac{\partial}{\partial y}f(x,y) \\ \end{cases} \end{aligned} \end{equation}\]

Example

Let us detail a computation example of a smooth multivariate polynomial function defined over all reals.

\[\begin{equation} \begin{aligned} f:\mathbb{R}\rightarrow\mathbb{R},~(x,y)\in\mathbb{R}^2 &\\ & f(x,y) = 2x^3-0.2y^2+x\\ & \frac{\partial}{\partial x} f(x,y) = 6x^2+1\\ & \frac{\partial}{\partial y} f(x,y) = -0.4y\\ \end{aligned} \end{equation}\]

Let us extend the definition of this function to \(\mathbb{D}^2\).

\[\begin{equation} \begin{aligned} g:\mathbb{D}\rightarrow\mathbb{D},~(x,y)\in\mathbb{R}^2 &\\ & g(x+\epsilon_x,~y+\epsilon_y) = 2(x+\epsilon_x)^3-0.2(y+\epsilon_y)^2+(x+\epsilon_x) \end{aligned} \end{equation}\]

Trivially,

\[\begin{equation} \begin{aligned} (x+\epsilon_x)^2 &= x^2 + 2x\epsilon_x\\ (x+\epsilon_x)^3 &= x^3 + 3x^2\epsilon_x \end{aligned} \end{equation}\]

Hence, \(g\) may be written as follows:

\[\begin{equation} \begin{aligned} g(x+\epsilon_x,~y+\epsilon_y) &= 2(x+\epsilon_x)^3-0.2(y+\epsilon_y)^2+(x+\epsilon_x) \\ &= 2(x^3+3x^2\epsilon_x)-0.2(y^2+2y\epsilon_y)+(x+\epsilon_x) \\ &= (2x^3-0.2y^2+x)+(6x^2+1)\epsilon_x-0.4y\epsilon_y\\ \end{aligned} \end{equation}\]

As expected, the \(dual_x\) part of \(g\) corresponds to the partial of \(f\) with respect to \(x\), the \(dual_y\) part of \(g\) corresponds to the partial of \(f\) with respect to \(y\), and the \(real\) part of the \(g\) corresponds to \(f\).

Computation

All hyperdual computations are handled by the hyperdual Rust crate, co-authored by Chris Rabotin.


Last update: 2021-03-09