Exponential function

As a function of the real variable x, the graph of y=e^x is always positive (above the x axis) and increasing (viewed left-to-right). It never touches the x axis, although it gets arbitrarily close to it (thus, the x axis is a horizontal asymptote to the graph). Its inverse function, the natural logarithm, ln(x), is defined for all positive x.

Sometimes, especially in the sciences, the term exponential function is more generally used for functions of the form ka^x, where a, called the base, is any positive real number not equal to one. This article will focus initially on the exponential function with base e, Euler's number.

In general, the variable x can be any real or complex number, or even an entirely different kind of mathematical object; see the formal definition below.

Some of the applications of the exponential function include modeling decay and/or growth in populations, economics, fatigue of materials, and amounts of radioactive material.

Properties

Most simply, exponential functions multiply at a constant rate. For example the population of a bacterial culture which doubles every 20 minutes can (approximatively, as this is not really a continuous problem) be expressed as an exponential, as can the value of a car which decreases by 10% per year.

Using the natural logarithm, one can define more general exponential functions. The function

$\,\!\,a^{x}=(e^{\ln a})^{x}=e^{x\ln a}$

defined for all a > 0, and all real numbers x, is called the exponential function with base a. Note that this definition of $\,a^{x}$ rests on the previously established existence of the function $\,e^{x}$, defined for all real numbers. (Here, we neither formally nor conceptually clarify whether such a function exists or what non-natural exponents are supposed to mean.)

Note that the equation above holds for a = e, since

$\,\!\,e^{x\ln e}=e^{x\cdot 1}=e^{x}.$

Exponential functions "translate between addition and multiplication" as is expressed in the first three and the fifth of the following exponential laws:

$\,\!\,a^{0}=1$

$\,\!\,a^{1}=a$

$\,\!\,a^{x+y}=a^{x}a^{y}$

$\,\!\,a^{xy}=\left(a^{x}\right)^{y}$

$\,\!\,{1 \over a^{x}}=\left({1 \over a}\right)^{x}=a^{-x}$

$\,\!\,a^{x}b^{x}=(ab)^{x}$

These are valid for all positive real numbers a and b and all real numbers x and y. Expressions involving fractions and roots can often be simplified using exponential notation:

$\,{1 \over a}=a^{-1}$

and, for any a > 0, real number b, and integer n > 1:

$\,{\sqrt[{n}]{a^{b}}}=\left({\sqrt[{n}]{a}}\right)^{b}=a^{b/n}.$

Derivatives and differential equations

The importance of exponential functions in mathematics and the sciences stems mainly from properties of their derivatives. In particular,

$\,{d \over dx}e^{x}=e^{x}$

That is, e^x is its own derivative. Functions of the form $\,Ke^{x}$ for constant K are the only functions with that property. (This follows from the Picard-Lindelöf theorem, with $\,y(t)=e^{t},y(0)=K$ and $\,f(t,y(t))=y(t)$.) Other ways of saying the same thing include:

• The slope of the graph at any point is the height of the function at that point.
• The rate of increase of the function at x is equal to the value of the function at x.
• The function solves the differential equation $\,y'=y$.
• exp is a fixed point of derivative as a functional

In fact, many differential equations give rise to exponential functions, including the Schrödinger equation and the Laplace's equation as well as the equations for simple harmonic motion.

For exponential functions with other bases:

$\,{d \over dx}a^{x}=(\ln a)a^{x}$

Thus any exponential function is a constant multiple of its own derivative.

If a variable's growth or decay rate is proportional to its size — as is the case in unlimited population growth (see Malthusian catastrophe), continuously compounded interest, or radioactive decay — then the variable can be written as a constant times an exponential function of time.

Furthermore for any differentiable function f(x), we find, by the chain rule:

$\,{d \over dx}e^{f(x)}=f'(x)e^{f(x)}$.

Computing exp(x) for real x

An even better algorithm can be found as follows.

First, notice that the answer y = e^x is usually a floating point number represented by a mantissa m and an exponent n so y = m 2ⁿ for some integer n and suitably small m. Thus, we get:

$\,y=m\,2^{n}=e^{x}.$

Taking log on both sides of the last two gives us:

$\,\ln(y)=\ln(m)+n\ln(2)=x.$

Thus, we get n as the result of dividing x by log(2) and finding the greatest integer that is not greater than this - that is, the floor function:

$\,n=\left\lfloor {\frac {x}{\ln(2)}}\right\rfloor .$

Having found n we can then find the fractional part u like this:

$\,u=x-n\ln(2).$

The number u is small and in the range 0 ≤ u < ln(2) and so we can use the previously mentioned series to compute m:

$\,m=e^{u}=1+u(1+u({\frac {1}{2!}}+u({\frac {1}{3!}}+u(....)))).$

Having found m and n we can then produce y by simply combining those two into a floating point number:

$\,y=e^{x}=m\,2^{n}.$

Computation of $\,a^{b}$ where both a and b are complex

This is also straightforward given the formulae:

if a = x + yi and b = u + vi we can first convert a to polar co-ordinates by finding a $\,\theta$ and an $\,r$ such that:

$\,re^{{\theta }i}=r\cos \theta +ir\sin \theta =a=x+yi$

or

$\,x=r\cos \theta$ and $\,y=r\sin \theta .$

Thus, $\,x^{2}+y^{2}=r^{2}$ or $\,r={\sqrt {x^{2}+y^{2}}}$ and $\,\tan \theta ={\frac {y}{x}}$ or $\,\theta =\operatorname {atan2} (y,x).$

Now, we have that:

$\,a=re^{{\theta }i}=e^{\log(r)+{\theta }i}$

so:

$\,a^{b}=(e^{\log(r)+{\theta }i})^{u+vi}=e^{(\log(r)+{\theta }i)(u+vi)}$

The exponent is thus a simple multiplication of two complex values yielding a complex result which can then be brought back to regular cartesian format by the formula:

$\,e^{p+qi}=e^{p}(\cos(q)+i\sin(q))=e^{p}\cos(q)+ie^{p}\sin(q)$

where p is the real part of the multiplication:

$\,p=u\log(r)-v\theta$

and q is the imaginary part of the multiplication:

$\,q=v\log(r)+u\theta .$

Note that all of $\,x,y,u,v,r,$ $\,\theta$, $\,p$ and $\,q$ are all real values in these computations. The result of $\,a^{b}$ is thus $\,p+qi$.

Also note that since we compute and use $\,\log(r)$ rather than r itself you don't have to compute the square root. Instead simply compute $\,\log(r)={\frac {1}{2}}\log(x^{2}+y^{2})$. Watch out for potential overflow though and possibly scale down the x and y prior to computing $\,x^{2}+y^{2}$ by a suitable power of 2 if $\,x$ and $\,y$ are so large that you would overflow. If you instead run the risk of underflow, scale up by a suitable power of 2 prior to computing the sum of the squares. In either case you then get the scaled version of $\,x$ - we can call it $\,x'$ and the scaled version of $\,y$ - call it $\,y'$ and so you get:

$\,x=x'2^{s}$ and $\,y=y'2^{s}$

where $\,2^{s}$ is the scaling factor.

Then you get $\,\log(r)={\frac {1}{2}}(\log(x'^{2}+y'^{2})+s)$ where $\,x'$ and $\,y'$ are scaled so that the sum of the squares will not overflow or underflow. If $\,x$ is very large while $\,y$ is very small so that you cannot find such a scaling factor you will overflow anyway and so the sum is essentially equal to $\,x^{2}$ since y is ignored and thus you get $\,r=|x|$ in this case and $\,\log(r)=\log(|x|)$. The same happens in the case when $\,x$ is very small and $\,y$ is very large. If both are very large or both are very small you can find a scaling factor as mentioned earlier.

Note that this function is, in general, multivalued for complex arguments. This is because rotation of a single point through any angle plus 360 degrees, or $2\pi$ radians, is the same as rotation through the angle itself. So $\theta$ above is not unique: $\theta _{k}=\theta +2\pi k$ for any integer $k$ would do as well. The convention though is that when $a^{b}$ is taken as a single value it must be that for $k=0$, ie. we use the smallest possible (in magnitude) value of theta, which has a magnitude of, at most, $\pi$.

Matrices and Banach algebras

The definition of the exponential function given above can be used verbatim for every Banach algebra, and in particular for square matrices (in which case the function is called the matrix exponential). In this case we have

$\,\ e^{x+y}=e^{x}e^{y}{\mbox{ if }}xy=yx$

$\,\ e^{0}=1$

$\,\ e^{x}$ is invertible with inverse $\,\ e^{-x}$

the derivative of $\,\ e^{x}$ at the point $\,\ x$ is that linear map which sends $\,\ u$ to $\,\ ue^{x}$.

In the context of non-commutative Banach algebras, such as algebras of matrices or operators on Banach or Hilbert spaces, the exponential function is often considered as a function of a real argument:

$\,\ f(t)=e^{tA}$

where A is a fixed element of the algebra and t is any real number. This function has the important properties

$\,\ f(s+t)=f(s)f(t)$

$\,\ f(0)=1$

$\,\ f'(t)=Af(t)$

Double exponential function

The term double exponential function can have two meanings:

• a function with two exponential terms, with different exponents
• a function $\,f(x)=a^{a^{x}}$; this grows even faster than an exponential function; for example, if a = 10: f(−1) = 1.26, f(0) = 10, f(1) = 10¹⁰, f(2) = 10¹⁰⁰ = googol, ..., f(100) = googolplex.

Factorials grow faster than exponential functions, but slower than double-exponential functions. Fermat numbers, generated by $\,F(m)=2^{2^{m}}+1$ and double Mersenne numbers generated by $\,MM(p)=2^{(2^{p}-1)}-1$ are examples of double exponential functions.

See also

• e (mathematical constant)
• Characterizations of the exponential function
• Exponential growth
• Exponentiation
• List of integrals of exponential functions
• List of exponential topics

References

ISBN links support NWE through referral fees

• Konyagin, Sergei and Igor Shparlinski. 1999. Character Sums with Exponential Functions and their Applications. Cambridge, UK: Cambridge University Press. ISBN 0521642639.
• Fried, H.M. 2002. Green's Functions and Ordered Exponentials. Cambridge, UK: Cambridge University Press. ISBN 0521443903.
• Carico, Charles C. 1974. Exponential and logarithmic functions (Wadsworth precalculus mathematics series). Belmont, CA: Wadsworth Pub. Co. ISBN 0534003141.

External links

• Complex exponential function. Retrieved September 9, 2007.
• Derivative of exponential function. Retrieved September 9, 2007.
• Weisstein, Eric W. Exponential Function. Retrieved September 9, 2007.
• Mathews, John H. Complex Exponential Function Module. Retrieved September 9, 2007.
• Taylor Series Expansions of Exponential Functions. efunda. Retrieved September 9, 2007.
• Complex exponential interactive graphic. Retrieved September 9, 2007.

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