Properties of Exponential Functions from the Functional Equation

Positivity, monotonicity, and convexity from E(x+y)=E(x)E(y).

Here is a functional characterization of exponentials; we don’t specify a formula for how to compute the function but instead we specify how the function ought to behave.

Exponential Functions

An exponential function is a continuous nonconstant function E ⁣:RRE\colon\mathbb{R}\to\mathbb{R} satisfying the law of exponents E(x+y)=E(x)E(y)E(x+y)=E(x)E(y) for all x,yRx,y\in\mathbb{R}.

This note records several properties that follow directly from this functional equation (which prove useful in Part II and III, discussing differentiation and integration). This is material preparing for real analysis, where I am teaching the exponential logarithm and trigonometric functions from a functional-characterization perspective this year.

Positivity

Exponentials are Nonzero

If EE is an exponential function then E(x)0E(x)\neq 0 for all xx.

Let EE be an exponential function and assume there is some zRz\in\RR such that E(z)=0E(z)=0. Then for any xRx\in\RR we may write x=xz+z=(xz)+z=y+zx=x-z+z=(x-z)+z=y+z for y=xzRy=x-z\in\RR. Evaluating E(x)E(x) using the law of exponents, E(x)=E(y+z)=E(y)E(z)=E(y)0=0E(x)=E(y+z)=E(y)E(z)=E(y)\cdot 0 =0 Thus EE is constantly zero, which is a contradiction as we assumed EE was a nonconstant solution to the Law of Exponents.

E(0)=1

If EE is any exponential function, then E(0)=1E(0)=1.

Since 0=0+00=0+0 apply the law of exponents: E(0)=E(0)E(0)E(0)=E(0)E(0) Since we know E(0)E(0) to be nonzero we can divide through by it, yielding 1=E(0)1=E(0)

Because exponentials are continuous (by definition), are nonzero (the proposition above) and return the positive number 11 at x=0x=0 (the other proposition above), the intermediate value theorem ensures exponentials can never have negative number outputs.

Exponential functions are positive.

Uniqueness

Exponential on Natural Numbers

Prove that if EE is an exponential function, xRx\in\RR and nNn\in\mathbb{N} then E(nx)=E(x)nE\left(nx\right)=E(x)^{n}

Since nx=x+x++xnx=x+x+\cdots+x, we may inductively apply the law of exponents: E(x+x++xn)=E(x)E(x)E(x)n=E(x)nE\left(\underbrace{x+x+\cdots+x}_n\right)=\underbrace{E(x)E(x)\cdots E(x)}_n=E(x)^n

Exponential on Integers

Prove that if EE is an exponential function, xRx\in\RR and jZj\in\mathbb{Z} then E(jx)=E(x)jE\left(jx\right)=E(x)^{j}

If jj is positive, the result is already proven for natural numbers above. If j=0j=0 then the claim reduces to E(0)=1E(0)=1, also already proven. So, it remains to consider only the case j=nj=-n for nNn\in\mathbb{N}. Here, we apply the law of exponents to nn=0n-n=0 to get 1=E(0)=E(nxnx)=E(nx)E(nx)1=E(0)=E(nx-nx)=E(nx)E(-nx) Thus E(nx)=1/E(nx)E(-nx)=1/E(nx), and we know E(nx)=E(x)nE(nx)=E(x)^n from the natural number case. Putting this together with the definition of negative exponents, E(jx):=E(nx)=1E(x)n=E(x)n=E(x)jE(jx):=E(-nx)=\frac{1}{E(x)^n}=E(x)^{-n}=E(x)^j

Exponential on Rationals

Prove that if EE is an exponential function, xRx\in\RR and rQr\in\mathbb{Q} then E(xr)=E(x)rE\left(xr\right)=E(x)^{r}

Let r=p/qr=p/q for integers p,qp,q. We can assume without loss of generality that p0p\neq 0 (as we’ve covered this case) and q>1q > 1 (q=0q=0 is not allowed, and we can always collect negative signs into the numerator, and q=1q=1 is the integer case, also already covered.)

We proceed in two steps: first we look at fractions of the form 1/n1/n, so we must evaluate E(1nx)E(\frac{1}{n}x). Here we apply the law of exponents to the identity 1=1n+1n++1n1=\frac{1}{n}+\frac{1}{n}+\cdots+\frac{1}{n}:

E(x)=E(xn+xn++xnn)=E(xn)E(xn)E(xn)n=E(xn)n\begin{align} E(x)&=E\left(\underbrace{\tfrac{x}{n}+\tfrac{x}{n}+\cdots+\tfrac{x}{n}}_n\right)\\ &=\underbrace{E\left(\tfrac{x}{n}\right)E\left(\tfrac{x}{n}\right)\cdots E\left(\tfrac{x}{n}\right)}_n\\ &=E\left(\tfrac{x}{n}\right)^n \end{align}

Since E(x)E(x), E(x/n)E(x/n) are known to be positive, we can uniquely take the nthn^{th} root of both sides to get

E(x)1n=E(1nx)E(x)^{\frac{1}{n}}=E\left(\tfrac{1}{n}x\right)

Now let r=p/qr=p/q be an arbitrary fraction, and consider E(pqx)E(\tfrac{p}{q}x). We compute as

E(pqx)=E(p[1qx])=E(1qx)p=(E(x)p)1q=E(x)pq\begin{align} E\left(\tfrac{p}{q}x\right) &= E\left( p\left[\tfrac{1}{q}x\right]\right)\\ &=E\left(\tfrac{1}{q}x\right)^p\\ &= \left(E\left(x\right)^p\right)^{\frac{1}{q}}\\ &= E(x)^\frac{p}{q} \end{align}

Thus E(rx)=E(x)rE(rx)=E(x)^r as claimed.

Exponentials Agreeing at a Point

If E,FE,F are exponentials which take the same value at any nonzero point cc, then they agree on the entire real line.

Assume E(c)=F(c)=aE(c)=F(c)=a, and consider the set SS of rational multiples of cc: S={crrQ} S=\{ c r\mid r\in\mathbb{Q}\} This is dense in R\RR and for every sSs\in S we can calculate E(s)E(s) and F(s)F(s) using the previous proposition E(s)=E(rc)=E(c)r=arE(s)=E(rc)=E(c)^r=a^r F(s)=F(rc)=F(c)r=arF(s)=F(rc)=F(c)^r=a^r Thus E(s)=F(s)E(s)=F(s) on all of SS, so the functions agree on a dense set, and by continuity, agree on all of R\RR.

Base of an Exponential

If EE is an exponential function, its base is defined as the value a=E(1)a=E(1).

Uniqueness with Given Base

If two exponentials have the same base, they are equal on the entire real line.

By defintion they agree at 11, so apply the previous proposition.

Monotonicity & Convexity

If EE is an exponential, then restricted to the positive reals E(x)E(x) is either (i) always greater than 1, or (ii) always less than 1.

Assume there are two positive numbers a,ba,b with E(a)>1E(a) > 1 and E(b)<1E(b) < 1. Then by the intermediate value theorem there must be a point c(a,b)c\in (a,b) where E(c)=1E(c)=1.
Now consider the set of rational multiples of cc: S={crrQ} S=\{ c r\mid r\in\mathbb{Q}\} This is dense in R\RR and for every element sSs\in S we see E(s)=E(rc)=E(c)r=1r=1E(s)=E(rc)=E(c)^r=1^r=1 Thus EE is constantly equal to 1 on the dense set SS, and so by continuity is constantly equal to 11 on all of R\RR. This contradicts the definition of exponentials, but even more immediately contradicts the premise of this proposition, that E(a)>1E(a) >1 and E(b)<1E(b) <1.

Exponentials are Monotone

If EE is an exponential function then EE is strictly monotone: it is monotone increasing if E(x)>1E(x) > 1 on the positive reals, and decreasing if E(x)<1E(x) < 1 there.

Without loss of generality we work with the case that E>1E > 1 on the positives. Let x<yx < y be arbitrary real numbers, we wish to show that E(x)<E(y)E(x) < E(y). Since yx>0y-x > 0 we know E(yx)>1E(y-x) > 1 and by the law of exponents E(y)=E(yx+x)=E(yx)E(x)>1E(x)E(y)= E(y-x+x)=E(y-x)E(x) > 1 E(x) So, E(y)>E(x)E(y) > E(x) as required.

Next we look at convexity

Convex Function

A function ff is convex on an interval if the secant line between any two points in the interval lies strictly above the graph of ff.

Exponentials are Convex

Let EE be an exponential. Then EE is convex on all of R\mathbb{R}.

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