β—€ Back to Note

Tony's Intertwingled Memex β€’ Reference Manual

Growth Rates of Functions

Formulas & Definitions
Core Definition

In mathematical analysis and engineering algorithm design, the relative growth rate of two functions as xβ†’βˆžx \to \inftyxβ†’βˆž describes which function dominates asymptotically.

A function g(x)g(x)g(x) is said to grow faster than f(x)f(x)f(x) as xβ†’βˆžx \to \inftyxβ†’βˆž if:

lim⁑xβ†’βˆžf(x)g(x)=0(orΒ equivalently,Β lim⁑xβ†’βˆžg(x)f(x)=∞)\lim_{x \to \infty} \frac{f(x)}{g(x)} = 0 \quad \left(\text{or equivalently, } \lim_{x \to \infty} \frac{g(x)}{f(x)} = \infty\right)xβ†’βˆžlim​g(x)f(x)​=0(orΒ equivalently,Β xβ†’βˆžlim​f(x)g(x)​=∞)
Two functions have comparable growth rates if lim⁑xβ†’βˆžf(x)g(x)=M\lim_{x \to \infty} \frac{f(x)}{g(x)} = Mlimxβ†’βˆžβ€‹g(x)f(x)​=M for some non-zero finite constant M>0M > 0M>0.


Concept Explanation

1. The Asymptotic Dominance Hierarchy

When evaluating limits at infinity involving ratios of disparate function families, L'HΓ΄pital's Rule rigorously confirms the universal hierarchy of asymptotic growth:

ln⁑(ln⁑x)β‰ͺln⁑xβ‰ͺxpβ‰ͺaxβ‰ͺx!β‰ͺxx(p>0,β€…β€Ša>1)\ln(\ln x) \ll \ln x \ll x^p \ll a^x \ll x! \ll x^x \qquad (p > 0, \; a > 1)ln(lnx)β‰ͺlnxβ‰ͺxpβ‰ͺaxβ‰ͺx!β‰ͺxx(p>0,a>1)

  Rate of Growth as x ──> ∞
   β–²
   β”‚                                   / Exponential (e^x, 2^x)
   β”‚                                 /
   β”‚                               /  / Power / Polynomial (x^3, x^2)
   β”‚                             /  /
   β”‚                           /  /  / Linear (x)
   β”‚                         /  /  /
   β”‚                       /  /  /  / Square Root (x^0.5)
   β”‚                     /  /  /  /
   β”‚                   /  /  /  /  / Logarithmic (ln x)
   β”‚                 /  /  /  /  /
   0────────────────────────────────────────► x

2. Proof of Exponential Dominance via L'HΓ΄pital's Rule

Consider the ratio of any positive integer power of xxx to the natural exponential exe^xex:

lim⁑xβ†’βˆžxnex\lim_{x \to \infty} \frac{x^n}{e^x}xβ†’βˆžlim​exxn​
Direct substitution gives the indeterminate form ∞∞\frac{\infty}{\infty}βˆžβˆžβ€‹. Applying L'HΓ΄pital's Rule nnn consecutive times:
lim⁑xβ†’βˆžxnex=L’Hlim⁑xβ†’βˆžnxnβˆ’1ex=L’Hlim⁑xβ†’βˆžn(nβˆ’1)xnβˆ’2ex=β‹―=lim⁑xβ†’βˆžn!ex\lim_{x \to \infty} \frac{x^n}{e^x} \overset{\text{L'H}}{=} \lim_{x \to \infty} \frac{n x^{n-1}}{e^x} \overset{\text{L'H}}{=} \lim_{x \to \infty} \frac{n(n-1)x^{n-2}}{e^x} = \cdots = \lim_{x \to \infty} \frac{n!}{e^x}xβ†’βˆžlim​exxn​=L’Hxβ†’βˆžlim​exnxnβˆ’1​=L’Hxβ†’βˆžlim​exn(nβˆ’1)xnβˆ’2​=β‹―=xβ†’βˆžlim​exn!​
Because the numerator is reduced to a static constant (n!n!n!) while the denominator continues to grow without bound (exβ†’βˆže^x \to \inftyexβ†’βˆž), the limit is strictly:
lim⁑xβ†’βˆžn!ex=0\lim_{x \to \infty} \frac{n!}{e^x} = 0xβ†’βˆžlim​exn!​=0
Fundamental Takeaway: Any exponential function with base a>1a > 1a>1 eventually outgrows any polynomial function, no matter how large the power nnn or how small the base aaa.

3. Logarithmic Subordinance

Similarly, the natural logarithm grows slower than any positive power of xxx, even extremely small fractional powers like x0.01x^{0.01}x0.01:

lim⁑xβ†’βˆžln⁑xxp=L’Hlim⁑xβ†’βˆž1xpxpβˆ’1=lim⁑xβ†’βˆž1pxp=0(p>0)\lim_{x \to \infty} \frac{\ln x}{x^p} \overset{\text{L'H}}{=} \lim_{x \to \infty} \frac{\frac{1}{x}}{p x^{p-1}} = \lim_{x \to \infty} \frac{1}{p x^p} = 0 \quad (p > 0)xβ†’βˆžlim​xplnx​=L’Hxβ†’βˆžlim​pxpβˆ’1x1​​=xβ†’βˆžlim​pxp1​=0(p>0)
This mathematical reality underpins the extreme efficiency of binary search trees and logarithmic database indexing algorithms in computer engineering.


Engineering Applications

  • Computer Science & Software Engineering (Algorithmic Complexity): The Big-OOO runtime efficiency of search and sorting algorithms is governed by growth rates. Algorithms scaling as O(log⁑n)O(\log n)O(logn) or O(nlog⁑n)O(n \log n)O(nlogn) (like MergeSort) remain highly performant for billion-element datasets, whereas O(n2)O(n^2)O(n2) or O(2n)O(2^n)O(2n) algorithms suffer exponential execution timeouts.
  • Electrical & Control Engineering (Transient Decay vs. Steady State): In circuit stability analysis, transient decay terms governed by eβˆ’Ξ±ttke^{-\alpha t} t^keβˆ’Ξ±ttk must vanish as tβ†’βˆžt \to \inftytβ†’βˆž. L'HΓ΄pital's Rule proves that negative exponential dampening always overpowers polynomial voltage surges.

Example Problems

Example 1: Comparing Polynomial and Exponential Growth

Evaluate lim⁑xβ†’βˆž3x2+500xe0.2x\lim_{x \to \infty} \frac{3x^2 + 500x}{e^{0.2x}}limxβ†’βˆžβ€‹e0.2x3x2+500x​.

Solution

Step 1: Check form As xβ†’βˆžx \to \inftyxβ†’βˆž, both numerator and denominator diverge to ∞\infty∞. Form: ∞∞\frac{\infty}{\infty}βˆžβˆžβ€‹.

Step 2: First application of L'HΓ΄pital's Rule

lim⁑xβ†’βˆž3x2+500xe0.2x=L’Hlim⁑xβ†’βˆž6x+5000.2e0.2x\lim_{x \to \infty} \frac{3x^2 + 500x}{e^{0.2x}} \overset{\text{L'H}}{=} \lim_{x \to \infty} \frac{6x + 500}{0.2 e^{0.2x}}xβ†’βˆžlim​e0.2x3x2+500x​=L’Hxβ†’βˆžlim​0.2e0.2x6x+500​
Form: ∞∞\frac{\infty}{\infty}βˆžβˆžβ€‹.

Step 3: Second application of L'HΓ΄pital's Rule

lim⁑xβ†’βˆž6x+5000.2e0.2x=L’Hlim⁑xβ†’βˆž6(0.2)2e0.2x=lim⁑xβ†’βˆž60.04e0.2x=lim⁑xβ†’βˆž150e0.2x\lim_{x \to \infty} \frac{6x + 500}{0.2 e^{0.2x}} \overset{\text{L'H}}{=} \lim_{x \to \infty} \frac{6}{(0.2)^2 e^{0.2x}} = \lim_{x \to \infty} \frac{6}{0.04 e^{0.2x}} = \lim_{x \to \infty} \frac{150}{e^{0.2x}}xβ†’βˆžlim​0.2e0.2x6x+500​=L’Hxβ†’βˆžlim​(0.2)2e0.2x6​=xβ†’βˆžlim​0.04e0.2x6​=xβ†’βˆžlim​e0.2x150​

Step 4: Evaluate As xβ†’βˆžx \to \inftyxβ†’βˆž, e0.2xβ†’βˆže^{0.2x} \to \inftye0.2xβ†’βˆž, so:

150∞=0\frac{150}{\infty} = 0∞150​=0

Example 2: Comparing Logarithms and Roots

Evaluate lim⁑xβ†’βˆž(ln⁑x)3x\lim_{x \to \infty} \frac{(\ln x)^3}{\sqrt{x}}limxβ†’βˆžβ€‹x​(lnx)3​.

Solution

Step 1: Form ∞∞\frac{\infty}{\infty}βˆžβˆžβ€‹.

Step 2: Differentiate Using the Chain Rule on the numerator:

lim⁑xβ†’βˆž3(ln⁑x)2β‹…1x12x=lim⁑xβ†’βˆž6(ln⁑x)2x\lim_{x \to \infty} \frac{3(\ln x)^2 \cdot \frac{1}{x}}{\frac{1}{2\sqrt{x}}} = \lim_{x \to \infty} \frac{6(\ln x)^2}{\sqrt{x}}xβ†’βˆžlim​2x​1​3(lnx)2β‹…x1​​=xβ†’βˆžlim​x​6(lnx)2​

Step 3: Successive applications Repeating L'HΓ΄pital's Rule two more times will reduce the numerator powers of ln⁑x\ln xlnx until only a constant remains in the numerator while x\sqrt{x}x​ remains in the denominator. Therefore:

lim⁑xβ†’βˆž(ln⁑x)3x=0\lim_{x \to \infty} \frac{(\ln x)^3}{\sqrt{x}} = 0xβ†’βˆžlim​x​(lnx)3​=0


Connections & References

  • Parent Concepts:
    • Limits at Infinity
    • L'HΓ΄pital's Rule
  • Related Notes:
    • Indeterminate Forms
  • Course Sessions:
    • Session 12 - L’Hopital’s Rule and Indeterminate Forms