Natural Log Function Notes

Definition and intuition

  • The natural logarithm, denoted as lnx\ln x, is the inverse function of the natural exponential function exe^x.
    • Inverse relationship: elnx=xe^{\ln x} = x for all x>0x>0 and ln(ex)=x\ln(e^x) = x for all real xx.
    • The base is the constant e2.718281828e\approx 2.718281828…, defined by limits such as e=limn(1+1n)ne = \lim_{n\to\infty}\left(1+\frac{1}{n}\right)^n or as the unique base for which the derivative of exe^x equals itself.
  • Domain of lnx\ln x in real numbers: x>0x>0. Range: (,)(-\infty, \infty).
  • Graphically, lnx\ln x is increasing, passes through (1,0), has a vertical asymptote at x=0+x=0^+, and grows without bound as xx\to\infty while approaching -\infty as x0+x\to 0^+.
  • Practical interpretation: the natural log measures proportional (percentage) changes; it is the inverse of continuous growth modeled by ete^t.

Domain, range, and basic properties

  • Domain: x>0x>0; Range: (,)(-\infty, \infty).
  • Key special values:
    • ln1=0\ln 1 = 0
    • lne=1\ln e = 1
  • Inverse with exponential:
    • elnx=x(x>0)e^{\ln x} = x\quad (x>0)
    • ln(ex)=x(for all x)\ln(e^x) = x\quad (\text{for all } x)
  • Fundamental rules (for a>0,b>0a>0, b>0):
    • ln(ab)=lna+lnb\ln(ab) = \ln a + \ln b
    • ln(ab)=lnalnb\ln\left(\frac{a}{b}\right) = \ln a - \ln b
    • ln(ak)=klna\ln(a^k) = k\ln a
    • ln(xr)=rlnx\ln(x^r) = r\ln x
  • Relationship to other bases (change of base):
    • logbx=lnxlnb\log_b x = \dfrac{\ln x}{\ln b}
    • In particular, base-10 logs relate via log10x=lnxln10\log_{10} x = \dfrac{\ln x}{\ln 10}.
  • Domain nuance: real-valued lnx\ln x is defined only for positive argument; expressions like lnx\ln|x| are used in some contexts (e.g., integrals involving absolute value) but are not the natural log function itself on negative inputs.

Derivative and integral

  • Derivative: for x>0x>0,
    • ddxlnx=1x\frac{d}{dx}\ln x = \frac{1}{x}
  • Integral: for x>0x>0,
    • 1xdx=lnx+C\int \frac{1}{x}\,dx = \ln x + C
  • Relationship to the exponential: derivative of exe^x is exe^x, while the derivative of lnx\ln x is its reciprocal; they are inverse functions.

Graphical features and intuition

  • Monotonicity: strictly increasing on (0,)(0,\infty).
  • Concavity: second derivative d2dx2lnx=1x2<0\dfrac{d^2}{dx^2}\ln x = -\dfrac{1}{x^2} < 0 for all x>0x>0; hence concave down everywhere on its domain.
  • End behavior:
    • As x0+x\to 0^+, lnx\ln x \to -\infty.
    • As xx\to \infty, lnx\ln x \to \infty.
  • Key points:
    • Passes through (1,0)(1,0) and increases slowly for large xx compared to polynomial functions.

Series expansions and approximations

  • Basic Taylor series around x=1x=1 (i.e., in terms of h=x1h = x-1):
    • For h<1|h|<1,
    • ln(1+h)=hh22+h33h44+=n=1(1)n+1hnn.\ln(1+h) = h - \frac{h^2}{2} + \frac{h^3}{3} - \frac{h^4}{4} + \cdots = \sum_{n=1}^{\infty} (-1)^{n+1} \frac{h^n}{n}.
    • This gives a local approximation for values near 1, with convergence for 1<h1-1 < h \le 1, i.e., 0<x20 < x \le 2.
  • Common specific expansion:
    • For x<1|x|<1, ln(1+x)=xx22+x33x44+.\ln(1+x) = x - \frac{x^2}{2} + \frac{x^3}{3} - \frac{x^4}{4} + \cdots.
  • For small deviations around 1: let x=1+tx = 1+t with t<1|t|<1, then
    • lnx=tt22+t33.\ln x = t - \frac{t^2}{2} + \frac{t^3}{3} - \cdots.
  • Practical note: series converge more slowly as you move away from the expansion point; use change of base or other numerical methods for large values.
Numerical examples
  • Quick approximate values:
    • ln20.6931\ln 2 \approx 0.6931
    • ln31.0986\ln 3 \approx 1.0986
    • ln71.9459\ln 7 \approx 1.9459
    • ln102.3026\ln 10 \approx 2.3026
  • Exact/inverse example:
    • If lnx=3\ln x = 3, then x=e320.0855x = e^3 \approx 20.0855.

Applications and connections

  • Inverse relationship with the exponential function makes lnx\ln x central in solving equations of the form at=xa^t = x, leading to t=logax=lnxlnat = \log_a x = \dfrac{\ln x}{\ln a}.
  • In calculus and analysis:
    • Areas under the hyperbola: the area under y=1xy = \frac{1}{x} from 1 to a is 1a1xdx=lna\int_1^a \frac{1}{x}\,dx = \ln a.
    • Growth and decay models with continuous compounding use erte^{rt} and natural logs for analytic solutions.
  • In statistics and data science, log-transformations with base ee stabilize variance and linearize multiplicative relationships.

Practice problems (conceptual)

  • Solve for x: lnx=2\ln x = 2x=e2.x = e^2\,.
  • Solve for x: lnx=ln5\ln x = \ln 5x=5.x = 5\,.
  • Change of base: express log<em>381\log<em>3 81 using natural logs: log</em>381=ln81ln3=4.\log</em>3 81 = \dfrac{\ln 81}{\ln 3} = 4.
  • If ln(2x)=1\ln(2x) = 1, find x: 2x=e1=e2x = e^1 = ex=e2x = \dfrac{e}{2}.

Common pitfalls and practical tips

  • Domain trap: never take lnx\ln x for nonpositive x  (x0)x\; (x \le 0) in real-valued contexts.
  • Remember base-10 vs natural logarithm: many calculators have a ln button (base ee) and a log button (base 10) separately; convert using log10x=lnxln10\log_{10} x = \dfrac{\ln x}{\ln 10} if needed.
  • When solving equations involving lnx\ln x, check that the solution lies in the domain x>0x>0.
  • Use the derivative to check monotonicity: since ddxlnx=1x>0\frac{d}{dx}\ln x = \frac{1}{x} > 0 for all x>0x>0, the function is strictly increasing.
  • Be mindful of the absolute value when integrating: 1xdx=lnx+C\int \frac{1}{x}\,dx = \ln|x| + C in a context where the domain may cross zero; for strictly positive arguments, this reduces to \ln x + C).

Quick reference formulas (LaTeX-ready)

  • Basic log rules:
    • \ln(ab)=\ln a+\ln b,\quad \ln\left(\frac{a}{b}\right)=\ln a-\ln b,\quad \ln(a^k)=k\ln a.
  • Special values:
    • \ln 1 = 0,\quad \ln e = 1.
  • Derivative and integral:
    • \frac{d}{dx}\ln x = \frac{1}{x},\quad x>0.
    • \int \frac{1}{x}\,dx = \ln x + C,\quad x>0.
  • Change of base:
    • \log_b a = \frac{\ln a}{\ln b}.
  • Inverse relationships:
    • e^{\ln x} = x,\quad \ln(e^x) = x.
  • Series (around 0 for ln(1+x)):
    • \ln(1+x) = \sum_{n=1}^{\infty} (-1)^{n+1}\frac{x^n}{n},\quad -1<x\le 1.$$

Summary

  • The natural logarithm is a fundamental, well-behaved function on its domain that links linear and exponential growth, provides a powerful tool for solving equations, computing areas, and modeling continuous processes. Mastery of its rules, derivatives, integrals, and series is essential for core calculus, analysis, and applied contexts.