Chapter 9: Problem 13
Find the Maclaurin polynomials of orders \(n=0,1,2,3\), and 4, and then find the \(n\) th Maclaurin polynomials for the function in sigma notation. $$ \cosh x $$
Short Answer
Expert verified
P_n(x) = \sum_{k=0}^{\lfloor n/2 \rfloor} \frac{x^{2k}}{(2k)!} is the nth Maclaurin polynomial for \( \cosh x \).
Step by step solution
01
Understand Maclaurin Series
The Maclaurin series of a function \( f(x) \) is a Taylor series expansion about 0: \( f(x) = f(0) + f'(0)x + \frac{f''(0)}{2!}x^2 + \frac{f'''(0)}{3!}x^3 + \ldots \). For \( n \)-th order polynomial, use terms up to \( f^{(n)}(0)x^n \).
02
Evaluate Derivatives of \( \cosh x \)
The function is \( \cosh x = \frac{e^x + e^{-x}}{2} \). Calculate derivatives as: - \( f(0) = \cosh(0) = 1 \) - \( f'(x) = \sinh x, \ f'(0) = 0 \) - \( f''(x) = \cosh x, \ f''(0) = 1 \) - \( f'''(x) = \sinh x, \ f'''(0) = 0 \) - \( f^{(4)}(x) = \cosh x, \ f^{(4)}(0) = 1 \)
03
Construct Maclaurin Polynomial for \( n=0 \)
For \( n=0 \), the Maclaurin polynomial is simply the value of the function at zero: \( P_0(x) = 1 \).
04
Construct Maclaurin Polynomial for \( n=1 \)
The first order polynomial is: \( P_1(x) = 1 + 0\cdot x = 1 \), since the first derivative at zero is 0.
05
Construct Maclaurin Polynomial for \( n=2 \)
The second order polynomial is: \( P_2(x) = 1 + 0\cdot x + \frac{1}{2!}x^2 = 1 + \frac{x^2}{2} \).
06
Construct Maclaurin Polynomial for \( n=3 \)
For the third order polynomial: \( P_3(x) = 1 + 0\cdot x + \frac{1}{2}x^2 + 0 \cdot x^3 = 1 + \frac{x^2}{2} \).
07
Construct Maclaurin Polynomial for \( n=4 \)
The fourth order polynomial is: \( P_4(x) = 1 + 0 \cdot x + \frac{1}{2}x^2 + 0 \cdot x^3 + \frac{1}{4!}x^4 = 1 + \frac{x^2}{2} + \frac{x^4}{24} \).
08
Find General Maclaurin Polynomial in Sigma Notation
The nth Maclaurin polynomial in sigma notation is: \[ P_n(x) = \sum_{k=0}^{\lfloor n/2 \rfloor} \frac{x^{2k}}{(2k)!} \], as only even powers contribute due to odd derivatives being zero.
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Taylor Series
A Taylor series is essentially a powerful way of approximating complex functions with an infinite sum of polynomial terms. This technique involves taking the derivatives of a function at a particular point — often zero, which is specifically known as a Maclaurin series.
The general form for Taylor series of a function \( f(x) \) about a value \( a \) is expressed as:
The general form for Taylor series of a function \( f(x) \) about a value \( a \) is expressed as:
- \( f(x) = f(a) + f'(a)(x-a) + \frac{f''(a)}{2!}(x-a)^2 + \frac{f'''(a)}{3!}(x-a)^3 + \ldots \).
Hyperbolic Functions
Hyperbolic functions are analogs of trigonometric functions but are based on hyperbolas instead of circles. A key hyperbolic function is the hyperbolic cosine, \( \cosh x \). This function can be expressed as:
Just like trigonometric functions, hyperbolic functions also have derivatives:
- \( \cosh x = \frac{e^x + e^{-x}}{2} \).
Just like trigonometric functions, hyperbolic functions also have derivatives:
- Derivative of \( \cosh x \) is \( \sinh x \).
- Derivative of \( \sinh x \) is \( \cosh x \).
Polynomial Approximation
Polynomial approximation allows us to represent complex functions as sums of polynomials up to a certain degree. The idea is to use simpler polynomial functions to approximate more complex functions.
When constructing a Maclaurin polynomial, we only need to consider terms up to a certain order, \( n \), in order to approximate the function closely. For instance, when approximating \( \cosh x \), we can express it as:
When constructing a Maclaurin polynomial, we only need to consider terms up to a certain order, \( n \), in order to approximate the function closely. For instance, when approximating \( \cosh x \), we can express it as:
- \( P_0(x) = 1 \) — first term for \( n=0 \)
- \( P_1(x) = 1 \) — for \( n=1 \), due to zero first derivative
- \( P_2(x) = 1 + \frac{x^2}{2} \)
- \( P_3(x) = 1 + \frac{x^2}{2} \)
- \( P_4(x) = 1 + \frac{x^2}{2} + \frac{x^4}{24} \)
Derivatives
Derivatives measure how a function changes as its input changes. When constructing a Taylor or Maclaurin series, derivatives play a key role in determining each term of the approximation. They provide the coefficients for each polynomial term in the series expansion.
For \( \cosh x \), we compute several derivatives at \( x = 0 \):
For \( \cosh x \), we compute several derivatives at \( x = 0 \):
- \( f(0) = 1 \)
- First derivative: \( f'(x) = \sinh x, \ f'(0) = 0 \)
- Second derivative: \( f''(x) = \cosh x, \ f''(0) = 1 \)
- Third derivative: \( f'''(x) = \sinh x, \ f'''(0) = 0 \)
- Fourth derivative: \( f^{(4)}(x) = \cosh x, \ f^{(4)}(0) = 1 \)