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Problem Set

Problem 1. Let A,B⊆RA, B \subseteq \mathbb{R} be non-empty and bounded above. Prove that sup⁡(A∪B)=max⁡(sup⁡A,sup⁡B)\sup(A \cup B) = \max(\sup A, \sup B).

Solution

Solution. Let M=max⁡(sup⁡A,sup⁡B)M = \max(\sup A, \sup B). Without loss, assume sup⁡A≥sup⁡B\sup A \geq \sup BSo M=sup⁡AM = \sup A. For all x∈A∪Bx \in A \cup B: either x∈Ax \in ASo x≤sup⁡A=Mx \leq \sup A = M; or x∈Bx \in BSo x≤sup⁡B≤Mx \leq \sup B \leq M. Thus MM is an upper bound for A∪BA \cup B.

For the least property: since M=sup⁡AM = \sup A and A⊆A∪BA \subseteq A \cup BEvery upper bound of A∪BA \cup B Is an upper bound of AAHence ≥sup⁡A=M\geq \sup A = M. Therefore sup⁡(A∪B)=M\sup(A \cup B) = M. ■\blacksquare

If you get this wrong, revise: Section 1.3 (Supremum and Infimum), Section 1.5 (Properties).

Problem 2. Prove that inf⁡A=−sup⁡(−A)\inf A = -\sup(-A) for any non-empty bounded set A⊆RA \subseteq \mathbb{R}.

Solution

Solution. Let u=sup⁡(−A)u = \sup(-A). For all a∈Aa \in A: −a∈−A-a \in -ASo −a≤u-a \leq uGiving a≥−ua \geq -u. Thus −u-u is a lower bound for AA. If vv is any lower bound for AAThen −v-v is an upper bound for −A-ASo u≤−vu \leq -vI.e., −u≥v-u \geq v. Hence −u-u is the greatest lower bound, so inf⁡A=−u=−sup⁡(−A)\inf A = -u = -\sup(-A). ■\blacksquare

If you get this wrong, revise: Section 1.5 (Properties of Supremum and Infimum).

Problem 3. Using the ε\varepsilon-NN definition, prove that lim⁡n→∞n2+3n2n2+1=12\lim_{n \to \infty} \frac{n^2 + 3n}{2n^2 + 1} = \frac{1}{2}.

Solution

Solution. Let ε>0\varepsilon > 0. Compute:

∣n2+3n2n2+1−12∣=∣2(n2+3n)−(2n2+1)2(2n2+1)∣=∣6n−12(2n2+1)∣\left|\frac{n^2 + 3n}{2n^2 + 1} - \frac{1}{2}\right| = \left|\frac{2(n^2 + 3n) - (2n^2 + 1)}{2(2n^2 + 1)}\right| = \left|\frac{6n - 1}{2(2n^2 + 1)}\right|

For n≥1n \geq 1: 6n−1<6n6n - 1 \lt 6n and 2n2+1>2n22n^2 + 1 > 2n^2So

6n−12(2n2+1)<6n4n2=32n\frac{6n - 1}{2(2n^2 + 1)} \lt \frac{6n}{4n^2} = \frac{3}{2n}

We need 32n<ε\frac{3}{2n} \lt \varepsilonI.e., n>3/(2ε)n > 3/(2\varepsilon). Choose N=⌈3/(2ε)⌉N = \lceil 3/(2\varepsilon) \rceil. For n≥Nn \geq N: the expression is <ε\lt \varepsilon. ■\blacksquare

If you get this wrong, revise: Section 2.1 (Convergence), Section 2.7 (Worked Examples).

Problem 4. Let a1=1a_1 = 1 and an+1=12(an+2an)a_{n+1} = \frac{1}{2}\left(a_n + \frac{2}{a_n}\right). Prove (an)(a_n) converges And find its limit.

Solution

Solution. Step 1: (an)(a_n) is bounded below by 2\sqrt{2}. By AM-GM: an+1=12(an+2/an)≥an⋅2/an=2a_{n+1} = \frac{1}{2}(a_n + 2/a_n) \geq \sqrt{a_n \cdot 2/a_n} = \sqrt{2}.

Step 2: (an)(a_n) is decreasing for n≥2n \geq 2. Note a1=1a_1 = 1, a2=3/2a_2 = 3/2. an+1−an=12(an+2/an)−an=12(2/an−an)=2−an22ana_{n+1} - a_n = \frac{1}{2}(a_n + 2/a_n) - a_n = \frac{1}{2}(2/a_n - a_n) = \frac{2 - a_n^2}{2a_n}. Since an≥2a_n \geq \sqrt{2} for n≥2n \geq 2, an2≥2a_n^2 \geq 2So an+1−an≤0a_{n+1} - a_n \leq 0.

Step 3: By the Monotone Convergence Theorem, L=lim⁡anL = \lim a_n exists. Taking limits: L=12(L+2/L)L = \frac{1}{2}(L + 2/L)Giving 2L=L+2/L2L = L + 2/LSo L=2/LL = 2/LHence L2=2L^2 = 2. Since an≥2a_n \geq \sqrt{2} for n≥2n \geq 2, L≥0L \geq 0So L=2L = \sqrt{2}. ■\blacksquare

If you get this wrong, revise: Section 2.2 (Monotone Convergence Theorem), Section 2.7 (recursive sequences).

Problem 5. Compute lim sup⁡n→∞an\limsup_{n \to \infty} a_n and lim inf⁡n→∞an\liminf_{n \to \infty} a_n for an=2+(−1)nnn+1a_n = 2 + (-1)^n \frac{n}{n+1}.

Solution

Solution. Write an=2+(−1)n⋅nn+1a_n = 2 + (-1)^n \cdot \frac{n}{n+1}.

For even n=2kn = 2k: a2k=2+2k2k+1→2+1=3a_{2k} = 2 + \frac{2k}{2k+1} \to 2 + 1 = 3. For odd n=2k−1n = 2k - 1: a2k−1=2−2k−12k→2−1=1a_{2k-1} = 2 - \frac{2k-1}{2k} \to 2 - 1 = 1.

Since these are the only two subsequential limits: lim sup⁡an=3\limsup a_n = 3 and lim inf⁡an=1\liminf a_n = 1. The sequence diverges since lim sup⁡≠lim inf⁡\limsup \neq \liminf. ■\blacksquare

If you get this wrong, revise: Section 2.6 (Limit Superior and Limit Inferior).

Problem 6. Determine whether ∑n=2∞1n(ln⁡n)2\sum_{n=2}^{\infty} \frac{1}{n(\ln n)^2} converges.

Solution

Solution. Apply the integral test with f(x)=1/(x(ln⁡x)2)f(x) = 1/(x(\ln x)^2) on [2,∞)[2, \infty). The function is Positive, continuous, and decreasing. Compute via u=ln⁡xu = \ln x, du=dx/xdu = dx/x:

∫2∞1x(ln⁡x)2 dx=∫ln⁡2∞1u2 du=[−1u]ln⁡2∞=1ln⁡2<∞\int_2^{\infty} \frac{1}{x(\ln x)^2}\, dx = \int_{\ln 2}^{\infty} \frac{1}{u^2}\, du = \left[-\frac{1}{u}\right]_{\ln 2}^{\infty} = \frac{1}{\ln 2} \lt \infty

The integral converges, so by the integral test, the series converges. ■\blacksquare

If you get this wrong, revise: Section 3.2 (Integral Test), Section 3.6 (Worked Examples).

Problem 7. Does ∑n=1∞(−1)n+1n1/3\sum_{n=1}^{\infty} \frac{(-1)^{n+1}}{n^{1/3}} converge absolutely, conditionally, or diverge?

Solution

Solution. The absolute series is ∑1/n1/3\sum 1/n^{1/3}Which is a pp-series with p=1/3<1p = 1/3 \lt 1 So it diverges. Hence the series does not converge absolutely.

For conditional convergence, apply the alternating series test: an=1/n1/3a_n = 1/n^{1/3} is positive, Decreasing, and an→0a_n \to 0. Therefore ∑(−1)n+1/n1/3\sum (-1)^{n+1}/n^{1/3} converges.

Since it converges but not absolutely, it converges conditionally. ■\blacksquare

If you get this wrong, revise: Section 3.3 (Absolute and Conditional Convergence), Section 3.6 (Alternating Series Test).

Problem 8. Find the sum of ∑n=1∞1n(n+2)\sum_{n=1}^{\infty} \frac{1}{n(n+2)}.

Solution

Solution. Use partial fractions: 1n(n+2)=12(1n−1n+2)\frac{1}{n(n+2)} = \frac{1}{2}\left(\frac{1}{n} - \frac{1}{n+2}\right). The NN-th partial sum telescopes:

SN=12[(11−13)+(12−14)+(13−15)+⋯+(1N−1N+2)]S_N = \frac{1}{2}\left[\left(\frac{1}{1} - \frac{1}{3}\right) + \left(\frac{1}{2} - \frac{1}{4}\right) + \left(\frac{1}{3} - \frac{1}{5}\right) + \cdots + \left(\frac{1}{N} - \frac{1}{N+2}\right)\right]

Most terms cancel. The surviving terms are:

SN=12(1+12−1N+1−1N+2)S_N = \frac{1}{2}\left(1 + \frac{1}{2} - \frac{1}{N+1} - \frac{1}{N+2}\right)

As N→∞N \to \infty: SN→12(1+1/2)=34S_N \to \frac{1}{2}(1 + 1/2) = \frac{3}{4}. ■\blacksquare

If you get this wrong, revise: Section 3.1 (Definitions and Convergence), telescoping series.

Problem 9. Give an explicit rearrangement of ∑n=1∞(−1)n+1n\sum_{n=1}^{\infty} \frac{(-1)^{n+1}}{n} whose sum is 00.

Solution

Solution. By the Riemann Rearrangement Theorem, such a rearrangement exists. We construct it Explicitly. The positive terms are 1,1/3,1/5,…1, 1/3, 1/5, \ldots and the negative terms are −1/2,−1/4,−1/6,…-1/2, -1/4, -1/6, \ldots.

Start: S1=1S_1 = 1. Then add negative terms until we go below 00: S2=1−1/2=1/2>0S_2 = 1 - 1/2 = 1/2 > 0. S3=1−1/2−1/4=1/4>0S_3 = 1 - 1/2 - 1/4 = 1/4 > 0. S4=1−1/2−1/4−1/6=−1/12<0S_4 = 1 - 1/2 - 1/4 - 1/6 = -1/12 \lt 0.

Then add positive terms until we exceed 00: S5=−1/12+1/3=1/4>0S_5 = -1/12 + 1/3 = 1/4 > 0.

Then add negative terms until below 00: S6=1/4−1/8=1/8>0S_6 = 1/4 - 1/8 = 1/8 > 0. S7=1/8−1/10=1/40>0S_7 = 1/8 - 1/10 = 1/40 > 0. S8=1/40−1/12=−7/120<0S_8 = 1/40 - 1/12 = -7/120 \lt 0.

Continue this process. Since ∑1/(2k−1)=∞\sum 1/(2k-1) = \infty and ∑1/(2k)=∞\sum 1/(2k) = \inftyWe can always Continue. Since 1/n→01/n \to 0The oscillations shrink to 00. The resulting rearrangement converges to 00. ■\blacksquare

If you get this wrong, revise: Section 3.5 (Rearrangement of Series).

Problem 10. Prove using ε\varepsilon-δ\delta that f(x)=x3f(x) = x^3 is continuous at every a∈Ra \in \mathbb{R}.

Solution

Solution. Let a∈Ra \in \mathbb{R} and ε>0\varepsilon > 0. Compute:

∣f(x)−f(a)∣=∣x3−a3∣=∣x−a∣⋅∣x2+ax+a2∣|f(x) - f(a)| = |x^3 - a^3| = |x - a| \cdot |x^2 + ax + a^2|

Restrict to ∣x−a∣<1|x - a| \lt 1So ∣x∣<∣a∣+1|x| \lt |a| + 1Giving ∣x2+ax+a2∣≤(∣a∣+1)2+∣a∣(∣a∣+1)+a2=3a2+3∣a∣+1|x^2 + ax + a^2| \leq (|a|+1)^2 + |a|(|a|+1) + a^2 = 3a^2 + 3|a| + 1. Let M=3a2+3∣a∣+1M = 3a^2 + 3|a| + 1.

Choose δ=min⁡(1,ε/M)\delta = \min(1, \varepsilon/M). Then ∣x−a∣<δ|x - a| \lt \delta implies:

∣x3−a3∣≤∣x−a∣⋅M<εM⋅M=ε|x^3 - a^3| \leq |x - a| \cdot M \lt \frac{\varepsilon}{M} \cdot M = \varepsilon

■\blacksquare

If you get this wrong, revise: Section 4.2 (Continuity), Section 4.7 (Worked Examples).

Problem 11. Prove that f(x)=xsin⁡(1/x)f(x) = x \sin(1/x) (with f(0)=0f(0) = 0) is continuous on R\mathbb{R} but not Uniformly continuous on (0,1)(0, 1). (Trick question --- see solution.)

Solution

Solution. Continuity at 00: Given ε>0\varepsilon > 0Choose δ=ε\delta = \varepsilon. For ∣x−0∣=∣x∣<δ|x - 0| = |x| \lt \delta: ∣f(x)−f(0)∣=∣xsin⁡(1/x)∣≤∣x∣<δ=ε|f(x) - f(0)| = |x \sin(1/x)| \leq |x| \lt \delta = \varepsilon. So ff is continuous at 00. For x≠0x \neq 0, ff is a product of continuous functions, hence continuous.

On uniform continuity: Actually, f(x)=xsin⁡(1/x)f(x) = x\sin(1/x) is uniformly continuous on (0,1)(0, 1)! Here is why: ff extends continuously to [0,1][0, 1] (define f(0)=0f(0) = 0). By the Heine-Cantor theorem (Theorem 4.5), ff is uniformly continuous on [0,1][0, 1]And hence on the subset (0,1)(0, 1).

The function that is not uniformly continuous on (0,1)(0, 1) is g(x)=sin⁡(1/x)g(x) = \sin(1/x)Which does not Extend continuously to 00. Or h(x)=1/xh(x) = 1/xWhich is unbounded. But f(x)=xsin⁡(1/x)f(x) = x\sin(1/x) is bounded And has a continuous extension, so it is uniformly continuous. ■\blacksquare

If you get this wrong, revise: Section 4.5 (Uniform Continuity), Section 4.6 (Heine-Cantor).

Problem 12. Prove that if f"(x)=g′(x)f"(x) = g'(x) for all x∈(a,b)x \in (a, b)Then f(x)=g(x)+Cf(x) = g(x) + C for some Constant CC.

Solution

Solution. Let h(x)=f(x)−g(x)h(x) = f(x) - g(x). Then h′(x)=f′(x)−g′(x)=0h'(x) = f'(x) - g'(x) = 0 for all x∈(a,b)x \in (a, b). By Corollary 5.4 (a consequence of the Mean Value Theorem), hh is constant on (a,b)(a, b). So f(x)−g(x)=Cf(x) - g(x) = C for some C∈RC \in \mathbb{R}I.e., f(x)=g(x)+Cf(x) = g(x) + C. ■\blacksquare

If you get this wrong, revise: Section 5.3 (Mean Value Theorem, Corollary 5.4).

Problem 13. Use Taylor’s theorem with remainder to bound the error in approximating e0.2e^{0.2} Using the fourth-degree Maclaurin polynomial.

Solution

Solution. The fourth-degree Maclaurin polynomial of exe^x is:

T4(x)=1+x+x22+x36+x424T_4(x) = 1 + x + \frac{x^2}{2} + \frac{x^3}{6} + \frac{x^4}{24}

By Taylor’s theorem, R4(x)=eξ5!x5R_4(x) = \frac{e^{\xi}}{5!} x^5 for some ξ\xi between 00 and xx. For x=0.2x = 0.2: ξ∈(0,0.2)\xi \in (0, 0.2)So eξ<e0.2<e1/4<1.3e^{\xi} \lt e^{0.2} \lt e^{1/4} \lt 1.3.

∣R4(0.2)∣=eξ120(0.2)5<1.3120⋅0.00032=1.3×0.00032120≈3.47×10−6|R_4(0.2)| = \frac{e^{\xi}}{120} (0.2)^5 \lt \frac{1.3}{120} \cdot 0.00032 = \frac{1.3 \times 0.00032}{120} \approx 3.47 \times 10^{-6}

So T4(0.2)=1+0.2+0.02+0.001333+0.000067=1.221400T_4(0.2) = 1 + 0.2 + 0.02 + 0.001333 + 0.000067 = 1.221400 approximates e0.2e^{0.2} with Error less than 3.5×10−63.5 \times 10^{-6}. ■\blacksquare

If you get this wrong, revise: Section 5.4 (Taylor’s Theorem), Section 5.7 (Worked Examples).

Problem 14. Compute ∫01x3 dx\int_0^1 x^3\, dx from the definition using upper and lower Riemann sums.

Solution

Solution. Let Pn={0,1/n,2/n,…,1}P_n = \{0, 1/n, 2/n, \ldots, 1\}. On [(i−1)/n,i/n][(i-1)/n, i/n], f(x)=x3f(x) = x^3 has Mi=(i/n)3M_i = (i/n)^3 and mi=((i−1)/n)3m_i = ((i-1)/n)^3.

U(f,Pn)=∑i=1ni3n3⋅1n=1n4∑i=1ni3=1n4⋅n2(n+1)24U(f, P_n) = \sum_{i=1}^{n} \frac{i^3}{n^3} \cdot \frac{1}{n} = \frac{1}{n^4} \sum_{i=1}^{n} i^3 = \frac{1}{n^4} \cdot \frac{n^2(n+1)^2}{4}

As n→∞n \to \infty:

lim⁡n→∞U(f,Pn)=lim⁡n→∞(n+1)24n2=14\lim_{n \to \infty} U(f, P_n) = \lim_{n \to \infty} \frac{(n+1)^2}{4n^2} = \frac{1}{4}

Similarly, L(f,Pn)→1/4L(f, P_n) \to 1/4. So ∫01x3 dx=1/4\int_0^1 x^3\, dx = 1/4. ■\blacksquare

If you get this wrong, revise: Section 6.1 (Definition), Section 6.5 (Worked Examples).

Problem 14b. Show that the Dirichlet function f(x)={1x∈Q0x∉Qf(x) = \begin{cases} 1 & x \in \mathbb{Q} \\ 0 & x \notin \mathbb{Q} \end{cases} is not Riemann integrable on [0,1][0, 1].

Solution

Solution. Every non-empty subinterval [xi−1,xi][x_{i-1}, x_i] of any partition contains both rational and Irrational numbers (by density of Q\mathbb{Q} and density of R∖Q\mathbb{R} \setminus \mathbb{Q}). So Mi=sup⁡f=1M_i = \sup f = 1 and mi=inf⁡f=0m_i = \inf f = 0 for every subinterval.

For any partition PP: U(f,P)=∑1⋅Δxi=1U(f, P) = \sum 1 \cdot \Delta x_i = 1 and L(f,P)=∑0⋅Δxi=0L(f, P) = \sum 0 \cdot \Delta x_i = 0. Hence ∫01‾f=1≠0=∫01‾f\overline{\int_0^1} f = 1 \neq 0 = \underline{\int_0^1} fSo ff is not Riemann integrable.

This also follows from Lebesgue’s criterion: ff is discontinuous everywhere, and [0,1][0,1] does not Have measure zero. ■\blacksquare

If you get this wrong, revise: Section 6.2 (Integrability Criteria), Theorem 6.4b.

Problem 15. Evaluate ∫01x1−x2 dx\int_0^1 \frac{x}{\sqrt{1 - x^2}}\, dx as an improper integral.

Solution

Solution. The integrand f(x)=x/1−x2f(x) = x/\sqrt{1 - x^2} is unbounded as x→1−x \to 1^-. This is a Type II Improper integral.

∫01x1−x2 dx=lim⁡b→1−∫0bx1−x2 dx\int_0^1 \frac{x}{\sqrt{1 - x^2}}\, dx = \lim_{b \to 1^-} \int_0^b \frac{x}{\sqrt{1 - x^2}}\, dx

Compute via substitution u=1−x2u = 1 - x^2, du=−2x dxdu = -2x\, dx:

=lim⁡b→1−[−1−x2]0b=lim⁡b→1−(−1−b2+1)=0+1=1= \lim_{b \to 1^-} \left[-\sqrt{1 - x^2}\right]_0^b = \lim_{b \to 1^-} \left(-\sqrt{1 - b^2} + 1\right) = 0 + 1 = 1

The improper integral converges to 11. ■\blacksquare

If you get this wrong, revise: Section 6.6 (Improper Integrals).

Problem 16. Let fn(x)=nx1+n2x2f_n(x) = \frac{nx}{1 + n^2 x^2} on (0,∞)(0, \infty). Find the pointwise limit and Determine whether the convergence is uniform on (0,∞)(0, \infty).

Solution

Solution. Pointwise limit: For fixed x>0x > 0: lim⁡n→∞fn(x)=lim⁡n→∞nx1+n2x2=lim⁡n→∞x/n1/n2+x2=0\lim_{n \to \infty} f_n(x) = \lim_{n \to \infty} \frac{nx}{1 + n^2 x^2} = \lim_{n \to \infty} \frac{x/n}{1/n^2 + x^2} = 0.

So fn→0f_n \to 0 pointwise on (0,∞)(0, \infty).

Uniform convergence? We check sup⁡x>0∣fn(x)−0∣=sup⁡x>0nx1+n2x2\sup_{x > 0} |f_n(x) - 0| = \sup_{x > 0} \frac{nx}{1 + n^2 x^2}. To maximize, differentiate with respect to xx (treating nn as fixed):

ddx(nx1+n2x2)=n(1+n2x2)−nx⋅2n2x(1+n2x2)2=n−n3x2(1+n2x2)2\frac{d}{dx}\left(\frac{nx}{1 + n^2 x^2}\right) = \frac{n(1 + n^2 x^2) - nx \cdot 2n^2 x}{(1 + n^2 x^2)^2} = \frac{n - n^3 x^2}{(1 + n^2 x^2)^2}

Setting to zero: n−n3x2=0n - n^3 x^2 = 0So x=1/nx = 1/n. The maximum value is fn(1/n)=n⋅1/n1+n2/n2=12f_n(1/n) = \frac{n \cdot 1/n}{1 + n^2/n^2} = \frac{1}{2}.

Since sup⁡x>0∣fn(x)∣=1/2\sup_{x > 0} |f_n(x)| = 1/2 for all nnThis does not tend to 00. Therefore the convergence Is not uniform on (0,∞)(0, \infty). ■\blacksquare

If you get this wrong, revise: Section 7.2 (Uniform Convergence), Section 7.1 (Pointwise Convergence).

Problem 17. Find the radius of convergence of ∑n=1∞(2n)!(n!)2xn\sum_{n=1}^{\infty} \frac{(2n)!}{(n!)^2} x^n.

Solution

Solution. Apply the ratio test to the terms:

∣an+1an∣=(2(n+1))!((n+1)!)2⋅(n!)2(2n)!⋅∣x∣=(2n+2)(2n+1)(n+1)2⋅∣x∣\left|\frac{a_{n+1}}{a_n}\right| = \frac{(2(n+1))!}{((n+1)!)^2} \cdot \frac{(n!)^2}{(2n)!} \cdot |x| = \frac{(2n+2)(2n+1)}{(n+1)^2} \cdot |x|

=2(2n+1)n+1⋅∣x∣=4n+2n+1⋅∣x∣→4∣x∣as n→∞= \frac{2(2n+1)}{n+1} \cdot |x| = \frac{4n + 2}{n + 1} \cdot |x| \to 4|x| \quad \mathrm{as\ } n \to \infty

The series converges when 4∣x∣<14|x| \lt 1I.e., ∣x∣<1/4|x| \lt 1/4And diverges when 4∣x∣>14|x| > 1. The radius of convergence is R=1/4R = 1/4. ■\blacksquare

If you get this wrong, revise: Section 7.7 (Power Series), Section 3.2 (Ratio Test).

Problem 18. Let fn(x)=xn/nf_n(x) = x^n/n on [0,1][0, 1]. Show that fn→0f_n \to 0 uniformly, but fn′(x)=xn−1f_n'(x) = x^{n-1} does not converge uniformly on (0,1)(0, 1).

Solution

Solution. Uniform convergence of fnf_n: sup⁡x∈[0,1]∣xn/n∣=1/n→0\sup_{x \in [0,1]} |x^n/n| = 1/n \to 0 as n→∞n \to \infty. So fn→0f_n \to 0 uniformly on [0,1][0, 1].

Non-uniform convergence of fn′f_n': fn′(x)=xn−1f_n'(x) = x^{n-1}. The pointwise limit is g(x)=0g(x) = 0 for 0≤x<10 \leq x \lt 1 and g(1)=1g(1) = 1. So sup⁡x∈[0,1]∣fn′(x)−g(x)∣≥∣fn′(1)−g(1)∣=∣1−1∣=0\sup_{x \in [0,1]} |f_n'(x) - g(x)| \geq |f_n'(1) - g(1)| = |1 - 1| = 0.

Actually, check sup⁡x∈[0,1)∣xn−1∣=1\sup_{x \in [0,1)} |x^{n-1}| = 1 (approached as x→1−x \to 1^-). But g(x)=0g(x) = 0 on [0,1)[0, 1)So sup⁡x∈[0,1)∣xn−1−0∣=1\sup_{x \in [0,1)} |x^{n-1} - 0| = 1 for all nn. This does not Tend to 00So fn′f_n' does not converge uniformly on [0,1)[0, 1).

This illustrates that uniform convergence of functions does not imply uniform convergence of Derivatives, which is why Theorem 7.4 requires the stronger hypothesis of uniform convergence of (fn′)(f_n'). ■\blacksquare

If you get this wrong, revise: Section 7.2 (Uniform Convergence), Section 7.6 (Uniform Convergence and Differentiation).

Problem 19. Let fn(x)=x1+nx2f_n(x) = \frac{x}{1 + nx^2} on [0,∞)[0, \infty). Find the pointwise limit and determine Whether the convergence is uniform.

Solution

Solution. Pointwise limit: For x=0x = 0: fn(0)=0f_n(0) = 0 for all nn. For x>0x > 0: lim⁡n→∞x1+nx2=lim⁡n→∞11/x+nx=0\lim_{n \to \infty} \frac{x}{1 + nx^2} = \lim_{n \to \infty} \frac{1}{1/x + nx} = 0. So fn→0f_n \to 0 pointwise.

Uniform convergence on [0,∞)[0, \infty)? We check sup⁡x≥0∣fn(x)∣\sup_{x \geq 0} |f_n(x)|. Differentiate: ddx(x1+nx2)=1−nx2(1+nx2)2\frac{d}{dx}\left(\frac{x}{1 + nx^2}\right) = \frac{1 - nx^2}{(1 + nx^2)^2}. Setting to zero: x=1/nx = 1/\sqrt{n}. The maximum value is fn(1/n)=1/n1+n/n=12nf_n(1/\sqrt{n}) = \frac{1/\sqrt{n}}{1 + n/n} = \frac{1}{2\sqrt{n}}.

Since sup⁡x≥0∣fn(x)∣=12n→0\sup_{x \geq 0} |f_n(x)| = \frac{1}{2\sqrt{n}} \to 0 as n→∞n \to \inftyThe convergence is Uniform on [0,∞)[0, \infty). ■\blacksquare

If you get this wrong, revise: Section 7.2 (Uniform Convergence).

Problem 20. Prove that the series ∑n=0∞(−1)n2n+1x2n+1\sum_{n=0}^{\infty} \frac{(-1)^n}{2n+1} x^{2n+1} converges uniformly on [−1,1][-1, 1] and identify its sum.

Solution

Solution. For ∣x∣≤1|x| \leq 1: ∣(−1)nx2n+12n+1∣≤12n+1\left|\frac{(-1)^n x^{2n+1}}{2n+1}\right| \leq \frac{1}{2n+1}. The series ∑12n+1\sum \frac{1}{2n+1} diverges (it dominates half the harmonic series), so the Weierstrass M-test does not apply directly with these bounds.

However, by the alternating series test, the series converges pointwise for every ∣x∣≤1|x| \leq 1 (since ∣x∣2n+12n+1\frac{|x|^{2n+1}}{2n+1} decreases to 00 for ∣x∣≤1|x| \leq 1). The sum is arctan⁡x\arctan x Which is the Taylor series of arctan⁡\arctan about 00.

For uniform convergence, we use Abel’s test for uniform convergence of series: if ∑fn(x)\sum f_n(x) has uniformly bounded partial sums and gn(x)g_n(x) decreases uniformly to 00Then ∑fn(x)gn(x)\sum f_n(x) g_n(x) converges uniformly. Here fn(x)=(−1)nx2n+1f_n(x) = (-1)^n x^{2n+1} and gn(x)=1/(2n+1)g_n(x) = 1/(2n+1) Is independent of xx.

The partial sums ∣∑k=0n(−1)kx2k+1∣=∣x∣⋅∣1−(−x2)n+1∣1+x2≤2∣x∣1+x2≤1\left|\sum_{k=0}^{n} (-1)^k x^{2k+1}\right| = \frac{|x| \cdot |1-(-x^2)^{n+1}|}{1+x^2} \leq \frac{2|x|}{1+x^2} \leq 1 for ∣x∣≤1|x| \leq 1 (geometric series with closed form). And 1/(2n+1)→01/(2n+1) \to 0 uniformly. By Abel’s test, the convergence is uniform on [−1,1][-1, 1].

Setting x=1x = 1: ∑n=0∞(−1)n2n+1=arctan⁡1=π/4\sum_{n=0}^{\infty} \frac{(-1)^n}{2n+1} = \arctan 1 = \pi/4. ■\blacksquare

If you get this wrong, revise: Section 7.3 (Weierstrass M-Test), Section 7.7 (Power Series), Abel’s theorem.

  • Assuming every bounded set has a maximum. A set can be bounded above without having a maximum; the supremum always exists but may not be a member of the set. Fix: The supremum sup⁡(S)\sup(S) is the least upper bound; it equals the maximum only when sup⁡(S)∈S\sup(S) \in S.
  • Misusing the ε\varepsilon-δ\delta definition. The order of quantifiers matters: “for every ε>0\varepsilon > 0, there exists δ>0\delta > 0” — δ\delta depends on ε\varepsilon and the point, not the other way around. Fix: In proofs, choose δ\delta after ε\varepsilon is given; δ\delta depends on both ε\varepsilon and x0x_0 (unless the function is uniformly continuous).
  • Confusing pointwise and uniform convergence. Pointwise: δ\delta may depend on xx. Uniform: δ\delta works for all xx simultaneously. Fix: Uniform convergence implies pointwise convergence but not conversely; the Weierstrass M-test gives a sufficient condition for uniform convergence.

Example 1: Proving a limit using ε\varepsilon-δ\delta

Section titled “Example 1: Proving a limit using ε\varepsilonε-δ\deltaδ”

Problem. Prove that lim⁡x→2(3x−1)=5\lim_{x \to 2} (3x - 1) = 5.

Solution. Let ε>0\varepsilon > 0 be given. We need ∣3x−1−5∣<ε|3x - 1 - 5| < \varepsilon, i.e. ∣3x−6∣<ε|3x - 6| < \varepsilon, i.e. 3∣x−2∣<ε3|x - 2| < \varepsilon.

Choose δ=ε/3\delta = \varepsilon/3. Then ∣x−2∣<δ|x - 2| < \delta implies 3∣x−2∣<3⋅ε/3=ε3|x - 2| < 3 \cdot \varepsilon/3 = \varepsilon.

Therefore lim⁡x→2(3x−1)=5\lim_{x \to 2}(3x - 1) = 5. ■\blacksquare

Problem. Find sup⁡\sup and inf⁡\inf of the set S={1/n:n∈N}S = \{1/n : n \in \mathbb{N}\}.

Solution. The elements are 1,1/2,1/3,…1, 1/2, 1/3, \ldots. The sequence decreases and approaches 00.

sup⁡(S)=1∈S\sup(S) = 1 \in S (this is also the maximum). inf⁡(S)=0∉S\inf(S) = 0 \notin S.

■\blacksquare

  • R\mathbb{R} is a complete ordered field; the completeness axiom guarantees sup⁡(S)\sup(S) exists for every non-empty bounded-above set.
  • Supremum sup⁡(S)\sup(S) is the least upper bound; it equals max⁡(S)\max(S) iff sup⁡(S)∈S\sup(S) \in S.
  • ε\varepsilon-δ\delta definition: lim⁡x→af(x)=L\lim_{x \to a} f(x) = L iff for every ε>0\varepsilon > 0 there exists δ>0\delta > 0 such that 0<∣x−a∣<δ0 < |x-a| < \delta implies ∣f(x)−L∣<ε|f(x) - L| < \varepsilon.
  • Uniform convergence preserves continuity, differentiability (under appropriate conditions), and integrability.
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