All Study Guides Intro to Mathematical Analysis Unit 3
🏃🏽♀️➡️ Intro to Mathematical Analysis Unit 3 – Monotone and Cauchy SequencesMonotone and Cauchy sequences are essential concepts in mathematical analysis. Monotone sequences consistently increase or decrease, while Cauchy sequences have terms that become arbitrarily close to each other. These sequences help us understand convergence and limits.
Monotone sequences are either bounded and convergent or unbounded and divergent. Cauchy sequences are always convergent in complete metric spaces like real numbers. These concepts are crucial for constructing real numbers and solving optimization problems in various fields of mathematics.
Key Concepts and Definitions
Monotone sequences are sequences that either increase or decrease consistently
Increasing monotone sequence: a n ≤ a n + 1 a_n \leq a_{n+1} a n ≤ a n + 1 for all n ∈ N n \in \mathbb{N} n ∈ N
Decreasing monotone sequence: a n ≥ a n + 1 a_n \geq a_{n+1} a n ≥ a n + 1 for all n ∈ N n \in \mathbb{N} n ∈ N
Strictly monotone sequences have strict inequalities (< < < or > > > ) instead of ≤ \leq ≤ or ≥ \geq ≥
Bounded sequences have an upper bound and/or a lower bound
Upper bound: ∃ M ∈ R \exists M \in \mathbb{R} ∃ M ∈ R such that a n ≤ M a_n \leq M a n ≤ M for all n ∈ N n \in \mathbb{N} n ∈ N
Lower bound: ∃ m ∈ R \exists m \in \mathbb{R} ∃ m ∈ R such that a n ≥ m a_n \geq m a n ≥ m for all n ∈ N n \in \mathbb{N} n ∈ N
Convergent sequences approach a limit as n n n approaches infinity
Limit of a sequence: lim n → ∞ a n = L \lim_{n \to \infty} a_n = L lim n → ∞ a n = L if ∀ ε > 0 , ∃ N ∈ N \forall \varepsilon > 0, \exists N \in \mathbb{N} ∀ ε > 0 , ∃ N ∈ N such that ∣ a n − L ∣ < ε |a_n - L| < \varepsilon ∣ a n − L ∣ < ε for all n ≥ N n \geq N n ≥ N
Cauchy sequences have terms that become arbitrarily close to each other as n n n increases
Cauchy sequence: ∀ ε > 0 , ∃ N ∈ N \forall \varepsilon > 0, \exists N \in \mathbb{N} ∀ ε > 0 , ∃ N ∈ N such that ∣ a n − a m ∣ < ε |a_n - a_m| < \varepsilon ∣ a n − a m ∣ < ε for all n , m ≥ N n, m \geq N n , m ≥ N
Properties of Monotone Sequences
Monotone sequences are either non-increasing or non-decreasing
Every monotone sequence is either convergent or divergent
Convergent if bounded (monotone convergence theorem)
Divergent if unbounded (lim n → ∞ a n = ∞ \lim_{n \to \infty} a_n = \infty lim n → ∞ a n = ∞ for increasing, lim n → ∞ a n = − ∞ \lim_{n \to \infty} a_n = -\infty lim n → ∞ a n = − ∞ for decreasing)
The limit of a convergent monotone sequence is equal to its supremum (increasing) or infimum (decreasing)
Supremum: least upper bound, sup { a n } = min { x ∈ R : a n ≤ x for all n ∈ N } \sup\{a_n\} = \min\{x \in \mathbb{R} : a_n \leq x \text{ for all } n \in \mathbb{N}\} sup { a n } = min { x ∈ R : a n ≤ x for all n ∈ N }
Infimum: greatest lower bound, inf { a n } = max { x ∈ R : a n ≥ x for all n ∈ N } \inf\{a_n\} = \max\{x \in \mathbb{R} : a_n \geq x \text{ for all } n \in \mathbb{N}\} inf { a n } = max { x ∈ R : a n ≥ x for all n ∈ N }
Arithmetic operations preserve monotonicity
Sum, difference, product, and quotient of monotone sequences are monotone (assuming divisor sequence is never zero)
Subsequences of monotone sequences are also monotone
Convergence of Monotone Sequences
Monotone convergence theorem states that a monotone sequence converges if and only if it is bounded
Increasing and bounded above ⟹ \implies ⟹ convergent
Decreasing and bounded below ⟹ \implies ⟹ convergent
The limit of a convergent monotone sequence can be found using the supremum or infimum
lim n → ∞ a n = sup { a n } \lim_{n \to \infty} a_n = \sup\{a_n\} lim n → ∞ a n = sup { a n } for increasing sequences
lim n → ∞ a n = inf { a n } \lim_{n \to \infty} a_n = \inf\{a_n\} lim n → ∞ a n = inf { a n } for decreasing sequences
Convergence of monotone sequences can be proven using the definition of convergence and the monotone convergence theorem
Rate of convergence for monotone sequences depends on the specific sequence
Geometric sequences (a n = a r n a_n = ar^n a n = a r n ) converge exponentially fast
Harmonic sequences (a n = 1 n a_n = \frac{1}{n} a n = n 1 ) converge slowly
Introduction to Cauchy Sequences
Cauchy sequences are fundamental in analysis and the construction of real numbers
Cauchy criterion: ∀ ε > 0 , ∃ N ∈ N \forall \varepsilon > 0, \exists N \in \mathbb{N} ∀ ε > 0 , ∃ N ∈ N such that ∣ a n − a m ∣ < ε |a_n - a_m| < \varepsilon ∣ a n − a m ∣ < ε for all n , m ≥ N n, m \geq N n , m ≥ N
Terms become arbitrarily close to each other as n n n and m m m increase
Cauchy sequences are named after Augustin-Louis Cauchy, a French mathematician
Cauchy sequences are defined in metric spaces, generalizing the concept from real numbers
Metric space: set with a distance function (metric) satisfying certain properties
Cauchy sequences are a tool for proving convergence without knowing the limit
Relationship Between Cauchy and Convergent Sequences
In complete metric spaces (including R \mathbb{R} R ), Cauchy sequences are convergent
Completeness: every Cauchy sequence converges to a point within the space
Convergent sequences are always Cauchy
If lim n → ∞ a n = L \lim_{n \to \infty} a_n = L lim n → ∞ a n = L , then { a n } \{a_n\} { a n } is Cauchy
In incomplete metric spaces, Cauchy sequences may not converge (within the space)
Example: Q \mathbb{Q} Q is incomplete, sequence { 1 , 1.4 , 1.41 , 1.414 , … } \{1, 1.4, 1.41, 1.414, \ldots\} { 1 , 1.4 , 1.41 , 1.414 , … } is Cauchy but converges to 2 ∉ Q \sqrt{2} \notin \mathbb{Q} 2 ∈ / Q
Cauchy sequences are used to construct real numbers from rational numbers
Dedekind cuts and Cauchy sequences provide equivalent constructions of R \mathbb{R} R
Examples and Applications
Geometric sequences (a n = a r n a_n = ar^n a n = a r n ) are monotone and convergent for ∣ r ∣ < 1 |r| < 1 ∣ r ∣ < 1
Increasing if 0 < r < 1 0 < r < 1 0 < r < 1 , decreasing if − 1 < r < 0 -1 < r < 0 − 1 < r < 0
lim n → ∞ a r n = 0 \lim_{n \to \infty} ar^n = 0 lim n → ∞ a r n = 0 for ∣ r ∣ < 1 |r| < 1 ∣ r ∣ < 1
Harmonic sequence (a n = 1 n a_n = \frac{1}{n} a n = n 1 ) is decreasing and convergent
Bounded below by 0, lim n → ∞ 1 n = 0 \lim_{n \to \infty} \frac{1}{n} = 0 lim n → ∞ n 1 = 0
Alternating harmonic sequence (a n = ( − 1 ) n + 1 n a_n = \frac{(-1)^{n+1}}{n} a n = n ( − 1 ) n + 1 ) is not monotone but is Cauchy
Convergent to ln ( 2 ) \ln(2) ln ( 2 ) , can be shown using the alternating series test
Monotone sequences appear in optimization problems and numerical methods
Gradient descent, Newton's method, and fixed-point iteration generate monotone sequences
Cauchy sequences are used in the construction of real numbers and in functional analysis
Lp spaces, Banach spaces, and Hilbert spaces are complete metric spaces
Common Pitfalls and Misconceptions
Not all bounded sequences are convergent (oscillating sequences)
Example: a n = ( − 1 ) n a_n = (-1)^n a n = ( − 1 ) n is bounded but not convergent
Not all convergent sequences are monotone
Example: a n = ( − 1 ) n n a_n = \frac{(-1)^n}{n} a n = n ( − 1 ) n converges to 0 but alternates between positive and negative
Monotonicity does not imply strict monotonicity
Constant sequences are both increasing and decreasing
Cauchy sequences are not always easy to identify
May require clever manipulations or estimates to prove Cauchy criterion
Incomplete metric spaces have Cauchy sequences that do not converge within the space
Convergence in R \mathbb{R} R does not imply convergence in Q \mathbb{Q} Q
Practice Problems and Exercises
Prove that the sequence a n = n n + 1 a_n = \frac{n}{n+1} a n = n + 1 n is increasing and find its limit.
Show that the sequence a n = 1 2 n a_n = \frac{1}{2^n} a n = 2 n 1 is decreasing and converges to 0.
Determine whether the sequence a n = cos ( π n 2 ) a_n = \cos(\frac{\pi n}{2}) a n = cos ( 2 πn ) is monotone. Is it convergent?
Prove that the sequence a n = n a_n = \sqrt{n} a n = n is unbounded and not Cauchy.
Show that the sequence a n = 1 n 2 a_n = \frac{1}{n^2} a n = n 2 1 is Cauchy using the definition of Cauchy sequences.
Find an example of a sequence that is Cauchy but not monotone.
Construct a monotone sequence that converges to 3 \sqrt{3} 3 .
Prove that if { a n } \{a_n\} { a n } and { b n } \{b_n\} { b n } are Cauchy sequences, then { a n + b n } \{a_n + b_n\} { a n + b n } is also Cauchy.