Sequences of Real Numbers ((𝑎𝑛)𝑛∊ℕ, 𝑎: ℕ → ℝ)
- is a map from natural numbers ℕ to real numbers ℝ (𝑎: ℕ → ℝ)
Sequences of Real Numbers - Syntax
-
𝑎: ℕ → ℝ
- (𝑎1, 𝑎2, … )
- (𝑎𝑛)𝑛∊ℕ
Sequences of Real Numbers - Examples
|
(𝑎𝑛)𝑛∊ℕ |
(1)𝑛∊ℕ |
(1, 1, 1, 1, …) |
|
(𝑎𝑛)𝑛∊ℕ |
((-1)𝑛)𝑛∊ℕ |
(-1, 1, -1, 1, …) |
|
(𝑎𝑛)𝑛∊ℕ |
(1/𝑛)𝑛∊ℕ |
(1/1, 1/2, 1/3, 1/4, …) |
|
(𝑎𝑛)𝑛∊ℕ |
(2𝑛)𝑛∊ℕ |
(2, 4, 8, 16, 32, …) |
Sequences of Real Numbers - Properties
|
Property |
Definition |
Examples |
Proof |
|---|---|---|---|
|
Convergent |
a sequence (𝑎𝑛)𝑛∊ℕ is convergent if:
|
(1)𝑛∊ℕ |
|
|
(1/𝑛)𝑛∊ℕ |
| ||
|
Divergent |
a sequence (𝑎𝑛)𝑛∊ℕ is divergent if it is not convergent:
|
((-1)𝑛)𝑛∊ℕ |
|
|
(2𝑛)𝑛∊ℕ |
| ||
|
Bounded |
a sequence (𝑎𝑛)𝑛∊ℕ is bounded if:
|
((-1)𝑛)𝑛∊ℕ |
|
|
Unbounded |
a sequence (𝑎𝑛)𝑛∊ℕ is unbounded if it is not bounded:
|
(2𝑛)𝑛∊ℕ |
|
theorems:
- if a sequence is convergent then it is also bounded
- if a sequence is unbounded then it is also divergent
TODO
Theorem on Limits
Given two convergent sequences (𝑎𝑛)𝑛∊ℕ and (𝑏𝑛)𝑛∊ℕ then:
- 𝑙𝑖𝑚𝑛→∞(𝑎𝑛 + 𝑏𝑛) = 𝑙𝑖𝑚𝑛→∞(𝑎𝑛) + 𝑙𝑖𝑚𝑛→∞(𝑏𝑛)
- 𝑙𝑖𝑚𝑛→∞(𝑎𝑛 · 𝑏𝑛) = 𝑙𝑖𝑚𝑛→∞(𝑎𝑛) · 𝑙𝑖𝑚𝑛→∞(𝑏𝑛)
- 𝑙𝑖𝑚𝑛→∞(𝑎𝑛 / 𝑏𝑛) = 𝑙𝑖𝑚𝑛→∞(𝑎𝑛) / 𝑙𝑖𝑚𝑛→∞(𝑏𝑛) # 𝑏𝑛≠ 0
Monotonicity
Given two convergent sequences (𝑎𝑛)𝑛∊ℕ and (𝑏𝑛)𝑛∊ℕ:
- if 𝑎𝑛≤ 𝑏𝑛 for all 𝑛∊ℕ → 𝑙𝑖𝑚𝑛→∞(𝑎𝑛) ≤ 𝑙𝑖𝑚𝑛→∞(𝑏𝑛)
Monotonically Increasing/Decreasing
A sequence (𝑎𝑛)𝑛∊ℕ is:
- monotonically increasing if: 𝑎𝑛≤ 𝑎𝑛+1 for all 𝑛
- monotonically decreasing if: 𝑎𝑛≥ 𝑎𝑛+1 for all 𝑛
Strictly Monotonically Increasing/Decreasing
A sequence (𝑎𝑛)𝑛∊ℕ is:
- strictly monotonically increasing if: 𝑎𝑛< 𝑎𝑛+1 for all 𝑛
- strictly monotonically decreasing if: 𝑎𝑛> 𝑎𝑛+1 for all 𝑛
Bounded From Above/Below - Bounded
A sequence (𝑎𝑛)𝑛∊ℕ is:
- bounded from above if the set {𝑎𝑛}𝑛∊ℕ has an upper bound
- bounded from below if the set {𝑎𝑛}𝑛∊ℕ has a lower bound
- bounded if the set {𝑎𝑛}𝑛∊ℕ has an upper bound and lower bound
Sandwich Theorem
Given two convergent sequences (𝑎𝑛)𝑛∊ℕ and (𝑏𝑛)𝑛∊ℕ, and a sequence (𝑐𝑛)𝑛∊ℕ:
- if 𝑎𝑛≤ 𝑏𝑛 ≤ 𝑐𝑛for all 𝑛∊ℕ AND 𝑙𝑖𝑚𝑛→∞(𝑎𝑛) = 𝑙𝑖𝑚𝑛→∞(𝑏𝑛) → (𝑐𝑛)𝑛∊ℕ is convergent with 𝑙𝑖𝑚𝑛→∞(𝑐𝑛) = 𝑙𝑖𝑚𝑛→∞(𝑎𝑛) = 𝑙𝑖𝑚𝑛→∞(𝑏𝑛)
Cauchy Sequence
A sequence (𝑎𝑛)𝑛∊ℕ is a Cauchy sequence if:
- ∀𝜀>0 ∃𝑁∊ℕ ∀𝑛,𝑚≥𝑁 : |𝑎𝑛 - 𝑎𝑚| < 𝜀
Info
For sequences of real numbers:
- Cauchy sequence ↔ convergent sequence
Dedekind Completeness
- If subset 𝑆⊆ℝ is bounded from above, then 𝑠𝑢𝑝𝑟𝑒𝑚𝑢𝑚(𝑆) exists
- If subset 𝑆⊆ℝ is bounded from below, then 𝑖𝑛𝑓𝑖𝑚𝑢𝑚(𝑆) exists
Monotone Convergence Criterion
A sequence (𝑎𝑛)𝑛∊ℕ is convergent if both:
- monotonically decreasing (i.e. 𝑎𝑛≥𝑎𝑛+1 for all 𝑛)
- bounded from below (i.e. the set {𝑎𝑛}𝑛∊ℕ has a lower bound)
A sequence (𝑎𝑛)𝑛∊ℕ is convergent if both:
- monotonically increasing (i.e. 𝑎𝑛≤𝑎𝑛+1 for all 𝑛)
- bounded from above (i.e. the set {𝑎𝑛}𝑛∊ℕ has an upper bound)
Accumulation/Cluster/Partial-Limit Values/Point
𝑎̃∊ℝ is called an accumulation value of a sequence (𝑎𝑛)𝑛∊ℕ if either:
- there exists a subsequence (𝑎𝑛𝑘)𝑘∊ℕ with 𝑙𝑖𝑚𝑘→∞𝑎𝑛𝑘 = 𝑎̃ (i.e. subsequence is convergent)
- ∀𝜀>0: the 𝜀-neighborhood of 𝑎̃ contains infinitely many sequence members of (𝑎𝑛)𝑛∊ℕ
Improper Accumulation Value
- a sequence (𝑎𝑛)𝑛∊ℕ has the improper accumulation value ∞ ↔ (𝑎𝑛)𝑛∊ℕ is not bounded from above
- a sequence (𝑎𝑛)𝑛∊ℕ has the improper accumulation value ∞ ↔ (𝑎𝑛)𝑛∊ℕ is not bounded from below
Limit Superior - Limit Inferior
Given a sequence (𝑎𝑛)𝑛∊ℕ, an element 𝑎̃ ∊ ℝ∪{∞,-∞} = [-∞,∞] is called:
- limit superior of (𝑎𝑛)𝑛∊ℕif 𝑎̃ is the largest (improper) accumulation value of (𝑎𝑛)𝑛∊ℕ (denoted as 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞𝑎𝑛)
- limit inferior of (𝑎𝑛)𝑛∊ℕif 𝑎̃ is the smallest (improper) accumulation value of (𝑎𝑛)𝑛∊ℕ(denoted as 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞𝑎𝑛)
Limit superior relates to supremum:
- 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞𝑎𝑛 = 𝑙𝑖𝑚𝑛→∞𝑠𝑢𝑝𝑟𝑒𝑚𝑢𝑚{𝑎𝑘 | 𝑘 ≥ 𝑛}
Limit inferior relates to infimum:
- 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞𝑎𝑛 = 𝑙𝑖𝑚𝑛→∞𝑖𝑛𝑓𝑖𝑚𝑢𝑚{𝑎𝑘 | 𝑘 ≥ 𝑛}
Limit Superior/Inferior Algebra:
- 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛+𝑏𝑛) ≤ 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛) + 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑏𝑛)
- 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛·𝑏𝑛) ≤ 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛) · 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑏𝑛) # if 𝑎𝑛,𝑏𝑛≥ 0
- 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛+𝑏𝑛) ≥ 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛) + 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑏𝑛)
- 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛·𝑏𝑛) ≥ 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛) · 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑏𝑛) # if 𝑎𝑛,𝑏𝑛≥ 0
Limit Superior/Inferior Algebra Examples:
Example #1
Given the following sequences:
- (𝑎𝑛)𝑛∊ℕ = (1, -1, 1, -1, 1, …)
- (𝑏𝑛)𝑛∊ℕ = (0, 2, 0, 2, 0, …)
- (𝑎𝑛+ 𝑏𝑛)𝑛∊ℕ = (1, 1, 1, 1, 1, …)
- (𝑎𝑛· 𝑏𝑛)𝑛∊ℕ = (0, -2, 0, -2, 0, …)
Then:
- 1 = 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛+𝑏𝑛) ≤ 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛) + 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑏𝑛) = 1 + 2 = 3
- 1 = 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛+𝑏𝑛) ≥ 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛) + 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑏𝑛) = -1 + 0 = -1
Example #2
Given the following sequences:
- (𝑎𝑛)𝑛∊ℕ = (1, 0, 1, 0, 1, …)
- (𝑏𝑛)𝑛∊ℕ = (0, 2, 0, 2, 0, …)
- (𝑎𝑛· 𝑏𝑛)𝑛∊ℕ = (0, 0, 0, 0, 0, …)
Then:
- 0 = 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛·𝑏𝑛) ≤ 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑎𝑛) · 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞(𝑏𝑛) = 1 · 2 = 2
- 0 = 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛·𝑏𝑛) ≥ 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑎𝑛) · 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞(𝑏𝑛) = 0 · 0 = 0
Convergent/Divergent vs Limit Superior/Inferior
- (𝑎𝑛)𝑛∊ℕ is convergent ↔ 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞𝑎𝑛= 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞𝑎𝑛 ∉ {±∞}
- (𝑎𝑛)𝑛∊ℕ is divergent to ∞ ↔ 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞𝑎𝑛= 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞𝑎𝑛 = ∞
- (𝑎𝑛)𝑛∊ℕ is divergent to -∞ ↔ 𝑙𝑖𝑚𝑠𝑢𝑝𝑛→∞𝑎𝑛= 𝑙𝑖𝑚𝑖𝑛𝑓𝑛→∞𝑎𝑛 = -∞
Bolzano-Weierstrass Theorem
Bolzano-Weierstrass Theorem:
- sequence (𝑎𝑛)𝑛∊ℕ is bounded → (𝑎𝑛)𝑛∊ℕ has at least 1 accumulation value
Proof:
Click here to expand...
TODO
Divergent to Infinity
- divergent to infinity ↔ 𝑙𝑖𝑚𝑛→∞𝑎𝑛 = ∞ ↔ ∀𝑐>0 ∃𝑁∊ℕ ∀𝑛≥𝑁 : 𝑎𝑛>𝑐
- divergent to -infinity ↔ 𝑙𝑖𝑚𝑛→∞𝑎𝑛 = -∞ ↔ ∀𝑐<0 ∃𝑁∊ℕ ∀𝑛≥𝑁 : 𝑎𝑛<𝑐
Epsilon/𝜀-Neighborhoods
For 𝜀>0, (𝑥-𝜀,𝑥+𝜀) = 𝐵𝜀(𝑥) is the epsilon-neighborhood of 𝑥
𝑆⊆ℝ is called a neighborhood of 𝑥 if:
- ∃𝜀>0 : 𝐵𝜀(𝑥)⊆𝑆
Open Sets - Closed Sets
𝑆⊆ℝ is called open (in ℝ) if:
- ∀𝑥∊𝑆 ∃𝜀>0 : 𝐵𝜀(𝑥)⊆𝑆
𝑆⊆ℝ is called closed (in ℝ) if:
- 𝑆c = ℝ\𝑆 is open
Open and Closed Sets Examples:
- ⦰, ℝ are both open and closed
- [-2, 2] is closed but not open
- (-2, 2) is open but not closed
- (-2,2] is neither open nor closed
Closed Sets vs Convergent Sequences
both statements are equivalent:
- 𝑆⊆ℝ is closed ↔ for all convergent sequences (𝑎𝑛)𝑛∊ℕ with 𝑎𝑛∊𝑆 for all 𝑛∊ℕ we have: 𝑙𝑖𝑚𝑛→∞𝑎𝑛 ∊ 𝑆
- 𝑆⊆ℝ is closed ↔ any convergent sequences (𝑎𝑛)𝑛∊ℕ⊆𝑆 has limit point 𝑎̃∊𝑆
Compact Sets vs Convergent Subsequences
both statements are equivalent:
- 𝑆⊆ℝ is compact ↔ for all sequences (𝑎𝑛)𝑛∊ℕ with 𝑎𝑛∊𝑆 for all 𝑛∊ℕ, there exists a convergent subsequence (𝑎𝑛𝑘)𝑘∊ℕ with 𝑙𝑖𝑚𝑘→∞𝑎𝑛𝑘 ∊ 𝑆
- 𝑆⊆ℝ is compact ↔ any sequence (𝑎𝑛)𝑛∊ℕ⊆𝑆 has an accumulation value 𝑎̃∊𝑆
Compact Sets Examples:
- ⦰ is compact
- {5} is compact
- ℝ is not compact (is closed though) # for example (𝑎𝑛)𝑛∊ℕ = (𝑛)𝑛∊ℕ has no accumulation value 𝑎̃∊𝑆
-
[𝑐,𝑑] is compact
proof
Let (𝑎𝑛)𝑛∊ℕ⊆[𝑐,𝑑] thus:
- (𝑎𝑛)𝑛∊ℕ⊆[𝑐,𝑑] → (𝑎𝑛)𝑛∊ℕ is a bounded sequence
- (𝑎𝑛)𝑛∊ℕ⊆[𝑐,𝑑] → (𝑎𝑛)𝑛∊ℕ is has an accumulation value 𝑎̃∊ℝ # via Bolzano-Weierstrass Theorem
- (𝑎𝑛)𝑛∊ℕ⊆[𝑐,𝑑] → accumulation value actually satisfies 𝑎̃∊[𝑐,𝑑] # [𝑐,𝑑] is closed
Heine-Borel Theorem
For 𝑆⊆ℝ, we have:
- 𝑆 is compact ↔ 𝑆 is bounded and closed
Proof:
𝑆 is bounded and closed → 𝑆 is compact
Assume 𝑆⊆ℝ is bounded and closed.
Let (𝑎𝑛)𝑛∊ℕ be a sequence in 𝑆 thus:
- (𝑎𝑛)𝑛∊ℕ⊆𝑆 → (𝑎𝑛)𝑛∊ℕ⊆𝑆
- (𝑎𝑛)𝑛∊ℕ⊆𝑆 → (𝑎𝑛)𝑛∊ℕ is a bounded sequence
- (𝑎𝑛)𝑛∊ℕ⊆𝑆 → (𝑎𝑛)𝑛∊ℕ has an accumulation value 𝑎̃∊ℝ # via Bolzano-Weierstrass Theorem
- (𝑎𝑛)𝑛∊ℕ⊆𝑆 → accumulation value actually satisfies 𝑎̃∊𝑆 # because 𝑆 is closed
𝑆 is compact → 𝑆 is closed
Assume 𝑆⊆ℝ is compact. Prove that for any convergent sequences (𝑎𝑛)𝑛∊ℕ with 𝑎𝑛∊𝑆 for all 𝑛∊ℕ we have: 𝑙𝑖𝑚𝑛→∞𝑎𝑛∊𝑆
Let:
- (𝑎𝑛)𝑛∊ℕ be a convergent sequence in 𝑆
- (𝑎𝑛)𝑛∊ℕ has an accumulation value 𝑎̃∊𝑆 # via 𝑆 is compact
- 𝑙𝑖𝑚𝑛→∞𝑎𝑛 = 𝑎̃ ∊ 𝑆 # Every convergent sequence has only 1 accumulation value
- 𝑙𝑖𝑚𝑛→∞𝑎𝑛 ∊ 𝑆
𝑆 is compact → 𝑆 is bounded
Proof by Contradiction
𝑆 is not bounded → 𝑆 is not compact
Bounded Definition
- a set is bounded if it has an upper bound and lower bound
Not Bounded Definition
- a set is unbounded if (does not have an upper bound) or (does not have a lower bound)
Compact Definition
- ∀(𝑎𝑛)𝑛∊ℕ⊆𝑆 ∃(𝑎𝑛𝑘)𝑘∊ℕ : (𝑎𝑛𝑘)𝑘∊ℕis convergent AND 𝑙𝑖𝑚𝑘→∞𝑎𝑛𝑘∊𝑆
Not Compact Definition
- ∃(𝑎𝑛)𝑛∊ℕ⊆𝑆 ∀(𝑎𝑛𝑘)𝑘∊ℕ : (𝑎𝑛𝑘)𝑘∊ℕis not convergent OR 𝑙𝑖𝑚𝑘→∞𝑎𝑛𝑘∉𝑆
Assume 𝑆⊆ℝ is unbounded. Prove that 𝑆 is not convergent (i.e. there exists a sequence in 𝑆 such that all subsequences are not convergent)
- 𝑆⊆ℝ is unbounded → 𝑆⊆ℝ is unbounded
- 𝑆⊆ℝ is unbounded → There is a sequence (𝑎𝑛)𝑛∊ℕ⊆𝑆 such that |𝑎𝑛|>𝑛 for all 𝑛∊ℕ # 𝑆 does not have a lower bound or upper bound
- 𝑆⊆ℝ is unbounded → all subsequences of (𝑎𝑛)𝑛∊ℕ⊆𝑆 is not convergent
Next Topics
Absolutely Convergent - Absolute Convergence
A series 𝛴1≤𝑖≤∞𝑎𝑖 absolutely convergent if 𝛴1≤𝑖≤∞|𝑎𝑖| is convergent
Theorem:
- absolute convergence → convergence
Proof:
Click here to expand...
- 𝛴1≤𝑖≤∞|𝑎𝑖| is convergent → ∀𝜀>0 ∃𝑁∊ℕ ∀𝑛≥𝑚≥𝑁 : |𝛴1≤𝑖≤∞|𝑎𝑖|| < 𝜀 # via Cauchy criterion
- 𝛴1≤𝑖≤∞|𝑎𝑖| is convergent → ∀𝜀>0 ∃𝑁∊ℕ ∀𝑛≥𝑚≥𝑁 : 𝛴1≤𝑖≤∞|𝑎𝑖| < 𝜀 # all summands are positive
- 𝛴1≤𝑖≤∞|𝑎𝑖| is convergent → ∀𝜀>0 ∃𝑁∊ℕ ∀𝑛≥𝑚≥𝑁 : |𝛴1≤𝑖≤∞𝑎𝑖| < 𝜀 # triangle inequality |𝛴1≤𝑖≤∞𝑎𝑖| ≤ 𝛴1≤𝑖≤∞|𝑎𝑖|
- 𝛴1≤𝑖≤∞|𝑎𝑖| is convergent → 𝛴1≤𝑖≤∞𝑎𝑖 # via Cauchy criterion
Majorant Criterion
Theorem
Let 𝛴1≤𝑖≤∞𝑎𝑖be a series. If there is 𝑛0∊ℕ and a convergent series 𝛴1≤𝑖≤∞𝑏𝑖satisfying the following for all 𝑖≥𝑛0:
- 𝑏𝑖≥0
- |𝑎𝑖| ≤ 𝑏𝑖
Then 𝛴1≤𝑖≤∞𝑎𝑖 is an absolutely convergent series
Proof
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Apply the Cauchy criterion to series 𝛴1≤𝑖≤∞𝑏𝑖:
- 𝛴1≤𝑖≤∞𝑏𝑖 is a convergent series → ∀𝜀>0 ∃𝑁≥ℕ ∀𝑛≥𝑚≥𝑁 : |𝛴𝑚≤𝑖≤𝑛𝑏𝑖| < 𝜀 # via the Cauchy criterion
- 𝛴1≤𝑖≤∞𝑏𝑖 is a convergent series → ∀𝜀>0 ∃𝑁≥𝑛0 ∀𝑛≥𝑚≥𝑁 : |𝛴𝑚≤𝑖≤𝑛𝑏𝑖| < 𝜀 # choose an 𝑁≥𝑛0
- 𝛴1≤𝑖≤∞𝑏𝑖 is a convergent series → ∀𝜀>0 ∃𝑁≥𝑛0 ∀𝑛≥𝑚≥𝑁 : 𝛴𝑚≤𝑖≤𝑛𝑏𝑖 < 𝜀 # because 𝑏𝑖≥0
- 𝛴1≤𝑖≤∞𝑏𝑖 is a convergent series → ∀𝜀>0 ∃𝑁≥𝑛0 ∀𝑛≥𝑚≥𝑁 : 𝛴𝑚≤𝑖≤𝑛|𝑎𝑖| < 𝜀 # because |𝑎𝑖| ≤ 𝑏𝑖
- 𝛴1≤𝑖≤∞𝑏𝑖 is a convergent series → 𝛴𝑚≤𝑖≤𝑛|𝑎𝑖| is a convergent series # via the Cauchy criterion
- 𝛴1≤𝑖≤∞𝑏𝑖 is a convergent series → 𝛴𝑚≤𝑖≤𝑛𝑎𝑖 is an absolutely convergent series # by definition of absolutely convergent series
Minorant Criterion
Theorem
Let 𝛴1≤𝑖≤∞𝑎𝑖be a series with 𝑎𝑖≥0. If there is 𝑛0∊ℕ and a divergent series 𝛴1≤𝑖≤∞𝑏𝑖satisfying the following for all 𝑖≥𝑛0:
- 𝑏𝑖≥ 0
- 𝑎𝑖 ≥ 𝑏𝑖
Then 𝛴1≤𝑖≤∞𝑎𝑖 is a divergent series
Proof
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TODO
Example
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𝛴1≤𝑖≤∞(1/√𝑖) is divergent because:
- √𝑖 ≤ 𝑖 ↔ (1/√𝑖) ≥ (1/𝑖) for all 𝑖
- 𝛴1≤𝑖≤∞(1/𝑖) is the harmonic series which is known to be divergent
Thus the minorant criterion is satisfied → 𝛴1≤𝑖≤∞(1/√𝑖) is divergent