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Sequence Convergence
Let (xn):ℝ→ℝ be a sequence and let x∈ℝ, then we say that (xn) converges to x and write (xn)→x when the following holds true ∀ϵ∈ℝ+,∃n∈ℕ0 such that ∀n∈ℕ0,n≥N⟹|xn−x|<ϵ

Note that you may come across various other notations for this definition in other resources, the main ones to note will be: xn→x as n→∞, or even more shortened as xn→x, sometimes limit notation will be used: limn→∞⁡xn=x or just lim⁡xn=x

Convergent Sequence Doesn't Require Strict Inequality
(an)→L is equivalent to ∀ϵ∈ℝ+,∃N∈ℕ0, st ∀n∈ℕ0,n≥N⟹|an−L|≤ϵ
⟹ Suppose (an)→L, now let ϵ∈ℝ, and consider ϵ2, then since (an)→L we get some N∈ℕ0 such that for every n≥N we have |an−L|<ϵ2≤ϵ as needed. ⟸ Assume the other direction, and we want to prove (an)→L so let ϵ∈ℝ+ therefore we get an N∈ℕ0 such that for all n≥N we have |an−L|≤ϵ2<ϵ as needed.
Limit Notation
Suppose that xn→x then we write limn→∞⁡xn:=x

Note that if you have an arbitrary sequence (yn) which you don't know if it converges to anything and you write limn→∞⁡yn=L for some L∈ℝ, this is two assertions, first that (yn) converges to something, and the value it converges to is L.

Eventually Increasing Index Mapping Maintains Limit
Suppose that limn→∞⁡xn=x and f:ℕ1→ℕ1 is an eventually increasing function, then limn→∞⁡xf(n)=x
Reciprocal Power Goes to Zero
Let (xn):ℕ0→ℝ be the sequence such that xn=1nα for some α∈ℝ>0, then (xn)→0
Let ϵ∈ℝ>0, we need to pick an N∈ℕ1 such that for n≥N we have that |1nα−0|<ϵ, it's clear that 1nα>0 so therefore we can drop the absolute values so we just need an n that satisfies 1nα<ϵ⟺1ϵ1α<n By setting N=⌈1ϵ1α⌉+1 then we have that for any n≥N 1ϵ1α<⌈1ϵ1α⌉+1=N≤n So that 1ϵ1α<n as needed.
Limit of Sine Doesn't Exist at Infinity
Show that limn→∞⁡sin⁡(nπ2) doesn't exist using the definition of limit.
To show that the limit doesn't exist we will use the negation of the definition and show that is true, so we have to prove that ∀L∈ℝ,∃ϵ∈ℝ+ st ∀N∈ℕ0,∃n∈ℕ0 st (n≥N∧|an−L|≥ϵ) So let L∈ℝ and take ϵ=14 let N∈ℕ0.

Before finding our n value, consider sequence an=sin⁡(nπ2), and that |an−an+1|=1.

Now to find our n value we look at the requirement that |an−L|≥ϵ which means that it's not true that |an−L|<ϵ, so that in other words an∉(L−ϵ,L+ϵ), due to the fact that ℓ((L−ϵ,L+ϵ))=12 then given that |aN−aN+1|=1 then exactly one of aN,aN+1 is not in (L−ϵ,L+ϵ) therefore we can set n respectively to force |an−L|≥ϵ as needed.

Non-Zero Limit Implies Eventually Non-Zero Sequence
Suppose that limn→∞⁡an=L≠0 then there exists some N∈ℕ0 such that an≠0 for all n≥N.

Suppose for the sake of contradiction that that was not true, so that for every N we had some n≥N such that an=0, let's derive a contradiction.

Since (an)→L then specifically for ϵ=L2 we have some N′∈ℕ0 such that for every n≥N′ we have |an−L|≤L2, therefore by our contradiction assumption we also know there is some k≥N′ such that ak=0 so therefore because the limit exists we have |ak−L|≤L2 but ak=0 so that |L|≤L2 which is impossible so therefore we have a contradiction and so the original statement holds true.

Sequence Goes to Positive Infinity
We say that a sequence (xn) goes to positive infinity and notate it as (xn)→∞ when ∀M∈ℝ+,∃N∈ℕ0 such that ∀n∈ℕ0,n≥N⟹xn≥M

You can probably guess the next definition.

Sequence Goes to Negative Infinity
We say that a sequence (xn) goes to negative infinity and notate it as (xn)→−∞ when ∀M∈ℝ−,∃N∈ℕ0 such that ∀n∈ℕ0,n≥N⟹xn≤M

Note that these definitions formalize our idea that if something approaches infinity, namely that this object is greater (or smaller) than every possible other object.

Sequence Goes to Infinity
We say that a sequence goes to infinity if it goes to positive infinity or negative infinity, and write (xn)→±∞
Log Goes to Infinity
Show that (ln⁡(n))n=1∞→∞
Let M∈ℝ+ and take N=⌈eM⌉ and let n≥N therefore n=⌈eM⌉+k for some k∈ℕ0 since ln⁡ is increasing then we know that M=ln⁡(eM)≤ln⁡(⌈eM⌉)≤ln⁡(⌈eM⌉+k) so that M≤ln⁡(n) as needed therefore it goes to infinity
Two Limits that get Arbitrarily Close Have the Same Limit
Suppose htat (an),(bn) are sequence of real numbers such that |an−bn|<1n. If L=limn→∞⁡an exists, then limn→∞⁡bn=L as well

Let ϵ∈ℝ+ we need to pick an N∈ℕ0 such that for every n≥N we have that |bn−L|<ϵ.

Since limn→∞⁡an=L then we can set ϵ′=f(ϵ) for any function f:ℝ+→ℝ+ of our choosing, to get some N′ such that for any n≥N′ we have |an−L|<f(ϵ)

Morover note that for this given ϵ we can always find a K∈ℕ1 such that 1K<g(ϵ) where g:ℝ+→ℝ+ is of our choosing, By picking N=max⁡(N′,K) we know that

|bn−L|=|bn−an+an−L|≤|bn−an|+|an−L|≤1n+f(ϵ)≤1K+f(ϵ)≤g(ϵ)+f(ϵ)

to obtain the desired inequality one would have to pick f,g such that f(ϵ)+g(ϵ)<ϵ, a simple choice of f(x)=g(x)=x4 yields |bn−L|<ϵ2<ϵ

Bounded Sequence
Suppose that (xn):ℕ0→ℝ, is a sequence, then we say that it is bounded when there exists some M∈ℝ+ such that for any i∈ℕ0 we have |xi|≤M
If a Sequence Converges it is Bounded
Suppose that (xn)→x then (xn) is bounded

Let a∈ℝ since (xn) converges then we know that there is some N such that for all n≥N we have |xn−x|≤a, therefore |xn|≤a+|x|

Set I:={0,...,N−1} and we define L:=max⁡({|xi|:i∈I}), then it should be clear that for any k∈I we have |xk|≤L

Finally, we can see that the value M:=max⁡(L,a+|x|) has the property so that for any j∈ℕ0 |xj|≤M so that (xn) is bounded.

Pointwise Function Sequence
Suppose that (f1,f2,f3,…) are functions, of the form fi:X→Y then it's pointwise function sequence at x∈X is defined as the sequence (f1(x),f2(x),f3(x),…) denoted by (fn(x))
Pointwise Function Convergence
Suppoes that (fn) is a sequence of functions of the form fi:X→ℝ and we have another function f:X→ℝ then we say that (fn) converges pointwise to f(x) whenever the pointwise function sequence (fn(x)) converges to f(x)
Squeeze Theorem
Suppose that (an),(bn),(cn):ℕ1→ℝ are all sequences such that for all k∈ℕ1 we have ak≤bk≤ck Moreover suppose that limn→∞⁡an=limn→∞⁡cn=L, then limn→∞⁡bn=L

Let ϵ∈ℝ+, because the limits of (an),(cn) exist, then we get Na,Nc∈ℕ0 such that for any n≥Na we have |an−L|<ϵ and for any m≥Nc we have |cm−L|<ϵ.

Recall that these two inequalities are equivalent to L−ϵ<an<L+ϵ and L−ϵ<cm<L+ϵ. Therefore by setting N=max⁡(Na,Nc) then for any n≥N both of the aformentioned inequalities hold true, showing that L−ϵ<an≤bn≤cn<L+ϵ which is to say that |bn−L|<ϵ

Function Limit at Positive Infinity
Suppose that f:A→ℝ, where A⊆ℝ, and L∈ℝ. We say that f has limit L at positive infinity, and write limx→∞⁡f(x)=L, if for every ϵ∈ℝ+, there exists N∈ℝ such that for every x∈A, x≥N⟹|f(x)−L|<ϵ.
Integer Values Determine Monotone Function Limit at Infinity
Suppose that f:ℝ→ℝ is non-decreasing, f(x)≤L for all x∈ℝ, and limn→∞⁡f(n)=L. Then limx→∞⁡f(x)=L.
Let ϵ∈ℝ+. Since limn→∞⁡f(n)=L, there is N∈ℕ such that L−ϵ<f(N). If x≥N, then f(N)≤f(x) because f is non-decreasing. Also f(x)≤L by assumption. Therefore L−ϵ<f(N)≤f(x)≤L<L+ϵ. Hence |f(x)−L|<ϵ for all x≥N by absolute value bounds distance, so by the definition of function limit at positive infinity, limx→∞⁡f(x)=L.
limsup
Suppose that (an) is a sequence, then we define another sequence sn:=sup⁡({ak:k≥n}) and then we define the limsup of (an) as lim sup⁡(an):=limn→∞⁡sn
liminf
Suppose that (an) is a sequence, then we define another sequence in:=inf⁡({ak:k≥n}) and then we define the liminf of (an) as lim inf⁡(an):=limn→∞⁡in
limsup Exists iff the Sequence is Bounded Above
As per title.
A Sequence Eventually gets Close to Limsups Limit
Let (an):ℕ1→ℝ and suppose that lim sup⁡(an)→L , then for any ϵ∈ℝ+ there exists an N∈ℕ1 such that for any n≥N an<L+ϵ
Let ϵ∈ℝ+ then there exists an N∈ℕ1 such that |sup⁡({ak:k≥n})−L|<ϵ which is true if and only if L−ϵ<sup⁡({ak:k≥n})<L+ϵ thus since an≤sup⁡({ak:k≥n}) by transitivity we know that an<L+ϵ
Convergence iff Lim Sup and Inf are Equal
(an)→L⟺lim sup⁡(an)=L=lim inf⁡(an)

Define sn:=sup⁡({ak:k≥n}) and in:=inf⁡({ak:k≥n}).

Now suppose that lim sup⁡(an)=lim inf⁡(an)=L, since ak∈{ak:k≥n} , then as they are defined as upper and lower bounds, we have in≤an≤sn for all n∈ℕ1 then by the squeeze theorem (an)→L .

Now suppose that lim sup⁡(an)=lim sup⁡(an)=L, and let's prove (an)→L, let ϵ∈ℝ+, therefore we get an N∈ℕ1 such that for every n≥N we have |an−L|<ϵ iff L−ϵ≤an≤L+ϵ, thus L+ϵ and L−ϵ are upper and lower bounds of {ak:k≥n} respectively, since the sup and the inf are the lest and greatest of their bounds respectively so we have that sup⁡({ak:k≥n})≤L+ϵ and L−ϵ≤inf⁡({ak:k≥n}) combining the two we obtain L−ϵ≤inf⁡({ak:k≥n})≤sup⁡({ak:k≥n})≤L+ϵ which is equivalent to both |inf⁡({ak:k≥n})−L|≤ϵ and |sup⁡({ak:k≥n})−L|≤ϵ therefore lim sup⁡(an)=lim inf⁡(an)=L

Sum Law
Suppose that limx→a⁡f(x) and limx→a⁡g(x) exist, then
limx→a⁡[f(x)+g(x)]=limx→a⁡f(x)+limx→a⁡g(x)
TODO
Cauchy with Converging Subsequence Implies Entire Sequence Converges
Let (xn) be a cauchy sequence and (xσ(n)) a subsequence such that limk→∞⁡xσ(k)=L then limn→∞⁡xn=L.
Let ϵ∈ℝ+, since (xn) is cauchy we obtain some N1 such that for any n,m≥N,|an−am|≤ϵ2, on the other hand we see that there is some N2 such that for all n≥N2 we have |xσ(n)−L|≤ϵ2, so let N=max⁡(N1,N2) and let n≥N, consider σ(n), we will want this value to be greater or equal to N1 so we can use it in-place of m, if it turns out that σ(n)<N1 then since σ is increasing there exists some k>n≥N2 such that σ(k)≥N1, then note: |xn−L|=|xn−xσ(k)+xσ(k)−L|≤|xn−xσ(k)|+|xσ(k)−L|<ϵ2+ϵ2=ϵ
Strictly Increasing Natural Number Function Surpasses All Values
Suppose f:ℕ1→ℕ1 is increasing, then for any K∈ℝ there exists an n∈ℕ1 such that f(n)>K

Before we start this proof, note that for any n∈ℕ1 we have that f(n)<f(n+1) which means that f(n)+1≤f(n+1) which is to say that 1≤f(n+1)−f(n), running with this we can generalize this to say that for any j≤k∈ℕ1 f(n+j)−f(n+k)≥j−k

With that in mind, iff(1)>K we are done, so then suppose that f(1)≤K, let α=K+1−f(1)∈ℕ1 but then we know that f(1+α)−f(1)≥α=K+1−f(1) adding f(1) to both sides tells us that f(1+α)≥K+1>K as needed.

For all, There Exists Past a Point Yields Ordered Satisfaction
Suppose that you know the following statement holds true: ∀x∈ℕ1,∃Nx∈ℕ1,fx:ℕ1→ℕ1 st ,n≥Nx⟹P(x,fx(n)) where fx is strictly increasing. Then there exists an order sequence of values in ℕ1 where (α1≤α2≤α3≤α4≤…) such that P(1,α1)∧P(2,α2)∧P(3,α3)∧⋯

Plugging in x=1 we obtain some N1,f1 such that for all n≥N1 we have P(1,f1(n)), let α1=f1(N1) note that since N1≥N1 we have P(1,f1(N1))=P(1,α1)

Now for any k∈ℕ2 we similarly get an Nk,fk such that for all n≥Nk we have P(k,fk(n)), now consider the value fk(Nk), we'd like to set αk to it, but we have no idea if fk(Nk)≥αk−1, but since we do know that αk−1∈ℕ1 then since fk is increasing we know that there is a value Nk+m for some m∈ℕ1 such that fk(Nk+m)≥αk−1 , since Nk+m≥Nk then clearly P(k,fk(Nk+m)) holds true, and thus we define αk=f(Nk+m), so that P(k,αk) also holds. Notice that we've also just proven that αk≥αk−1 making them increasing.

Limit to a Limit
Suppose (xn):ℕ1→ℝ and that Lk are real numbers such that limk→∞⁡Lk=L, if for each k∈ℕ1 there is a subsequence of (xn) converging to Lk show that some subsequence of (xn) converges to L.

We will construct a subsequence (xσ(n)) such that |xσ(k)−L|<1k. By doing so, we will have solved the problem, because for any ϵ∈ℝ+ there is always a k∈ℕ1 such that 1k<ϵ which shows that |xσ(k)−L|<ϵ by transitivity.

Let k∈ℕ1 since (Ln)→L then by considering 12k we know that there is an Nk′∈ℕ1 such that for all n≥Nk′ we have |Ln−L|<12k, now consider any mk≥Nk′, thus we know that |Lmk−L|<12k.

Now since mk∈ℕ1 then there exists a subsequence xσmk(n)→Lmk , therefore using ϵ=12k we get a Nk such that for all n≥Nk,|xσmk(n)−Lmk|<12k, therefore we have

|xσmk(n)−L|=|xσmk(n)−Lm+Lm−L|≤|xσmk(n)−Lmk|+|Lmk−L|<12k+12k=1k

Initially it might seem as simple as taking the subsequence xσm1(N1),xσm2(N2),xσm3(N3),… but there's no guarentee that this subsequence has increasing indices (which is a requirement of a subsequence), therefore we need more work.

Condensing what we've proven above, we've shown that ∀k∈ℕ1,∃Nk∈ℕ1,σmk:ℕ1→ℕ1 st ∀n≥N2,P(k,σm(n))

Where P(k,v):=|xv−L|<1k, and since σmk defines a subsequence then it is strictly increasing, therefore there exists an ordered sequence (α1≤α2≤α3≤…) such that P(k,αk) which is to say that |xαk−L|<1k so that the following subsequence works (xα1,xα2,…) or in another notation with σ(n)=αn we are using the subsequence (xσ(n))

Telescoping Triangle Inequality
Let j≤k∈ℕ0 and (an) be a sequence, then we have the following |aj−ak|≤|aj−aj+1|+|aj+1−aj+2|+⋯+|ak−1−ak|
which is obtained by using the fact that we can insert 0=−ai+ai into the absolute value and then use the triangle inequality to break it, the general result is proven using induction using this fact in the induction step.
Series of Differences Converges Implies Cauchy
Let (an) be a sequence such that limN→∞⁡∑n=1N|an−an+1|<∞, show that (an) is cauchy.

Let ϵ∈ℝ+ and set Sm:=∑i=1k−1|ai−1−ai| since we we assumed that limN→∞⁡SN exists, then the sequence is cauchy so we get some N′ such that for any a,b≥N,|Sa−Sb|≤ϵ and take N=N′ and let n,m≥N, and without loss of generality assume that n≤m |an−am|≤|an−an+1|+|an+1−an+2|+⋯+|am−1−am|=Sm−Sn=|Sm−Sn|≤ϵ where we've used the generalized triangle inequality and the fact that Sk is increasing, as each higher index adds a non-negative element to the sum.

Cauchy Sequence Implies Subsequence with Convergent Differences
If (xn)n=1∞ is cauchy, show that it has a subsequence (xσ(n)) such that ∑k=1∞|xσ(k)−xσ(k+1)|<∞

Recall that a geometric series of halves is bounded, and thus we're inspired to try to make each |xσ(k)−xσ(k+1)|≤12k, call this property α.

Let's construct this subsequence, for any k∈ℕ1 consider ϵ=12k, then we get an Nk such that for all n,m≥Nk,|an−am|≤12k, and consider the sequence xN1,xN2,xN3,…, we'll show it satisfies α.

Let j∈ℕ1, and consider Nj,Nj+1, in the case that Nj≥Nj+1 then note that |xNj−xNj+1|≤12j+1≤12j (where n=Nj,m=Nj+1), in the case that Nj<Nj+1 we also get that |xNj−xNj+1|≤12j so α is satisfied for this subsequence. Therefore ∑k=1∞|xNk−xNk+1|≤∑k=1∞12k=1 as needed.

Zig-Zag Sequence has Nested Bound
Suppose that (an) is a sequence such that a2n≤a2n+2≤a2n+3≤a2n+1 for all n∈ℕ0 then for any k,n∈ℕ0 n≥2k+1⟹an∈[a2k,a2k+1]
Proven by induction.
Zig-Zag Sequence is Cauchy iff Differences go to Zero
Suppose that (an) is a sequence such that a2n≤a2n+2≤a2n+3≤a2n+1 for all n∈ℕ0, then this sequence is cauchy iff limn→∞⁡|an−an+1|=0.

⟹ this direction is easy, let ϵ∈ℝ+, since (an) is cauchy we get some N′ such that for all n,m≥N′,|an−am|<ϵ, and so take N=N′ then specifically for n,n+1≥N we have that ϵ>|an−an+1|=||an−an+1|−0| as needed.

⟸ Assume that limn→∞⁡|an−an+1|=0 and now we want to prove that (an) is cauchy so let ϵ∈ℝ+ and so we obtain some N such that for any n≥N we have that |an−an+1|≤ϵ take N′=2N+1 and let n,m≥N′ by our lemma, we see that an,am∈[a2N,a2N+1], but then again since 2N,2N+1≥N we see that |a2N+1−a2N|≤ϵ and therefore |an−am|≤ϵ as needed.

Monotone Increasing Sequence
A sequence (an)n=1∞ is said to be monotone increasing whenever we have: an≤an+1 for any n∈ℕ1
Monotone Decreasing Sequence
A sequence (an)n=1∞ is said to be monotone decreasing whenever we have: an≥an+1 for any n∈ℕ1
Bounded Above and Monotone Increasing Converges to Supremum
A monotone increasing sequence that is bounded above converges to L=sup⁡(im⁡((an)))

Since (an)n=1∞ is bounded above, then so is im⁡((an))⊆ℝ therefore since ℝ has the least upper bound property, we know that sup⁡(im⁡((an))) exists, call it L and we'll prove that (an) converges there.

Let ϵ∈ℝ+ by definition of the supremum we know that L−ϵ is not an upper bound for A, in other words there exists some element aN∈im⁡((an)) such that L−ϵ<aN

Since (an) is increasing, we know that for any n∈ℕ,n≥N,aN≤an, moreover L is an upperbound so that we get L−ϵ<aN≤an≤L<L+ϵ⟹L−ϵ<an<L+ϵ therefore |an−L|<ϵ, therefore limn→∞⁡an=L as needed.

Bounded Below and Monotone Decreasing Converges to Infimum
A monotone decreasing sequence that is bounded below converges to L=inf⁡(im⁡((an)))
If (an) is decreasing and bounded below by B, then the sequence (−an) is increasing and bounded above by −B. Thus the sequence (−an)n=1∞ has limit L=sup⁡(im⁡((−an))) recall that sup⁡(im⁡((−an)))=−inf⁡({−x:x∈im⁡((−an))})=−inf⁡(im⁡(an)) So that −L=inf⁡(im⁡((an))). Then note that limn→∞⁡−an=L implies that −L=limn→∞⁡an so we conclude that limn→∞⁡an=inf⁡(im⁡((an))) as needed.
Nested Square Root Twos
Consider the sequence defined as follows for α∈ℝ+
  • a1=α
  • an+1=α+an for every n≥1
Show that it converges

One way to show that it converges would to be the use the MCT for monotone increasing sequences. We start by showing that it is monotone increasing by showing it is strictly increasing.

For the base case we need to verify that a1<a2 which is equivalent to showing that α<α+α this is true because ⋅ is order preserving and we know that α<α+α because α>0.

For the induction step assume that ak<ak+1 and we'll prove that ak+1<ak+2. Note that ak+2=α+ak+1 by the induction hypothesis we can see that α+ak+1>α+ak=ak+1, thus we have that ak+2>ak+1 as needed.

We'll move on to showing that it is bounded now, to do so we claim that α+1 is an upper bound, we'll show it is by induction, so for n=1 we see that α≤α+1, now assuming it's true for k∈ℕ1 we'll show that ak+1≤α+1. We note that ak+1=α+ak and thus by the induction hypothesis we have α+ak≤α+α+1, but note that α+α+1<α+2α+1=(α+1)2=α+1 thus chaining inequalities we obtain ak+1≤α+1 as needed, the choice of α+1 was inspired by thinking ahead to induction, what we would have to prove and figuring out what it can be upper bounded.

Since we've shown monotone increasing and bounded above, then the sequence converges to some L∈ℝ, if that's true then L=α+L because limn→∞⁡an+1=limn→∞⁡α+an therefore L2=α+L so that L2−L−α=0 so by the quadratic formula we have L=1±1+4α2 but since an≥0 for all n∈ℕ1 then we know that L≥0 and therefore specifically it converges to L=1+1+4α2

Inequality From Sequence to Limit
Suppose (an),(bn) are converging sequences such that an≤bn for all n∈ℕ1 then limn→∞⁡an≤limn→∞⁡bn
Nested Intervals
Suppose that In=[an,bn] are nonempty closed intervals such that In+1⊆In for every n∈ℕ1, then ⋂n∈ℕ1In≠∅

Since [an+1,bn+1]⊆[an,bn] then we know that an≤an+1≤bn+1≤bn for any n∈ℕ1 and therefore we conclude that (an) is monotone increasing and that (bn) is monotone decreasing. Also note that an≤bn≤b1 and a1≤an≤bn so that by transitivity we obtain an≤b1 and a1≤bn which is to say that an is bounded above and that bn is bounded below.

Therefore from both versions of the montone convergence theorem we see that an and bn converge to a:=sup⁡(im⁡((an))),b:=inf⁡(im⁡(bn)) respectively and from the above proposition we see that a≤b

By the definition of the supremum and infimum, we also have that ak≤a≤b≤bk for all k∈ℕ1 meaning that a,b belongs to Ik, so that {a,b}⊆⋂n∈ℕ1In and so it must not be empty.

Bolzano-Weierstrass
Every bounded sequence of real numbers has a convergent subsequence.

Let (an) be bounded by B, therefore im⁡((an))⊆[−B,B]. If I is an interval containing infinitely man points of ths equence (an) and I=J1∪J2 then at least one of J1,J2 has infinitely many elements or we would have a contradiction.

With that in mind we construct the following sequence of intervals

  • I1=[a1,b1] where a1=−B and b1=B
  • Consider L=[am,am+bm2] and R=[am+bm2,bm]
    • If L∩im⁡(an) is infinite then Im+1=L
    • If R∩im⁡(an) is infinite then Im+1=R
    • If both are infinite just use Im+1=L

We now construct a subsequence as follows: Since every Ik∩im⁡((an)) is infinite then we know there is some aj∈Ik∩im⁡((an)), this defines a function σ:ℕ1→ℕ1 such that σ(k)=j and we use this to make our subsequence (aσ(n))

We will now show that this subsequence converges. Note that by construction we see that Ik+1⊆Ik for all k∈ℕ1, and that each is non-empty, so that by the nested intervals lemma there exists an L∈⋂n∈ℕ1In, let's show that the subsequence converges there. Moreover note that |Ik|=22−kB

Let ϵ∈ℝ+ then there exists some k∈ℕ1 such that 2k−2B≤ϵ and thus by definition of σ we have aσ(k),L∈Ik and thus |aσ(k)−L|≤|Ik|=22−kB≤ϵ which shows that (aσ(n))→L