Real Sequences#
Definition: Real Sequence
A real sequence is a sequence of real numbers.
Convergence#
Definition: Convergence of Real Sequences
Let \((a_n)_{n \in \mathcal{D}}\) be a real sequence and let \(L \in \mathbb{R}\).
We say that \(L\) is the limit of \((a_n)_{n \in \mathcal{D}}\) if for each \(\varepsilon \gt 0\) there exists some \(N \in \mathcal{D}\) such that
Notation
The most common notation is
In text, one also writes "\(a_n \to L\) as \(n \to \infty\)" or just "\(a_n \to L\)". Sometimes, one might also encounter \(a_n \underset{n \to \infty}{\longrightarrow} L\) and \(a_n \overset{n \to \infty}{\longrightarrow} L\).
Definition: Convergence
A real sequence is convergent if there exists some \(L \in \mathbb{R}\) which is its limit:
Theorem: Uniqueness of the Limit
If a real sequence is convergent, then it has exactly one limit.
Proof
We need to prove that if \(\lim_{n \to \infty} a_n = L\) and \(\lim_{n \to \infty} a_n = M\), then \(L = M\).
Pick some arbitrary \(\varepsilon \gt 0\).
Since \(\{a_n\} \to L\), by definition, there exists some integer \(N_L\) such that
Similarly, since \(\{a_n\} \to M\), there exists some integer \(N_M\) such that
Now, let \(N = \max\{N_L, N_M\}\). For all \(n \ge N\), both of the aforementioned inequalities hold. Therefore, for all \(n \ge N\), we have
Therefore,
So far, the argument does not actually depend on the particular choice of \(\varepsilon\) and is thus true for every \(\varepsilon \gt 0\). This means that \(\frac{1}{2}|L - M|\) is smaller that every positive real number. This is only possible if \(\frac{1}{2}|L - M|\) is zero which is in turn only possible if \(|L - M| = 0\). Therefore, \(L = M\).
Definition: Zero Sequence
A zero sequence is a real sequence whose limit is zero.
Definition: Divergence of Real Sequences
A real sequence is divergent if it is not convergent.
Definition: Divergence towards Positive Infinity
A real sequence \((a_n)_{\mathcal{D}}\) diverges towards positive infinity if for each \(A \in \mathbb{R}\) there is some \(N \in \mathcal{D}\) such that
Notation
Definition: Divergence towards Negative Infinity
A real sequence \((a_n)_{n \in \mathcal{D}}\) diverges towards negative infinity if for each \(A \in \mathbb{R}\) there is some integer \(N \in \mathcal{D}\) such that
Notation
Note
Even though we use limit notation for sequences that diverge towards positive or negative infinity, these sequences are not convergent and their limits do not exist. However, we often talk of "infinite limits" because of the notation we have chosen. Just remember that, strictly speaking, the "limits" of divergent real sequences never exist.
Theorem: Approaching Zero
A real sequence \(\{a_n\}\) converges to \(L \in \mathbb{R}\) if and only if
Proof
TODO
Theorem: Cauchy Criterion
A real sequence \(\{a_n\}\) is convergent if and only if, for each \(\varepsilon \gt 0\), there exists some integer \(N\) such that
Proof
TODO
Note
Sequences for which the above holds, i.e. convergent sequences, are also known as Cauchy sequences.
Theorem: Boundedness of Convergent Sequences
Every convergent real sequence is bounded.
Proof
Suppose that \(\{a_n\}\) converges to some \(L \in \mathbb{R}\). Then, by definition, for each \(\varepsilon \gt 0\), there exists some integer \(N\) such that
Choose \(\varepsilon = 1\). The actual choice is irrelevant, it will just result in a different bound. Then,
Let's look at the absolute value of \(a_n\):
Using the triangle inequality, we get
For all \(n \ge N\),
and so \(|a_n| \lt 1 + |L|\) for all \(n \ge N\). This means that the modulus of all sequence terms from the \(N\)-th one onwards is less than \(1 + |L|\). Amongst the first \(N-1\) terms of the sequence, choose the one whose modulus \(M\) is greatest. The moduli of the first \(N-1\) terms are thus all less than or equal to \(M\). Essentially, we have
- \(|a_n| \le M\) for every \(n \lt N\);
- \(|a_n| \lt 1 + |L|\) for every \(n \ge N\).
Let \(B = \max\{M, 1 + |L|\}\). Therefore, \(|a_n| \le B\) for every integer \(n\) and so \(a_n\) is bounded.
Theorem: Limit Inequality
Let \((a_n)_{n \in \mathcal{D}_a}\) and \((b_n)_{n \in \mathcal{D}_b}\) be convergent real sequences.
If there exists some \(N \in \mathcal{D}_a \cap \mathcal{D}_b\) such that \(a_n \le b_n\) for all \(n \gt N\), then
Proof
TODO
Theorem: Convergence to Zero
A real sequence \((a_n)\) converges to zero if and only if \((|a_n|)\) converges to zero.
Proof
TODO
The Squeeze Theorem for Sequences
Let \(\{a_n\}\), \(\{b_n\}\) and \(\{c_n\}\) be real sequences such that both \(\{a_n\}\) and \(\{b_n\}\) converge to \(L \in \mathbb{R}\).
If there exists an integer \(N\) such that \(a_n \le c_n \le b_n\) for all \(n \ge N\), then \(\{c_n\}\) also converges to \(L\).
Proof
Let \(\varepsilon \gt 0\). Since \((a_n)_{n \in \mathbb{N}}\) and \((b_n)_{n \in \mathbb{N}}\) are convergent, there exist \(N_a, N_b \in \mathbb{N}\) such that
We also assumed that there is an integer \(N\) such that
It follows then
From this we see that
This is the same as
Example: Limit of \(\frac{n}{2^n}\)
We look at the following sequence:
Using induction, it is fairly easy to prove that \(2^n \ge n^2\) for all \(n \ge 4\). We thus have the following:
Multiply both sides by \(n\):
If we choose \(a_n = 0\) to be the constant real sequence which always gives zero and we choose \(b_n = \frac{1}{n}\), then we see that
since \(\lim_{n\to \infty} a_n = 0\), \(\lim_{n \to \infty} b_n = 0\) and \(a_n \le c_n \le b_n\) for all \(n \ge 4\).
This can be extended to show that
Example: Limit of \(\sqrt[n]{n}\)
We examine the following real sequence:
By looking at a few terms, we may guess that \((a_n)\) converges to \(1\):
To prove this, we examine the real sequence \(b_n = \sqrt[n]{n} - 1\). We immediately see that
and so
Using the binomial theorem, we get that
Therefore,
We have
and we can take the square root:
Now, we recall the definition of \(b_n\) as \(b_n = a_n - 1\):
We have \(\lim_{n \to \infty} 1 = 1\) and
Therefore:
Theorem: Limit Arithmetic
If two real sequences \(\{a_n\}\) and \(\{b_n\}\) are both convergent, then
$$
\begin{aligned}
&\lim_{n \to \infty} (\alpha a_n + \beta b_n) = \alpha \lim_{n \to \infty} a_n + \beta \lim_{n \to \infty} b_n \qquad \forall \alpha, \beta \in \mathbb{R} \
\
&\lim_{n \to \infty} (a_n \cdot b_n) = \lim_{n \to \infty} a_n \cdot \lim_{n \to \infty} b_n \
\
&\lim_{n \to \infty} \frac{a_n}{b_n} = \frac{\displaystyle \lim_{n \to \infty} a_n}{\displaystyle \lim_{n \to \infty} b_n}, \qquad \lim_{n \to \infty} b_n \ne 0 \
\
&\lim_{n \to \infty} |a_n| = \left|\lim_{n \to \infty} a_n\right| \ \
&\lim_{n \to \infty} \sqrt{a_n} = \sqrt{\lim_{n \to \infty} a_n} \qquad \text{if } \exists N \in \mathcal{D} \text{ such that } a_n \ge 0, \forall n \ge N
\end{aligned}
$$
Proof
Let \(A = \displaystyle \lim_{n \to \infty} a_n\) and \(B = \displaystyle \lim_{n \to \infty} b_n\).
Proof of (1):
We have to prove that for each \(\varepsilon \gt 0\), there exists some integer \(N\) such that
The case of \(\alpha = \beta = 0\) is trivial, since then \(|\alpha a_n + \beta b_n - (\alpha A + \beta B)|\) is always zero and is thus smaller than all \(\varepsilon \gt 0\). As for the existence of \(N\) - not only does such an integer \(N\) exist, but there are actually infinitely many such integers, since the inequality holds irrespective of \(N\).
If \(\alpha\) and \(\beta\) are not zero, choose some arbitrary \(\varepsilon' \gt 0\). Since \(a_n \to A\) and \(b_n \to B\), there exist integers \(N_A\) and \(N_B\) such that
$$
\begin{aligned}
|a_n - A| \lt \varepsilon' \qquad \forall n \ge N_A \
|b_n - B| \lt \varepsilon' \qquad \forall n \ge N_B
\end{aligned}
$$
Let \(N = \max \{N_A, N_B\}\). Then both inequalities hold for every \(n \ge N\). Now, we look at
By the triangle inequality, we obtain
For every \(n \ge N\), we know that \(|a_n - A| \lt \varepsilon'\) and \(|b_n - B| \lt \varepsilon'\) and so we get
Since \(|\alpha (a_n - A) + \beta (b_n - B)| \le |\alpha| |a_n - A| + |\beta| |b_n - B|\) and \(|\alpha a_n + \beta b_n - (\alpha A + \beta B)| = |\alpha (a_n - A) + \beta (b_n - B)|\), we get
So far, the argument does not depend on the choice of \(\varepsilon'\) which means that it must be true for all \(\varepsilon' \gt 0\). Thus, we have proven that for each \(\varepsilon = |\alpha| \varepsilon' + |\beta| \varepsilon'\), there exists some integer, namely \(N\), such that
which is what we set out to prove.
Proof of (2):
We have to prove that for each \(\varepsilon \gt 0\), there exists some integer \(N\) such that
Choose some arbitrary \(\varepsilon' \gt 0\). Since \(a_n \to A\) and \(b_n \to B\), there exist integers \(N_A\) and \(N_B\) such that
$$
\begin{aligned}
&|a_n - A| \lt \varepsilon' \qquad \forall n \ge N_A \
&|b_n - B| \lt \varepsilon' \qquad \forall n \ge N_B.
\end{aligned}
$$
Let \(N = \max \{N_A, N_B\}\). Then both inequalities hold for all \(n \ge N\). We transform the expression \(|a_n \cdot b_n - A \cdot B|\) a bit:
Using the triangle inequality, we obtain
which is equivalent to
For all \(n \ge N\),
which in turn means that, for all \(n \ge N\),
Recall that every convergent sequence is bounded. This means that there exists some \(B \gt 0\) and some integer \(\mathcal{N}\) such that \(|b_n| \le B\) for all \(n \ge \mathcal{N}\). Therefore,
Set \(\varepsilon = B \cdot \varepsilon' + |A| \cdot \varepsilon'\). Therefore,
It is obvious that \(\varepsilon\) can be any positive real number. Moreover, since the argument so far does not depend on any particular choice of \(\varepsilon\), we know the argument holds for all \(\varepsilon \gt 0\). We have thus proven that for each \(\varepsilon \gt 0\), there exists some integer, namely \(\mathcal{N}\), such that
which is what we set out to show.
Proof of (3):
TODO
Proof of (4):
TODO
Theorem: The Limit of \(q^n\)
The real sequence \(q^n\):
- converges to \(0\) if and only if \(|q| \lt 1\);
- converges to \(1\) if and only if \(|q| = 1\);
- diverges if and only if \(|q| \gt 1\);
- diverges towards \(+ \infty\) if and only if \(q \gt 1\).
Proof
TODO
Theorem: The Limit of \(\frac{1}{n^k}\)
Proof
The following proof was generated by AI and may contain mistakes. TODO: Review
We want to prove that the sequence \(a_n = \frac{1}{n^k}\) converges to \(0\) for any fixed natural number \(k > 0\).
By the definition of convergence, we need to show that for every \(\epsilon > 0\), there exists a natural number \(N\) such that for all \(n > N\), we have \(|a_n - 0| < \epsilon\).
Let \(\epsilon > 0\) be an arbitrary positive real number. We want to find an \(N \in \mathbb{N}\) such that for all \(n > N\),
Since \(n\) is a natural number, \(n \ge 1\). Since \(k\) is a natural number \(k > 0\), we have \(n^k \ge 1^k = 1\). Thus, \(n^k\) is always positive.
Therefore, the absolute value simplifies to:
So, we need to find \(N \in \mathbb{N}\) such that for all \(n > N\),
Since \(\epsilon > 0\) and \(n^k > 0\), we can rearrange the inequality:
Take the reciprocal of both sides (this reverses the inequality sign):
Since \(k > 0\), we can take the \(k\)-th root of both sides. The function \(x \mapsto x^{1/k}\) is strictly increasing for positive \(x\).
We need to find a natural number \(N\) such that for all \(n > N\), the condition \(n > (\frac{1}{\epsilon})^{1/k}\) holds.
By the Archimedean Property of the real numbers, for any positive real number, such as \((\frac{1}{\epsilon})^{1/k}\), there exists a natural number \(N\) greater than it.
So, we can choose \(N\) to be any natural number such that
For example, we can choose \(N = \lfloor (\frac{1}{\epsilon})^{1/k} \rfloor + 1\).
Now, let's verify this choice of \(N\). Suppose \(n\) is any natural number such that \(n > N\). Since \(N > (\frac{1}{\epsilon})^{1/k}\), we have \(n > N > (\frac{1}{\epsilon})^{1/k}\). So, \(n > (\frac{1}{\epsilon})^{1/k}\). Since \(k > 0\), raising both sides to the power of \(k\) (which is an increasing function for positive values) preserves the inequality:
Since \(n^k > 0\) and \(\epsilon > 0\), we can take the reciprocal of both sides, which reverses the inequality:
Since we already established that \(|\frac{1}{n^k} - 0| = \frac{1}{n^k}\), we have shown that for any \(n > N\),
Since we found such an \(N\) for an arbitrary \(\epsilon > 0\), by the definition of convergence, the sequence \(\frac{1}{n^k}\) converges to \(0\).
This completes the proof.
Theorem: Reciprocal Limits
Let \(\{a_n\}\) be a real sequence.
If \(\{a_n\}\) converges to \(0\) and there exists some integer \(N\) such that \(a_n \gt 0\) for all \(n \ge N\), then \(\{\frac{1}{a_n}\}\) diverges towards \(+\infty\).
If \(\{a_n\}\) converges to \(0\) and there exists some integer \(N\) such that \(a_n \lt 0\) for all \(n \ge N\), then \(\{\frac{1}{a_n}\}\) diverges towards \(-\infty\).
If \(\{a_n\}\) diverges towards either \(+\infty\) or \(-\infty\), then \(\{\frac{1}{a_n}\}\) converges to \(0\).
Proof
TODO
Theorem: Arithmetic with Infinite Limits
Let \(\{a_n\}\) and \(\{b_n\}\) be real sequences.
If \(\{a_n\}\) converges but \(\{b_n\}\) diverges towards \(\pm \infty\), then \(\{a_n + b_n\}\) also diverges towards \(\pm \infty\).
If \(\{a_n\}\) converges towards \(L \in \mathbb{R}\) but \(\{b_n\}\) diverges towards \(\pm \infty\), then \(\{a_n \cdot b_n\}\) also diverges towards \(\pm \infty\) when \(L \gt 0\) and diverges towards \(\mp \infty\) when \(L \lt 0\).
If \(\{a_n\}\) and \(\{b_n\}\) both diverge towards \(\pm \infty\), then \(\{a_n + b_n\}\) also diverges towards \(\pm \infty\) and \(\{a_n \cdot b_n\}\) diverges towards \(+ \infty\).
If \(\{a_n\}\) diverges towards \(\pm \infty\) but \(\{b_n\}\) diverges towards \(\mp \infty\), then \(\{a_n \cdot b_n\}\) diverges towards \(- \infty\). However, this information is insufficient to determine \(\lim_{n\to \infty} (a_n + b_n)\).
Proof
TODO
Theorem: The Limit of \(\left(1 + \frac{1}{n}\right)^n\) and its Variations
The real sequence \(a_n = \left(1 + \frac{1}{n}\right)^n\) converges towards Euler's number \(\mathrm{e}\).
Similarly, the limits of the following real sequences can also be expressed using the real exponential function:
Proof
TODO
Theorem: Limits of Recursive Sequences
Let \((a_n)\) be a real sequence defined as \(a_{n+1} = f(a_n)\) for some real function \(f\).
If \(f\) is continuous and \((a_n)\) is convergent, then
Proof
TODO
Subsequential Limits#
Definition: Subsequential Limit
Let \((a_n)_{n \in \mathcal{D}}\) be a real sequence and let \(L \in \mathbb{R}\).
We say that \(L\) is a subsequential limit of \((a_n)_{n \in \mathcal{D}}\) if \((a_n)_{n \in \mathcal{D}}\) has some convergent subsequence whose limit is \(L\).
Example
Consider the sequence \(a_n = (-1)^n\) and consider its subsequence \(a_{2k} = 1^{2k}\). The sequence \(a_n = (-1)^n\) is divergent, but \(a_{2k} = 1^{2k}\) converges to \(1\), so \(1\) is a subsequential limit of \(a_n\).
Bolzano-Weierstraß Theorem
Every bounded infinite real sequence has at least one convergent subsequence.
Proof
TODO
Theorem: Limit \(\iff\) Subsequential Limits
The limit of an infinite real sequence \((a_n)_{n \in \mathcal{D}}\) is \(L \in \mathbb{R}\) if and only if all of the subsequences of \((a_n)_{n \in \mathcal{D}}\) converge to \(L\).
Proof
We need to prove two things:
- (I) The limit of \((a_n)_{n \in \mathcal{D}}\) is \(L \in \mathbb{R}\), then all of the subsequences of \((a_n)_{n \in \mathcal{D}}\) converge to \(L\).
- (II) If all of the subsequences of \((a_n)_{n \in \mathcal{D}}\) converge to \(L \in \mathbb{R}\), then the limit of \((a_n)_{n \in \mathcal{D}}\) is \(L\).
Proof of (I):
Let \((b_{m})_{m \in f(\mathcal{D})}\) be a subsequence of \((a_n)_{n \in \mathcal{D}}\). By definition, for each \(m\) there exists some \(n \in \mathcal{D}\) such that \(m = f(n)\) and \(b_m = a_m\). Since \((a_n)_{n \in \mathcal{D}}\) converges to \(L\), we know that for each \(\varepsilon \gt 0\) there exists some \(N \in \mathcal{D}\) with
i.e.
Proof of (II):
TODO
Limit Inferior and Limit Superior#
Theorem: Limit Inferior
Let \((a_n)_{n \in \mathcal{D}}\) be a real sequence.
The limit inferior of \((a_n)_{n \in \mathcal{D}}\), if it is finite, is equal to the minimum of all the limits of \((a_n)_{n \in \mathcal{D}}\)'s convergent subsequences:
Proof
TODO
Example: \(a_n = (-1)^n\)
We examine the following real sequence \((a_n)_{n \in \mathcal{D}}\):
It is obvious that the smallest limit which a subsequence of \((a_n)_{n \in \mathcal{D}}\) could have is \(-1\). Therefore:
Example
We examine the following real sequence \((a_n)_{n \in \mathcal{D}}\):
The values \(23\) and \(-42\) cannot be limits of subsequences of \((a_n)_{n \in \mathcal{D}}\), since they occur only once at a specific index. Therefore, the smallest limit which a subsequence of \((a_n)_{n \in \mathcal{D}}\) could have is still \(-1\):
Theorem: Limit Superior
Let \((a_n)_{n \in \mathcal{D}}\) be a real sequence.
The limit superior of \((a_n)_{n \in \mathcal{D}}\), if it is finite, is equal to the maximum of all the limits of \((a_n)_{n \in \mathcal{D}}\)'s convergent subsequences:
Proof
TODO
Example: \(a_n = (-1)^n\)
We examine the following real sequence \((a_n)_{n \in \mathcal{D}}\):
It is obvious that the greatest limit which a subsequence of \((a_n)_{n \in \mathcal{D}}\) could have is \(1\). Therefore:
Example
We examine the following real sequence \((a_n)_{n \in \mathcal{D}}\):
The values \(23\) and \(-42\) cannot be limits of subsequences of \((a_n)_{n \in \mathcal{D}}\), since they occur only once at a specific index. Therefore, the greatest limit which a subsequence of \((a_n)_{n \in \mathcal{D}}\) could have is still \(+1\):
Monotony#
Theorem: Difference Criteria for Sequence Monotony
A real sequence \((a_n)\) is
- increasing if \(a_{n+1} - a_n \ge 0\) for all \(n \in \mathbb{N}\);
- strictly increasing if \(a_{n+1} - a_n \gt 0\) for all \(n \in \mathbb{N}\);
- decreasing if \(a_{n+1} - a_n \le 0\) for all \(n \in \mathbb{N}\);
- strictly decreasing if \(a_{n+1} - a_n \lt 0\) for all \(n \in \mathbb{N}\)
Proof
TODO
Example: Monotony of \(\frac{1}{n}\)
The sequence \((a_n)_{n \in \mathbb{N}}\) defined as \(a_n = \frac{1}{n}\) is strictly decreasing, since
Example: Monotony of \(\frac{n!}{2^n}\)
The sequence \((a_n)_{n \in \mathbb{N}}\) defined as \(a_n = \frac{n!}{2^n}\) is increasing, since
Theorem: Quotient Criteria for Sequence Monotony
A real sequence \((a_n)\) with \(a_n \gt 0\) for all \(n \in \mathbb{N}\) is:
- increasing if \(\frac{a_{n+1}}{a_n} \ge 1\) for all \(n \in \mathbb{N}\);
- strictly increasing if \(\frac{a_{n+1}}{a_n} \gt 1\) for all \(n \in \mathbb{N}\);
- decreasing if \(\frac{a_{n+1}}{a_n} \le 1\) for all \(n \in \mathbb{N}\);
- strictly decreasing if \(\frac{a_{n+1}}{a_n} \lt 1\) for all \(n \in \mathbb{N}\)
Proof
TODO
Monotone Convergence Theorem
If a real sequence is increasing and bounded above, then it is convergent and its limit is the supremum of its image.
If a real sequence is decreasing and bounded below, then it is convergent and its limit is the infimum of its image.
Proof
TODO
Example
We want to see if the following, recursively defined sequence \((a_n)_{n \in \mathbb{N}}\) is convergent:
We prove two things:
- \((a_n)_{n \in \mathbb{N}}\) is bounded by \(\sqrt{2} \le a_n \le 2\);
- \((a_n)_{n \in \mathbb{N}}\) is decreasing.
Proof of (1):
We do this using induction:
- Base case: The statement holds for \(n = 1\), since \(a_1 = 2\) and \(\sqrt{2} \le 2 \le 2\).
- Induction step: We assume that there exists some arbitrary, fixed \(n \in \mathbb{N}\) such that \(\sqrt{2} \le a_n \le 2\). We have
Since \(\sqrt{2} \le a_n\), we know that \(\frac{1}{a_n} \le \frac{1}{\sqrt{2}} = \frac{\sqrt{2}}{2}\). We therefore have the following:
Furthermore,
Since \(\sqrt{2} \le a_n\), we know that \(\frac{(a_n - \sqrt{2})^2}{2a_n} \ge 0\), i.e. \(a_{n+1} - \sqrt{2} \ge 0\) and so \(a_{n+1} \ge \sqrt{2}\).
Thus we have shown at \((a_n)\) is bounded
Proof of (2):
We have
since \(a_n \ge \sqrt{2}\).
Thus, we have shown that \((a_n)\) is decreasing.
Since we showed that \((a_n)\) is both bounded and decreasing, we know it is convergent.