Some problems to think about

I had hoped to write some more problems and will return to this as soon as I can, but for now here are some (harder) problems to help you think about the course as well as some more recent material. As always, reading Spivak and doing exercises is also useful.

Practice Problems

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Local versus Global

This is just to reinforce today’s lecture. The idea is that many concepts:

  1. The limit of \(f(x)\) of a limit at \(x = a\),
  2. The continuity of \(f(x)\) at \(x= a\),
  3. The differentiability of \(f(x)\) at \(x=a\),
  4. The point \(a\) being a local maximum of \(f(x)\)

Only depend on the behavior of \(f(x)\) in a region \((a-\delta,a+\delta)\) for any \(\delta\).

But is there anything that is not a “local” property of a function?
Here local means some fact that can really be detected in one of these very small neighbourhoods of \(a\). One property is being a maximum (not must a local maximum). Remember that we proved the following:

Theorem: If \(f(x)\) is continuous on a closed interval \([a,b]\), then \(f(x)\) obtains a maximal value. That is, there exists a \(c \in [a,b]\) so that \(f(c) \ge f(x)\) for all \(x \in [a,b]\).

To prove this theorem, we really had to exploit not only continuity but also some extra properties of the real numbers, namely that any non-empty bounded set \(A\) has a least upper bound \(\mathrm{sup}(A)\). One reason why it is hard to prove is that we had to use local properties of continuity to establish something on the entire interval (which by contrast we call a global property). Leaving that aside, the property of being a maximum value is not a local property. That is, suppose you have a differentiable function \(f(x)\) on an interval \([a,b]\), and you know the behavior of the function \(f(x)\) around a point \(c\). On Friday, we will prove the following:

Theorem: If \(f(x)\) is differentiable at \(c\) and \(c\) is a local maximum of \(f(x)\), then \(f'(c)=0\).

However, something we can not do is tell whether \(c\) is actually a maximum of \(f(x)\) on the entire interval just by looking at the behavior around \(x =c\). This is hopefully intuitive, but let’s give an example. Consider the following three functions:

\[\begin{aligned}
a(x) & = 3 x^4 – 20 x^3 + 36 x^2, \\
b(x) & = 12 x^4 – 80 x^3 + 162 x^2 – 108 x + 33, \\
c(x) & = \begin{cases} a(x), & x < 1, \\ b(x), & x \ge 1. \end{cases} \end{aligned}\] Here is the graph of \(a(x)\) in blue and \(c(x)\) in orange: it's a graph!

I claim that the three functions \(a(x),b(x),c(x)\) are all differentiable. This should be clear for \(a(x)\) and \(b(x)\). For \(c(x)\) it follows from the local principle above except for the point \(x=1\). Note that

\[c(1) = b(1) = 12-80+162-108+33= 19 = 3 – 20 + 36= a(1).\]

To check that \(c(x)\) is differentiable we check that the right and limits both exist and they are both equal. We have

\[\lim_{h \rightarrow 0^{+}} \frac{c(1+h) – c(1)}{h} =
\lim_{h \rightarrow 0^{+}} \frac{b(1+h) – b(1)}{h} = b'(1) = 24.\]

On the other hand, since \(b(1)=a(1)\), we have

\[\lim_{h \rightarrow 0^{-}} \frac{c(1+h) – c(1)}{h} =
\lim_{h \rightarrow 0^{-}} \frac{a(1+h) – a(1)}{h} = a'(1) = 24.\]

The point is that the right and left hand side limits only involve \(a(x)\) or \(b(x)\), and because those functions are differentiable we can compute the limits in terms of those functions and their derivatives. Now let us check the critical points of \(a(x)\), \(b(x)\), and \(c(x)\). We have

\[\begin{aligned} a'(x) & = 12 (-3 + x) (-2 + x) x, \\
b'(x) & = 12 (-3 + x) (-3 + 2 x) (-1 + 2 x) \end{aligned}.\]

Since \(a'(1)=b'(1) = 24\), we get

\[c'(x) = \begin{cases} 12 (-3 + x) (-2 + x) x, & x < 1 \\ 12 (-3 + x) (-3 + 2 x) (-1 + 2 x), & x \ge 1. \end{cases}\] What are the critical points? We get:

  1. The critical points of \(a(x)\) are \(x = 0,2,3\).
  2. The critical points of \(c(x)\) are \(x=0,3/2,3\).

We now (finally) get the the point. The functions \(a(x)\) and \(c(x)\) are the same function in a neighbourhood of \(x=0\). So we deduce:

  1. The functions \(a(x)\) and \(c(x)\) have the same value at \(x = 0\), and the same derivative at \(x=0\).
  2. The point \(x = 0\) is a local minimum for \(a(x)\) and \(c(x)\).

However, the function \(a(x)\) has its mimimum for all \(x\) at \(x=0\), whereas the function \(c(x)\) does not, it’s minimum occurs at \(x=3\). There is no way to tell this just by looking at these functions around \(x=0\).

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Another midterm.

Here are the solutions by ChatGPT to this week’s midterm. What grade would you give it?
Give your grade in the comments! (Hint: there are definitely some things which are wrong here.)

Problem 1
We need to show that
\[
\lim_{x \rightarrow 1} x^2 = 1
\]
using the \(\varepsilon\)-\(\delta\) definition of a limit.

Solution
To prove that \(\lim_{x \to 1} x^2 = 1\) using the \(\varepsilon\)-\(\delta\) definition, we must show that for any \(\varepsilon > 0\), there exists a \(\delta > 0\) such that if \(0 < |x - 1| < \delta\), then \(|x^2 - 1| < \varepsilon\).

  1. Starting with \(|x^2 – 1|\): We have:
    \[
    |x^2 – 1| = |x^2 – 1^2| = |x – 1||x + 1|.
    \]
  2. Choosing \(\delta\):
    We want to make \(|x – 1||x + 1| < \varepsilon\). Notice that if \(x\) is close to 1, then \(x + 1\) will be close to 2. Let’s assume \(|x - 1| < 1\), which implies \(0 < x < 2\), so \(1 < x + 1 < 3\).
  3. Bounding \(|x + 1|\):
    In this case, \(|x + 1| < 3\). Then: \[ |x - 1||x + 1| < 3|x - 1|. \]
  4. Setting up \(\delta\):
    To ensure \(|x – 1||x + 1| < \varepsilon\), we can choose \(\delta\) such that \(3|x - 1| < \varepsilon\), or equivalently, \( |x - 1| < \frac{\varepsilon}{3} \).
  5. Conclusion:
    Let \(\delta = \frac{\varepsilon}{3}\). Then if \(0 < |x - 1| < \delta\), we have: \[ |x^2 - 1| = |x - 1||x + 1| < 3|x - 1| < 3 \cdot \frac{\varepsilon}{3} = \varepsilon. \] Thus, \(\lim_{x \to 1} x^2 = 1\) as required.

Problem 2
We need to construct a set \(A\) with the following properties:

  1. \(\sup A\) exists and is not in \(A\).
  2. \(\inf A\) exists and lies in \(A\).

Solution
Consider the set \(A = \{x \in \mathbb{R} : 0 \leq x < 1\}\).

  1. Checking \(\sup A\):
    The supremum of \(A\) is 1, as 1 is the least upper bound of all elements in \(A\). However, 1 is not in \(A\) because \(A\) only contains elements less than 1. Thus, \(\sup A = 1\) exists and is not in \(A\).
  2. Checking \(\inf A\):
    The infimum of \(A\) is 0, as 0 is the greatest lower bound of all elements in \(A\). Moreover, 0 is included in \(A\), so \(\inf A = 0\) exists and lies in \(A\).

Thus, the set \(A = \{x \in \mathbb{R} : 0 \leq x < 1\}\) satisfies the required conditions.

Problem 3
We analyze the conditions to determine whether each implies continuity at \(x = 0\).

  1. \(\exists \varepsilon > 0, \forall \delta > 0, \ \text{if \(0 < |x| < \delta\), then} \ |f(x) - f(0)| < \varepsilon.\) This condition does not imply continuity at \(x = 0\). Here’s why:

    • This condition states that there is some fixed \(\varepsilon > 0\) such that no matter how small we make \(\delta\), \(f(x)\) will always stay within \(\varepsilon\) of \(f(0)\) when \(x\) is close to 0.
    • Continuity requires that for every \(\varepsilon > 0\), there is a \(\delta\) such that if \(0 < |x| < \delta\), then \(|f(x) - f(0)| < \varepsilon\).

    Thus, this condition does not ensure continuity.

  2. \(\forall \varepsilon > 0, \forall \delta > 0, \ \text{if \(0 < |x| < \delta\), then} \ |f(x) - f(0)| < \varepsilon.\) This condition does imply continuity at \(x = 0\):

    • This condition is actually stronger than the usual \(\varepsilon\)-\(\delta\) definition of continuity, as it requires that \(|f(x) – f(0)| < \varepsilon\) for all \(\delta > 0\) rather than just for some \(\delta\) depending on \(\varepsilon\).
    • Therefore, this condition guarantees continuity at \(x = 0\).
  3. \(\forall \varepsilon > 0, \exists \delta > 0, \ \text{if \(0 < |x| < \delta\), then} \ |f(x) - f(0)| < \varepsilon^2.\) This condition does not imply continuity at \(x = 0\):

    • This condition is weaker than the standard \(\varepsilon\)-\(\delta\) definition because it bounds \(|f(x) – f(0)|\) by \(\varepsilon^2\) instead of \(\varepsilon\).
    • The fact that the bound involves \(\varepsilon^2\) instead of \(\varepsilon\) means it could still be large enough that \(|f(x) – f(0)|\) doesn’t approach 0 as \(\varepsilon \to 0\).

    Therefore, this does not imply continuity at \(x = 0\).

Problem 4
Let \(f(x)\) be a continuous function on \(\mathbb{R}\) satisfying \(f(x+1) = f(x)\) for all \(x \in \mathbb{R}\). We need to prove that \(f(x)\) is bounded on \(\mathbb{R}\).

Solution

  1. Periodicity: The condition \(f(x+1) = f(x)\) implies that \(f(x)\) is periodic with period 1. This means that the behavior of \(f(x)\) on the entire real line is determined by its behavior on any interval of length 1, for instance, the interval \([0, 1]\).
  2. Continuity on \([0, 1]\): Since \(f\) is continuous on \(\mathbb{R}\), it is also continuous on the closed interval \([0, 1]\).
  3. Boundedness on \([0, 1]\): By the Extreme Value Theorem, a continuous function on a closed interval \([0, 1]\) attains its maximum and minimum values on that interval. Thus, there exist constants \(m\) and \(M\) such that \(m \leq f(x) \leq M\) for all \(x \in [0, 1]\).
  4. Extending the Bound: For any \(x \in \mathbb{R}\), there exists an integer \(k\) such that \(x – k \in [0, 1]\). Using the periodicity, we have:
    \[
    f(x) = f(x – k + k) = f(x – k).
    \]
    Since \(x – k \in [0, 1]\), it follows that \(m \leq f(x) \leq M\) for all \(x \in \mathbb{R}\).

Therefore, \(f(x)\) is bounded on \(\mathbb{R}\).

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ChatGPT

I gave ChatGPT the midterm. It scored around 60/100. (Update: I just graded the midterm and was more generous, so 65/100.) It failed miserably on the graphing question, which is maybe expected since it doesn’t have the ability scan in a graph. After some prodding, it produced the following:

which is a somewhat heroic effort in the circumstances.

Let me give ChatGPT’s answers as generated entirely by ChatGPT, making some comments as we go along.

Question 1:

Suppose that \(\alpha\) and \(\beta\) are numbers such that \(\alpha \beta\) and \(\alpha + \beta\) are both integers. Prove that \(\alpha^n + \beta^n\) is an integer for each \(n \in \mathbb{N}\).

Solution:

We are given that \(\alpha \beta\) and \(\alpha + \beta\) are integers. We want to show that \(\alpha^n + \beta^n\) is an integer for each \(n \in \mathbb{N}\).

Let \(s_n = \alpha^n + \beta^n\). We will use a recurrence relation to prove that \(s_n\) is an integer for all \(n \geq 0\).

From the quadratic equation with roots \(\alpha\) and \(\beta\):
\[
x^2 – (\alpha + \beta)x + \alpha \beta = 0,
\]
we have the recurrence relation:
\[
s_{n+2} = (\alpha + \beta) s_{n+1} – \alpha \beta s_n.
\]

Initial conditions:

\[
s_0 = \alpha^0 + \beta^0 = 2, \quad s_1 = \alpha + \beta.
\]
Both are integers by assumption. By induction, assume \(s_n\) and \(s_{n+1}\) are integers for some \(n \geq 0\). Then, by the recurrence relation:
\[
s_{n+2} = (\alpha + \beta) s_{n+1} – \alpha \beta s_n,
\]
which is an integer because \(\alpha + \beta\), \(\alpha \beta\), \(s_n\), and \(s_{n+1}\) are all integers.

Thus, by the principle of induction, \(s_n = \alpha^n + \beta^n\) is an integer for all \(n \geq 0\).

Frank’s Comments: I would prefer not being so cavalier with writing \(\alpha^0 = 1\) when \(\alpha\) could be zero, but this answer is more or less correct. I would also have preferred that instead of talking about recurrence relations one could just prove that formula directly. That said, with generous grading \(25/25\).


Question 2:

Determine if the following claims are true or false. Justify your answer with a proof.

(a) There exists a function with domain \(\mathbb{R}\) and range the integers.

Solution:

This statement is true. A simple example is the floor function \(\lfloor x \rfloor\), which takes a real number \(x\) and returns the largest integer less than or equal to \(x\). The floor function has domain \(\mathbb{R}\) and range \(\mathbb{Z}\).

(b) The zero function is defined as the function which returns zero for all real numbers — it has domain \(\mathbb{R}\) and range \(0\). Suppose that \(f\) and \(g\) are two functions with domain \(\mathbb{R}\) whose product is equal to the zero function. Then one of \(f\) or \(g\) is the zero function.

Solution:

This statement is false. Consider the functions \(f(x) = x\) and \(g(x) = 0\). Their product is zero for all \(x\), but neither function is identically zero over \(\mathbb{R}\).

Frank’s Comments The function \(g(x)\) is the zero function here! One can easily modify this with \(g(x)=0\) for \(x \ne 0\) and \(g(0) = 1\). With generous grading \(5/10\).

(c) If the domain of \(f\) is all of \(\mathbb{R}\), then the domain of the function \(g(x) = \frac{1}{1 + f(x)^2}\) is also all of \(\mathbb{R}\).

Solution:

This statement is true. Since \(f(x)^2 \geq 0\) for all \(x \in \mathbb{R}\), we have \(1 + f(x)^2 \geq 1\), which means the denominator of \(g(x)\) is never zero. Therefore, the function \(g(x)\) is well-defined for all \(x \in \mathbb{R}\).


Question 3:

Let \(\Gamma(x)\) be a function with domain \((-1, 0) \cup (0, 5]\), such that \(\Gamma(1) = 1\) and \(\Gamma(x+1) = x \Gamma(x)\) for all \(x\) in the domain of \(\Gamma(x)\). Draw the graph of \(\Gamma(x)\), assuming that for \(x \in [1, 5]\), the graph is provided.

Solution:

We can compute the values of \(\Gamma(x)\) for \(x \in [1, 5]\) using the recurrence relation. We know that \(\Gamma(1) = 1\). From the relation \(\Gamma(x+1) = x \Gamma(x)\), we get:
\[
\Gamma(2) = 1 \cdot \Gamma(1) = 1,
\]
\[
\Gamma(3) = 2 \cdot \Gamma(2) = 2,
\]
\[
\Gamma(4) = 3 \cdot \Gamma(3) = 6,
\]
\[
\Gamma(5) = 4 \cdot \Gamma(4) = 24.
\]
Thus, we have the points \(\Gamma(1) = 1\), \(\Gamma(2) = 1\), \(\Gamma(3) = 2\), \(\Gamma(4) = 6\), and \(\Gamma(5) = 24\).

Frank’s Comments: Since ChatGPT couldn’t read the graph, there is not much content here; \(0/20\).


Question 4:

Let \(a_n\) and \(b_n\) be the sequences defined by \(a_0 = b_0 = 1\) and the recurrence relations:
\[
a_{n+1} = 3^{a_n}, \quad b_{n+1} = 2^{b_n}.
\]
Prove the following:

(a) Prove that \(a_n > b_{n+1}\) for \(n \geq 2\).

Solution:

We will use induction to prove that \(a_n > b_{n+1}\) for \(n \geq 2\).

Base case:

For \(n = 2\), we have:
\[
a_2 = 3^{a_1} = 3^1 = 3, \quad b_3 = 2^{b_2} = 2^2 = 4.
\]
Thus, \(a_2 = 3 < b_3 = 4\), which satisfies the inequality.

Inductive step:

Assume \(a_n > b_{n+1}\) for some \(n \geq 2\). We want to show that \(a_{n+1} > b_{n+2}\). We have:
\[
a_{n+1} = 3^{a_n}, \quad b_{n+2} = 2^{b_{n+1}}.
\]
By the inductive hypothesis, \(a_n > b_{n+1}\), so:
\[
a_{n+1} = 3^{a_n} > 3^{b_{n+1}} > 2^{b_{n+1}} = b_{n+2}.
\]
Thus, the inequality holds for \(n+1\), completing the induction.

(b) Prove that \(b_{n+2} > a_n\) for all \(n \geq 0\).

Solution:

We proceed similarly by induction.

Base case:

For \(n = 0\), we have:
\[
b_2 = 2^{b_1} = 2^1 = 2 > a_0 = 1.
\]
Thus, \(b_2 > a_0\) holds.

Inductive step:

Assume \(b_{n+2} > a_n\) for some \(n \geq 0\). We want to show that \(b_{n+3} > a_{n+1}\). We have:
\[
b_{n+3} = 2^{b_{n+2}}, \quad a_{n+1} = 3^{a_n}.
\]
By the inductive hypothesis, \(b_{n+2} > a_n\), so:
\[
b_{n+3} = 2^{b_{n+2}} > 3^{a_n} = a_{n+1}.
\]
Thus, the inequality holds for \(n+1\), completing the induction.

Frank’s Comments: Of course if \(b > a\) then it is not necessarily the case that \(2^b > 3^a\), so the second part is wrong, \(15/25\), for a total of

\[25+25+15=65\]

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The game of infinite intelligence

I’ve talked about how analyzing games naturally leads to inductive arguments, and gave a few examples. Here is a tricky game problem which is a little mind bending. It’s much tricker than anything else I have suggested, so consider it a challenge problem (for fun).

Problem: Alice and Bob are infinitely intelligent, and honest, and they play the following game. They both write down a natural number on a piece of paper (without showing the other) and then give them to Chuck. Let’s call them \(a\) and \(b\). Chuck then reveals to Alice and Bob two numbers; one of the numbers is the sum \(a+b\), and the other is an integer \(c\), but Chuck does not tell either Alice or Bob which is which.

Chuck asks Alice: “do you know Bob’s number”? If Alice says yes, the game ends. Otherwise:

Chuck asks Bob: “do you know Alice’s number?” If Bob says yes, the game ends. Otherwise:

Chuck asks Alice: “do you know Bob’s number”? If Alice says yes, the game ends. Otherwise:

… Chuck keeps going back and forth alternatively asking Bob and Alice the same question. The problem it to show that, after finitely many turns, one of Alice or Bob says yes.

An Example: Suppose that Alice write down \(a = 7\) and Bob writes down \(b = 17\), and that Chuck writes down the numbers \(32\) and \(24\).

  1. Alice looks at these numbers and she can’t distinguish between whether Bob has the number \(24 – 7 = 17\) or the number \(32 – 7 = 25\), so she says no.
  2. Now it is Bob’s turn. Bob knows that Alice either has the number \(24 – 17 = 7\) or the number \(32 – 17 = 15\). He knows that if Alice had the number \(7\), then she would have said no on the first term. He also knows that if Alice had the number \(15\), she would think that Bob either had then number \(9\) or the number \(17\), so she also would have said no. So Bob can’t distinguish from Alice’s last answer whether she had either a \(7\) or a \(15\), so he says no.
  3. Now it is Alice’s turn. Alice knows that Bob has the number \(17\) or the number \(25\). She knows that if Bob has the number \(17\) then he would say no (as he did). She also know that if Bob has the number \(25\), then Bob would have said yes, since then Bob would know that the sum is \(32\) since \(24\) is not the sum of \(25\) and a natural number. (The fact that natural numbers are positive is a key fact, the game would not end if Alice and Bob were allowed to choose an integer.) So Alice says yes, and the game ends!

It should be very much clear that something inductive is going on in this problem. So the problem is: what is going on?

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The Sticks Game

Although I did this in class, I thought it might be useful to write out a proof here. There are many variations, but it should look something quite similar to this.

Claim: For \(n = 0,1,2,\ldots\) a non-negative integer, the winner of the sticks game is as follows:

  1. If there are \(3n+1\) sticks, then the player to move loses.
  2. If there are \(3n+2\) sticks, then the player to move wins.
  3. If there are \(3n+3\) sticks, then the player to move wins.

Proof: We give a proof by induction starting from \(n = 0\). Let \(P(n)\) mean that the three listed statements above are true for \(n\).

Base Case: Suppose that \(n=0\).

  • If there is one stick, then the player to move has to pick up the stick and so loses.
  • If there are two sticks, then the player to move can pick up one stick, and then the next player has to pick up the final stick and so loses, and hence the first player wins.
  • If there are two sticks, then the player to move can pick up two sticks, and then the next player has to pick up the final stick and so loses, and hence the first player wins.

These three statements prove \(P(0)\) is true, which is the base case.

Inductive Step: We shall assume \(P(k)\) and show \(P(k+1)\).

  1. If there are \(3(k+1) + 1 = 3k+4\) sticks, and the player to move picks up one stick, then there are \(3k+3\) sticks remaining. But since we are assuming \(P(k)\), this means that the second player (who is now the player to move) wins, which means that the first player loses. On the other hand, if the first player picks up two sticks, there are \(3k+2\) sticks remaining. Again by our assumption \(P(k)\), this means the second player wins and the first player loses. So whatever the first player does, he will lose. So if there are \(3(k+1)+1\) sticks, the player to move loses.
  2. If there are \(3(k+1) + 2 = 3k+5\) sticks, then the player to move can pick up one stick, and there are \(3k+4\) sticks remaining. Now by part \(1\), the second player (who is now the player to move) must lose. Thus the first player can always win.
  3. If there are \(3(k+1) + 3 = 3k+6\) sticks, then the player to move can pick up two sticks, and there are \(3k+4\) sticks remaining. Now by part \(1\), the second player (who is now the player to move) must lose. Thus the first player can always win.

Thus assuming \(P(k)\) we have shown \(P(k+1)\) is true, and so by induction we are done!

Remarks:

  1. Notice how wordy the proof is! That’s a feature not a a bug; communicating in sentences is often a really clear way to convey ideas. It is often the case that mathematical notation is more compact and it is useful for that purpose, just make sure it doesn’t obscure what you are actually doing.
  2. Note that in the case \(n = 3k+5\) and \(n=3k+6\) we used the case \(n = 3k+4\) which was not part of \(P(k)\), but part of our argument showed that the case \(n = 3k+4\) did follow from \(P(k)\). That is fine — it just means that it took a few steps for us to prove \(P(k+1)\) only assuming \(P(k)\). Another interesting feature of the argument is that when deducing \(P(k+1)\) we didn’t even use the fact about the game with \(3k+1\) players.
  3. The sticks game is a special case of a more general game called nim. Although the more general game is a little more complicated, ultimately the analysis is quite similar and the proof (given at the link) is by induction.

Added: A real life application of the sticks game:

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Constructing Irrational Numbers using Cantor’s Argument

Cantor’s argument also allows us to “explicitly” construct irrational numbers. Let’s take a list which includes all the rational numbers between \(0\) and \(1\). First we add \(1\), and then we take \(a/b\) first over the possible denominators \(b > 1\) and then taking all possible numerators \(a\) from \(1\) to \(b-1\). Let’s not even worry about duplicates! So we could take \(r_1, r_2, r_3, \ldots \) to be:

\[1/2,1/3,2/3,1/4,2/4,3/4,1/5,2/5,3/5,4/5,1/6,2/6,3/6,4/6,5/6,1/7, \ldots \]

Taking the opposite convention to class, let’s consider the decimal expansion of these numbers which, if it ends in \(999999\ldots\) we round up. Now we take a real number \(r\) defined as follows:

  1. If the \(n\)th digit of \(r_n\) is equal to to \(1\), we make \(r\) have the digit \(2\),
  2. If the \(n\)th digit of \(r_n\) is *not* equal to to \(1\), we make \(r\) have the digit \(1\),

So here is the list:

\[\begin{aligned}
r_1 & = 0.5000000000 \ldots \\
r_2 & = 0.3333333333 \ldots \\
r_3 & = 0.6666666666 \ldots \\
r_4 & = 0.2500000000 \ldots \\
r_5 & = 0.5000000000 \ldots \\
r_6 & = 0.7500000000 \ldots \\
r_7 & = 0.2000000000 \ldots \\
r_8 & = 0.4000000000 \ldots \\
r_9 & = 0.6000000000 \ldots \\
r_{10} & = 0.8000000000 \ldots \\
\end{aligned}
\]

and so say using the mathematica code

\[ \begin{split}
\texttt{Q := Flatten[Table[a/b, {b, 2, 20}, {a, 1, b – 1}]]} \\
\texttt{Table[If[Mod[Floor[Q[[n]] 10^n], 10] == 1, 1, 2], {n, 1, Length[Q]}]}
\end{split}
\]

We find that

\[r = 0.222222222222222211212222222212222222222222222212222221222222222222222\ldots \]

is an irrational number, because if it were rational in \(0,1\) then it would be equal to \(r_n\) for some \(n\),
but the \(n\)th digit of \(r\) is not equal to the \(n\)th digit of \(r_n\) by construction.

Another fact about decimal expansions of rational numbers is that they are (eventually) repeating. This gives (yet another) way to construct them using decimal expansions.

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Rational Numbers

In class we gave the “classic” proof that \(\sqrt{2}\) is irrational, but we also gave a different proof using analysis. For each pair of positive integers \([a,b]\) with \(a/b \in [0,1]\) with \(b > 1\), we considered the interval

\[ I(a,b):= \left[ \frac{a}{b} – \frac{1}{b^{42}},\frac{a}{b} + \frac{1}{b^{42}} \right]\]

around the point \(a/b\). One possible guess is that the union ofthese intervals entirely covers \((0,1)\) (maybe with some overlap). There certainly will be some overlap since \(I(a,b)\) and \(I(ma,mb)\) are both centered on \(a/b = ma/mb\). But if these intervals do cover the entire interval \([0,1]\) then the total length of all these lines should be at least \(1\). But we can compute the length:

  • The intervals \(I(1,2)\) and \(I(2,2)\) both have length \(2/2^{42}\).
  • The intervals \(I(1,3)\), \(I(2,3)\), and \(I(3,3)\) both have length \(2/3^{42}\).
  • The intervals \(I(1,4)\), \(I(2,4)\), \(I(3,4\), and \(I(4,4)\) both have length \(2/4^{42}\).

and so on, so the total length is at least

\[ \begin{aligned} S &:=
\frac{2}{2^{42}} + \frac{2}{2^{42}} + \frac{2}{3^{42}}+ \frac{2}{3^{42}}+ \frac{2}{3^{42}} + \frac{2}{4^{42}} + \ldots \\
& = 2 \left(\underbrace{\frac{1}{2^{42}} + \frac{1}{2^{42}}}_{2} + \underbrace{\frac{1}{3^{42}} + \frac{1}{3^{42}} + \frac{1}{3^{42}}}_{3} + \underbrace{\frac{1}{4^{42}} + \ldots + \frac{1}{4^{42}}}_{4} + \ldots \right) \\
& = 2 \left(\frac{2}{2^{42}} + \frac{3}{3^{42}} + \frac{4}{4^{42}}+ \frac{5}{5^{42}}+ \ldots \right) \\
& = 2 \left(\frac{1}{2^{41}} + \frac{1}{3^{41}} + \frac{1}{4^{41}}+ \frac{1}{5^{41}}+ \ldots \right) \\
& = 0.00000000094947\ldots\end{aligned} \]
(We did not and will not justify the last line) which is less than one. So irrational numbers must exist, and lots of them! This proof even shows that if you take a “random” real number \(\alpha\) then unless are really really unlucky, you must have

\[ \left| \alpha – \frac{p}{q} \right| \ge \frac{1}{q^{42}} \]

for all integers \(p\) and \(q\) with \(q > 1\). But unlike the first proof, this proof doesn’t show that any particular number is irrational. It’s a great feat of humanity that \(\pi\) is irrational, but does it also have this property?

Things to think about:

  1. Check that
    \[ \left|\ \pi \ – \ \frac{22}{7} \right| = \frac{1}{7^{3.429288\ldots}} \]
  2. Would the argument we gave in class work if one replaced \(42\) by another number? Which numbers?
  3. What is \(\sqrt{2}\) and \(\pi\) anyway?

We know (because we have been told) that \(\pi\) is irrational. In fact this was first proven by Lambert in 1760. It is a much harder (and more recent) theorem of Kurt Mahler from the 1950s that
\[ \left| \pi- \frac{p}{q} \right| \ge \frac{1}{q^{42}} \]
for all \(q > 1\). The optimal value of the exponent is not known!

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Hello World!

This will be the class blog for 16100 in Autumn 2024, and will be an occasional supplement to the regular course lectures. (I started blogging about courses during the pandemic, but students find the blog useful so have continued to use it.)

Syllabus: can be found here.

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