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A function $f:\omega\to\omega$ is called

$\bullet$ 2-to-1 if $|f^{-1}(y)|\le 2$ for any $y\in\omega$;

$\bullet$ almost injective if the set $\{y\in \omega:|f^{-1}(y)|>1\}$ is finite.

Let us introduce two critical cardinals, related to $2$-to-$1$ functions:

$\mathfrak{j}_{2:1}$ is the largest cardinal $\kappa\le\mathfrak c$ such that for any family $F\subset \omega^\omega$ of $2$-to-$1$ functions with $|F|<\kappa$ there exists an infinite subset $J\subset\omega$ such that for any $f\in F$, the restriction $f{\restriction}J$ is almost injective;

$\mathfrak{j}_{2:2}$ is the largest cardinal $\kappa\le\mathfrak c$ such that for any family $F\subset \omega^\omega$ of $2$-to-$1$ functions with $|F|<\kappa$ there are two infinite sets $I,J\subset\omega$ such that for any $f\in F$ the intersection $f(I)\cap f(J)$ is finite.

It can be shown that $\max\{\mathfrak s,\mathfrak b\}\le\mathfrak j_{2:1}\le\mathfrak j_{2:2}\le\mathrm{non}(\mathcal M)$.

I would like to have more information on the cardinals $\mathfrak j_{2:1}$ and $\mathfrak j_{2:2}$.

Problem 0. Is $\mathfrak j_{2:1}=\mathfrak j_{2:2}$ in ZFC?

Problem 1. Is $\mathfrak j_{2:2}=\mathrm{non}(\mathcal M)$ in ZFC?

Problem 2. What is the value of the cardinals $\mathfrak j_{2:1}$ and $\mathfrak j_{2:2}$ in the Random Model? (In this model $\mathfrak b=\mathfrak s=\omega_1<\mathfrak c=\mathrm{non}(\mathcal M)$, see $\S$11.4 in this survey paper of Blass).

Remark. It can be shown that the cardinal $\mathfrak j_{2:1}$ (resp. $\mathfrak j_{2:2}$) is equal to the smallest weight of a finitary coarse structure on $\omega$ that contains no infinite discrete subspaces (resp. contains no infinite asymptotically separated sets). In this respect $\mathfrak j_{2:1}$ can be considered as an asymptotic counterpart of the cardinal $\mathfrak z$, defined as the smallest weight of an infinite compact Hausdorff space that contain no nontrivial convergent sequences. The cardinal $\mathfrak z$ was introduced by Damian Sobota and deeply studied by Will Brian and Alan Dow.

The similarity between $\mathfrak j_{2:1}$ and $\mathfrak z$ suggests another

Problem 3. Is $\mathfrak j_{2:1}=\mathfrak z$ in ZFC?

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    $\begingroup$ A theorem of Koppelberg states that $\mathrm{cov}(\mathcal M) \leq \mathfrak{z}$. It's consistent that $\mathrm{non}(\mathcal M) < \mathrm{cov}(\mathcal M)$ (this happens in the Cohen model), and you've proved $\mathfrak{j} \leq \mathrm{non}(\mathcal M)$. So it is consistent that $\mathfrak{j} < \mathfrak{z}$. If you feel there's some connection between $\mathfrak{j}$ and $\mathfrak{z}$, maybe Problem 3 should ask whether $\mathfrak{j} \leq \mathfrak{z}$. If you could prove this upper bound, it would also solve Problem 1, since $\mathfrak{z}$ and $\mathrm{non}(\mathcal M)$ are incomparable. $\endgroup$
    – Will Brian
    Feb 21, 2020 at 20:35
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    $\begingroup$ Actually, Alan Dow has proved (though it's unpublished) that $\mathfrak{z} = \aleph_1$ in the Laver model. But we have $\mathfrak{b} = \aleph_2$ in the Laver model and hence $\mathfrak{j} = \aleph_2$ as well. So $\mathfrak{z} < \mathfrak{j}$ is consistent. Combined with my previous comment, this shows there is no ZFC-provable inequality between $\mathfrak{j}$ and $\mathfrak{z}$. $\endgroup$
    – Will Brian
    Feb 21, 2020 at 20:42

1 Answer 1

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I can answer problems 2 and 3, although I still don't know the answer to problems 0 and 1. The main point is that

$\mathfrak{j}_{2:1} = \mathfrak{c}$ in the random model.

I'll sketch a proof of this below. (It's a bit long, but I've tried to make it readable.) The proof actually shows a little more: it gives you $\mathrm{cov}(\mathcal{N}) \leq \mathfrak{j}_{2:1}$.

This result also answers problem 3, because we know that $\mathfrak{z} = \aleph_1$ in the random model. (This was first proved by Alan Dow and David Fremlin here. It is also a corollary to Theorem 4.2 in this paper by me and Alan.) Therefore $\mathfrak{z} < \mathfrak{j}_{2:2},\mathfrak{j}_{2:1}$ is consistent. On the other hand, Koppelberg proved that $\mathfrak{z} \leq \mathrm{cov}(\mathcal{M})$. (Actually, she proved the dual statement in the category of Boolean algebras here. Stefan Geschke wrote a purely topological proof here.) Because you have proved that $\mathfrak{j}_{2:2},\mathfrak{j}_{2:1} \leq \mathrm{non}(\mathcal{M})$, and because $\mathrm{non}(\mathcal{M}) < \mathrm{cov}(\mathcal{M})$ in the Cohen model, it follows that $\mathfrak{j}_{2:2},\mathfrak{j}_{2:1} < \mathfrak{z}$ is consistent. Thus there is no inequality between $\mathfrak{z}$ and either of $\mathfrak{j}_{2:2}$ of $\mathfrak{j}_{2:1}$ that is provable in $\mathsf{ZFC}$.

(I know I gave a different argument for this in the comments. I don't like that argument as much because it relies on Alan's unpublished -- and mostly unwritten -- argument that $\mathfrak{z} = \aleph_1$ in the Laver model. I'm sure he's right. But I like that the argument here relies on the fact that $\mathfrak{z} = \aleph_1$ in the random model, and you can go read one or two proofs of this if you like.)

Now let's sketch the proof that $\mathfrak{j}_{2:1} = \mathfrak{c}$ in the random model. For the sake of clarity, I'm going to avoid forcing jargon and give a probabilistic argument that (I hope) will give you the right idea.

To show that $\mathfrak{j}_{2:1} = \mathfrak{c}$ in the random model, let's first recall how random real forcing works. Roughly, we imagine ourselves to live in a universe $V$ of sets, containing real numbers, subsets of $\mathbb N$, lots of $2$-to$1$ functions, and whatever else. But we know that our universe is about to get bigger -- this is the forcing -- by the introduction of a "truly random" real number $r$. The new, bigger universe is called $V[r]$.

The first observation I'd like to make is that all continuous measures on uncountable Polish spaces are essentially isomorphic. This means that it doesn't matter whether we view $r$ as a random element of $\mathbb R$, or of $[0,1]$, or of $2^\omega$ with the standard product measure, or whatever. For this problem, we want to view $r$ as an infinite sequence of random selections from larger and larger finite sets $I_n$, where $I_n$ has size $n!$. We select, at random, only a single element from each set. (This can be formalized by saying that we'd like $r$ to be a random element of the Polish space $\prod_{n = 0}^\infty \{1,2,\dots,n!\}$, equipped with the usual product measure. But let's keep it informal.) So our universe is about to get bigger by introducing a truly random sequence of selections from some sets $I_0, I_1, I_2, \dots$ with $|I_n| = n!$.

Within $V$, we can try to anticipate objects that will be constructible from $r$ in $V[r]$. For example, we can anticipate that once we get $r$, we can build a set $J \subseteq \mathbb N$ according to the following recipe: first identify $I_n$ with the interval $[1+1+2+\dots+(n-1)!,1+1+2+\dots+(n-1)!+n!) \subseteq \mathbb N$, and then let the $n^{\mathrm{th}}$ element of $J$ be whatever $r$ randomly selects from this interval.

Now I claim that this set $J$ described above has the following property: if $f$ is any $2$-to-$1$ function in the ground model $V$, then the restriction of $f$ to $J$ is almost-injective. To prove this, it suffices to argue that it's true with probability $1$, given that $r$ makes its selections randomly. This suffices because this is precisely what we mean when we say that $r$ is a "truly random" addition to $V$: if there is a randomness test defined in $V$ (such as one defined from any $f \in V$), then $r$ is random with respect to that test.

So let's argue probabilistically. Fix a $2$-to-$1$ function $f \in V$. If $f(a) = f(b)$, we may view this as a "guess" that $f$ is making about our set $J$: the guess is that $a$ and $b$ are both in $J$. In other words, $f$ gets to guess at pairs from $J$ infinitely many times, and it is our job to prove that, with probability $1$, only finitely many of these guesses are correct.

So what is the probability that $f$ correctly guesses a pair of elements from $J$? If $f$ identifies a member of some $I_m$ with a member of some $I_n$, where $m \neq n$, then there is a probability of exactly $\frac{1}{m!n!}$ that $f$ will have correctly guessed a pair from $J$. When $f$ makes other kinds of guesses (not identifying some member of some $I_m$ with a member of some $I_n$, where $m \neq n$), then the probability is $0$ that $f$ will have correctly guessed a pair from $J$.

If $m < n$, then $f$ gets at most $|I_m| = m!$ chances to guess a pair from $J$ with one member in $I_m$ and the other in $I_n$. By the previous paragraph, the probability of one of these guesses being correct is $\leq\! m!\frac{1}{m!n!} = \frac{1}{n!}$. Summing over all $n > m$, it follows that the probability of $f$ correctly guessing any pair of elements from $J$ with one member in $I_m$ and the other in $I_n$ for some $n > m$ is $$\leq\! \sum_{n = m+1}^\infty \frac{1}{n!} < \frac{1}{(m+1)!} \sum_{k = 0}^\infty \frac{1}{(m+1)^k} = \frac{1}{(m+1)!}\frac{m+1}{m} < \frac{1}{m!m}.$$

Now fix $k > 0$. Summing over all $m > k$, we see that the probability of $f$ correctly guessing a pair of elements from $J$ with one member in $I_m$ and the other in $I_n$ for some $n > m > k$ is $$\leq\! \sum_{m = k+1}^\infty \frac{1}{m!m} < \sum_{m = k+1}^\infty \frac{1}{m!} < \frac{1}{k!k}.$$

Therefore the probability of $f$ correctly guessing a pair of elements from $J \setminus (I_0 \cup \dots \cup I_k)$ is at most $\frac{1}{k!k}$. For any fixed $\varepsilon > 0$, we can choose $K$ large enough that $\sum_{k = K}^\infty \frac{1}{k!k} < \varepsilon$. This means that for $K$ large enough, the probability of $f$ correctly guessing more than ${K+1} \choose 2$ pairs of elements of $J$ is less than $\varepsilon$. Therefore the probability of $f$ correctly guessing infinitely many pairs of elements of $J$ is less than $\varepsilon$. As $\varepsilon$ was arbitrary, the probability of $f$ correctly guessing infinitely many pairs of elements of $J$ is $0$.

This shows that our set $J$ in $V[r]$ "should" (probabilistically) have the property that $f \restriction J$ is almost injective for every $f \in V$. But as we said earlier, this means $J$ really does have this property.

Why does this mean $\mathfrak{j}_{2:1} = \mathfrak{c}$ in the random model? The random model is $V[G]$, where $G$ is a "random" element of the measure algebra $2^{\aleph_2}$. If $\mathcal F$ is any set of $\aleph_1$ $2$-to-$1$ functions in $V[G]$, then a standard "nice names" argument shows that there is some weight-$\aleph_1$ subalgebra $X$ of $2^{\aleph_2}$ such that $\mathcal F$ is already in the intermediate model $V[X \cap G]$. Because $|X| = \aleph_1$, there will be random reals added in moving from the intermediate model $V[X \cap G]$ to the final model $V[G]$ -- random over $V[X \cap G]$, not just over $V$. We've just showed that the addition of these random reals adds some $J$ that "works" for every $f \in \mathcal F$.

Why does this mean $\mathrm{cov}(\mathcal{N}) \leq \mathfrak{j}_{2:1}$? There are a few ways to see this. The easiest is probably just to go through the above argument and convince yourself that what we've really proved is that every $2$-to-$1$ function $f$ is "solved" by a measure-$1$ set of $J$'s in the Polish space $\prod_{n = 0}^\infty \{1,2,\dots,n!\}$. Equivalently, the set of $J$'s that fail to work for a given $2$-to-$1$ function $f$ is a null set $N_f$. Therefore, if $\mathcal F$ is any size $<\! \mathrm{cov}(\mathcal{N})$ family of $2$-to-$1$ functions, $\bigcup_{f \in \mathcal F}N_f$ does not cover our Polish space, and so there is some $J$ that works for every $f \in \mathcal F$.

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  • $\begingroup$ Thank you Will, very much, for the detail explanation. But if I understood correctly, everything follows from the lower bound $\mathrm{cov}(\mathcal N)\le j_{2:1}$ which holds in ZFC. And then we can just apply the know information (see the Table 4 in the Blass' survey) that $\mathrm{cov}(\mathcal N)=\mathfrak c$ in the Random Model. Right? $\endgroup$ Feb 25, 2020 at 15:59
  • $\begingroup$ Yes, that's right. We prove the lower bound by considering the construction of $J$ from a random sequence as described above, and then showing that a "sufficiently random" sequence makes $J$ work for a given $2$-to-$1$ function. To be honest, I phrased the whole thing in terms of forcing because that's how I thought of it, and by the time realized the argument can be modified to give us a ZFC inequality, I'd already written most of it down and didn't have the energy to go back and modify it too much! $\endgroup$
    – Will Brian
    Feb 25, 2020 at 16:09
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    $\begingroup$ @TarasBanakh: You would be correct if $J$ were defined by just randomly deciding (via a coin flip, for example) with probability $\frac{1}{2}$ whether any given integer is in $J$. This is what is often meant by "a random real" and it won't work here for the reason you state. Our set $J$ is constructed differently, by selecting just one member of each interval $I_k$, where $|I_k| = k!$. The probability that some particular $n$ is in our set $J$ is equal to $\frac{1}{k!}$, where $k$ is the unique number with $n \in I_k$. So the probability of selecting the doubleton $\{2n,2n+1\}$ is very small. $\endgroup$
    – Will Brian
    Feb 25, 2020 at 16:33
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    $\begingroup$ The lower bound $\mathrm{cov}(\mathcal N)\le \mathfrak j_{2:1}$ cannot be improved to $\mathrm{cov}(\mathcal E)\le\mathfrak j_{2:1}$ as it would imply the lower bound $\mathrm{cov}(\mathcal M)\le\mathrm{non}(\mathcal M)$ which does not hold in ZFC. $\endgroup$ Feb 25, 2020 at 16:52
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    $\begingroup$ A good reference for that sort of question is the book by Bartoszynski and Judah -- Chapter 7 shows you how to separate any two cardinals in Cichon's diagram. There are three ways listed to get $\mathfrak{b},\mathrm{cov}(\mathcal N) < \mathrm{non}(\mathcal M)$, although none of them is particularly simple to describe. I would imagine all of them have $\mathfrak{s} = \mathfrak{b}$, although this isn't stated explicitly in the text. I'm not sure what the $\mathfrak{j}$'s would be in these models, but I think that would be a good place to look. $\endgroup$
    – Will Brian
    Feb 25, 2020 at 17:20

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