Harmonic LCM patterns and sunflower-free capacity


Abstract

Fix an integer \(k\ge 3\). Call a set \(A\subseteq [N]\) LCM-\(k\)-free if it does not contain distinct \(a_1,\dots,a_k\) such that \(\mathrm{lcm}(a_i,a_j)\) is the same for all \(1\le i<j\le k\). Define \[f_k(N):=\max\left\{\sum_{a\in A}\frac{1}{a}: A\subseteq [N] \text{ is LCM-k-free}\right\}.\] Addressing a problem of Erdős, we prove an explicit unconditional lower bound \[f_k(N)\ge (\log N)^{c_k-o(1)}, \qquad c_k:=\frac{k-2}{e((k-2)!)^{1/(k-2)}}.\] Let \(F_k(n)\) denote the maximum size of a \(k\)-sunflower-free family of subsets of \([n]\), and define the Erdős–Szemerédi \(k\)-sunflower-free capacity by \(\mu_k^{\mathrm S}:=\limsup_{n\to\infty}F_k(n)^{1/n}\). Motivated by a remark of Erdős relating this problem to the sunflower conjecture, we show that \[(\log N)^{\log\mu_k^{\mathrm S}-o(1)} \le f_k(N) \ll (\log N)^{\mu_k^{\mathrm S}-1+o(1)}.\] Furthermore, we show that the Erdős–Szemerédi sunflower conjecture fails for this fixed \(k\) (i.e. \(\mu_k^{\mathrm S}=2\)) if and only if \(f_k(N)=(\log N)^{1-o(1)}\).

1 Introduction↩︎

1.1 The problem and background↩︎

Fix integers \(k\ge 3\) and \(N\ge 1\). Following Erdős [1], we study subsets \(A\subseteq [N]:=\{1,2,\dots,N\}\) that avoid certain “equal–LCM” configurations. We say that \(A\) contains an LCM-\(k\)-tuple if there exist distinct \(a_1,\dots,a_k\in A\) such that all pairwise least common multiples coincide, i.e. \[\operatorname{lcm}(a_i,a_j)=\operatorname{lcm}(a_1,a_2)\qquad (1\le i<j\le k).\] We say \(A\) is LCM-\(k\)-free if it contains no LCM-\(k\)-tuple.

In [1], Erdős introduced the counting function \(g(k,x)\), defined as the largest integer \(s\) for which one can find \[1\le a_1<\cdots<a_s\le x\] with the property that no \(k\) of the \(a_i\) form an LCM-\(k\)-tuple. Erdős originally conjectured that \(g(k,x)=o(x)\) for every \(k\ge 3\), but later proved that this fails for all \(k\ge 4\); see [1]. In particular, for each \(k\ge 4\) there exists \(\delta_k>0\) such that \[g(k,x)\ge \delta_k x\] for all sufficiently large \(x\).

Erdős also considered a harmonic analogue. He showed [1] that for each \(k\ge 3\) there exists \(b_k>0\) such that whenever \(x\) is sufficiently large and \(1\le a_1<\cdots<a_s\le x\) satisfy \[\label{eq:Erdos-threshold} \sum_{i=1}^s \frac{1}{a_i} > b_k \log x,\tag{1}\] then some \(k\) of the \(a_i\) form an LCM-\(k\)-tuple. In [1], Erdős wrote:

I do not know how much 1 can be weakened so that there should always be \(k\) \(a\)’s every two of which have the same least common multiple.

If we define \[f_k(N)\;:=\;\max\left\{\sum_{a\in A}\frac{1}{a}:\;A\subseteq [N]\;\text{is LCM-k-free}\right\}.\] then Erdős is asking the following question.

Problem 1. Let \(k\ge 3\). Estimate \(f_k(N)\).

Problem 1 appears as Problem #856 on Bloom’s Erdős Problems website [2] and may be viewed as the harmonic counterpart of the counting problem introduced by Erdős in [1].

A trivial bound is \[f_k(N)\le \sum_{n\le N}\frac{1}{n} = \log N + O(1).\]

Erdős [1] provided a short proof of the improved upper bound \(f_k(N)\ll_k \log N/\log\log N\). It is observed in the comment section on the Erdős Problems website [2] that one can further improve this to \(f_k(N)\leq \log N \cdot \exp\left(-\Omega_k\left(\frac{\log\log N}{\log\log\log N}\right)\right)\). To our knowledge, no lower bounds of comparable strength were previously available.

1.2 A polylogarithmic lower bound↩︎

Our first result provides an explicit polylogarithmic lower bound.

Theorem 2. Fix an integer \(k\ge 3\). Then, as \(N\to\infty\), \[f_k(N)\ge (\log N)^{c_k-o(1)}, \qquad c_k:=\frac{k-2}{e ((k-2)!)^{1/(k-2)}}.\]

Our construction uses a “prime bucketing” scheme, which will be used for all lower bound constructions. We partition primes in a suitable interval into many disjoint blocks of comparable harmonic sum and form squarefree integers by choosing exactly \(k-2\) primes from each block. A short combinatorial lemma forces LCM-\(k\)-freeness, while the harmonic sum factorizes and can be optimized over a free parameter.

1.3 Connections with the sunflower problem↩︎

We next investigate the optimal exponent in the polylogarithmic bound. Erdős suggested that Problem 1 is related to the sunflower problem. Recall that a collection of \(k\) distinct sets \(S_1,\dots,S_k\) is called a \(k\)-sunflower if \[S_i\cap S_j = S_1\cap S_2 \qquad \text{for all }1\le i<j\le k.\] This common intersection is called the kernel. A family of sets \(\mathcal{F}\) is said to be \(k\)-sunflower-free if it contains no \(k\) distinct members forming a \(k\)-sunflower. Dually, a collection of \(k\) distinct sets \(S_1,\dots,S_k\) is called a \(k\)-cosunflower if \[S_i\cup S_j = S_1\cup S_2 \qquad \text{for all }1\le i<j\le k.\] A family \(\mathcal{F}\) is \(k\)-cosunflower-free if it contains no \(k\) distinct members forming a \(k\)-cosunflower.

In [1], Erdős wrote:

Problem 1 seems connected with the following combinatorial problem:

Problem 3. Let \(m=m(n,k)\) be minimal such that any distinct collection of sets \(A_1,\dots,A_m\subseteq [n]\) contains a \(k\)-sunflower. Estimate \(m(n,k)\), or ideally determine its asymptotic behavior.

Problem 3 is widely known as the Erdős–Szemerédi sunflower conjecture [3], and it appears as Problem #857 on Bloom’s Erdős Problems website [4]. Following the notation of [5], let \(F_k(n)\) be the maximum size of a \(k\)-sunflower-free family \(\mathcal{F}\subseteq 2^{[n]}\), and define the Erdős–Szemerédi \(k\)-sunflower-free capacity \[\mu_k^{\mathrm S}:=\limsup_{n\to\infty} F_k(n)^{1/n}.\]Trivially \(\mu_k^{\mathrm S}\le 2\), and the celebrated Erdős–Szemerédi sunflower conjecture [3] asserts that \(\mu_k^{\mathrm S}<2\) for every \(k\ge 3\). A standard tensor power argument1 shows that the limsup can be replaced with a limit: \[\label{eq:lim} \mu_k^{\mathrm S} =\lim_{n\to\infty} F_k(n)^{1/n}.\tag{2}\]

In this paper, we make Erdős’s suggested connection between Problem 1 and Problem 3 precise by showing the Erdős–Szemerédi sunflower conjecture is equivalent to a tight bound on \(f_k(N)\).

Theorem 4. For each \(k\ge 3\), we have \(\mu_k^{\mathrm S} = 2\) if and only if \(f_k(N) = (\log N)^{1 - o(1)}\).

The implication “\(\Rightarrow\)” is obtained by constructing a LCM-\(k\)-free set of squarefree integers whose prime-support sets form a large cosunflower-free family in an appropriate weighted product measure. The implication “\(\Leftarrow\)” follows from Theorem 5 below.

Theorem 5. Fix \(k\ge 3\). Then, as \(N\to\infty\), \[f_k(N)\ll (\log N)^{\mu_k^{\mathrm S}-1+o(1)}.\]

Its proof is a double-counting argument similar to Erdős’s original argument in [1]. To each integer \(m\) we associate a set system on the prime divisors of \(m\) and show that LCM-\(k\)-freeness forces these set systems to be \(k\)-sunflower-free. We then combine the resulting estimate with a Sathe–Selberg type lower bound for the harmonic sum of squarefree almost primes.

Finally, we wonder how good a lower bound for \(f_k(N)\) we can establish given knowledge of \(\mu_k^{\mathrm S}\). While we can obtain a lower bound by following the proof of Theorem 4, it is not good when \(\mu_k^{\mathrm S}\) is smaller than \(2\). Towards an improvement on Theorem 2, we show that

Theorem 6. Fix \(k\ge 3\). Then, as \(N\to\infty\), \[f_k(N) \ge (\log N)^{\log\mu_k^{\mathrm S} - o(1)}.\]

For \(k=3\), the best current upper bound due to Naslund and Sawin [5] states that \[\mu_3^{\mathrm S}\le \frac{3}{2^{2/3}}=1.889881574\dots\, .\] In the opposite direction, a construction of Deuber, Erdős, Gunderson, Kostochka and Meyer [6] yields \(\mu_3^{\mathrm S}>1.551\). Hence, by Theorems 5 and 6, we obtain the following consequence.

Corollary 7. As \(N\to\infty\), \[(\log N)^{\log(1.551) - o(1)} \leq f_3(N)\ll (\log N)^{\frac{3}{2^{2/3}}-1+o(1)}.\]

Unfortunately, Theorem 6 never gives an exponent greater than \(\log 2 < 0.7\), so it is strictly worse than Theorem 2 for \(k \geq 7\). We leave it as an open question to obtain the correct exponent.

Problem 8. In terms of \(\mu_k^{\mathrm S}\), determine the smallest \(c > 0\) such that for all sufficiently large \(N\), we have \[f_k(N) \leq (\log N)^{c + o(1)}.\]

The rest of the paper is organized as follows. In Section 2 we fix notation and record two analytic inputs. In Section 3 we prove our unconditional lower bound (Theorem 2). In Section 4 we prove the capacity-based upper bound (Theorem 5). In Section 5 we prove the full-density equivalence in Theorem 4. In Section 6 we establish the capacity-based lower bound Theorem 6. Finally, the appendix contains the proof of the technical Lemma 10.

Acknowledgements↩︎

The authors would like to express their sincere gratitude to Thomas Bloom and Terence Tao for valuable comments posted on the Erdős Problems website, which inspired the present work. They are also grateful to Thomas Bloom for founding and maintaining the Erdős Problems website.

2 Preliminaries↩︎

2.1 Notation and asymptotic conventions↩︎

Throughout the paper, \(\log\) denotes the natural logarithm. For a positive integer \(n\), let \(\omega(n)\) denote the number of distinct prime factors of \(n\), and let \(\Omega(n)\) denote the number of prime factors of \(n\) counted with multiplicity. For a condition \(E\) (e.g.\(i\in F\)), we write \(\mathbf{1}_{E}\) for the indicator of \(E\), namely \(\mathbf{1}_{E}=1\) if \(E\) holds and \(\mathbf{1}_{E}=0\) otherwise.

We use Vinogradov’s asymptotic notation. For functions \(f=f(n)\) and \(g=g(n)\), we write \(f=O(g)\), \(g=\Omega(f)\), \(f\ll g\), or \(g\gg f\) to mean that there exists a constant \(C>0\) such that \(|f(n)|\le C g(n)\) for all sufficiently large \(n\). We write \(f\asymp g\) or \(f=\Theta(g)\) to mean that \(f\ll g\) and \(g\ll f\), and we write \(f=o(g)\) to mean that \(f(n)/g(n)\to 0\) as \(n\to\infty\). If the implicit constant is allowed to depend on one or more parameters \(z_1,\dots,z_r\), we indicate this by writing \(f\ll_{z_1,\dots,z_r} g\), \(g\gg_{z_1,\dots,z_r} f\), \(f=O_{z_1,\dots,z_r}(g)\) or \(g=\Omega_{z_1,\dots,z_r}(f)\).

2.2 Auxiliary analytic estimates↩︎

In this subsection we record two standard analytic inputs that will be used in the proof of Theorem 5.

Lemma 9. Let \(z>0\) be a fixed real number. Then for all \(X\ge 2\) we have \[\sum_{m\le X}\frac{z^{\omega(m)}}{m} \ll_z (\log X)^z.\]

Proof. Fix \(X\ge 2\) and a real number \(z>0\). Since every integer \(m\le X\) has all its prime divisors \(\le X\), we have the crude but useful inequality \[\sum_{m\le X}\frac{z^{\omega(m)}}{m} \le \sum_{\substack{m\ge 1\\ \text{all prime divisors of }m\text{ are }\le X}} \frac{z^{\omega(m)}}{m} =: S(X).\]Because the arithmetic function \(n\mapsto z^{\omega(n)}\) is multiplicative, we can expand \(S(X)\) as a finite Euler product over primes \(p\le X\): \[S(X) = \prod_{p\le X}\left(\sum_{k=0}^\infty\frac{z^{\omega(p^k)}}{p^k}\right)= \prod_{p\le X}\left(1 + \sum_{k \ge 1} \frac{z}{p^k}\right)= \prod_{p\le X}\left(1 + \frac{z}{p-1}\right).\]Taking logarithms and using \(\log(1+u) \le u\), \[\log S(X) = \sum_{p\le X} \log \left(1 + \frac{z}{p-1}\right) \leq z\sum_{p\le X} \frac{1}{p-1}= z\log\log X + O(z),\]where we used the standard estimate \(\sum_{p\le X} (p-1)^{-1} = \log\log X + O(1)\). Thus \(S(X) \ll_z (\log X)^z\), and the claim follows. ◻

Lemma 10. Let \[H_\ell(N) := \sum_{\substack{n\le N\\ \omega(n)=\Omega(n)=\ell}} \frac{1}{n}.\]Then for every \(0<\eta<1\) we have \[\label{eq:H-ell-lower} H_\ell(N) \gg_\eta \frac{(\log\log N)^\ell}{\ell!} \qquad (N\to\infty,\;1\le \ell\le (1-\eta)\log\log N).\qquad{(1)}\]

Proof. See Appendix 7. ◻

3 An unconditional lower bound↩︎

We start from a simple combinatorial lemma.

Lemma 11. Let \(k\ge 3\). If \(S_1,\dots,S_k\) are \((k - 2)\)-element sets with the same pairwise union, then \(S_1=\cdots=S_k\).

Proof. Let \(U = \cup_{j = 1}^k S_j\). Write \(u:=|U|\) and \(r:=k-2\). For each \(j\) set \(M_j:=U\setminus S_j\). Then \(M_a\cap M_b=\varnothing\) for \(a\ne b\), since otherwise an element missing from both \(S_a\) and \(S_b\) would be missing from \(S_a\cup S_b=U\). Also \(|M_j|=u-r\) for all \(j\) because \(|S_j|=r\). Thus \[k(u-r)=\sum_{j=1}^k |M_j| = \left|\bigsqcup_{j=1}^k M_j\right|\le |U|=u,\] so \(u\le \frac{kr}{k-1}=\frac{k(k-2)}{k-1}<k-1=r+1\). Hence \(u\le r\). But \(u\ge r\) since each \(S_j\) has size \(r\) and lies in \(U\). Therefore \(u=r\), so \(u-r=0\) and every \(M_j\) is empty. Thus \(S_j=U\) for all \(j\). ◻

Proof of Theorem 2. Write \(L:=\log\log N\) and fix \(k\ge 3\), \(r:=k-2\). Let \[\delta:=\delta(N):=L^{-1/2}, \qquad t:=\left\lfloor \frac{(1-\delta)L}{B}\right\rfloor, \qquad x:=N^{1/(rt)}, \qquad y:=\exp(L^{1/3}),\] where \(B>1\) is a constant to be chosen later. For \(N\) large we have \(t\ge 1\), \(y<x\), and \(1/p\le 1/y\le \delta\) for every prime \(p\ge y\).

By Mertens’ theorem for primes, we have \[\label{eq:enough-total-sum} \sum_{y<p\le x}\frac{1}{p} =\log\log x-\log\log y+O(1) = L - \log(rt)-\frac{1}{3}\log L +O(1) \ge t(B+\delta)\tag{3}\] for \(N\) sufficiently large.

List the primes in \([y,x]\) in increasing order, and form disjoint sets \(P_1,P_2,\dots\) greedily as follows: start with \(P_1=\varnothing\) and keep adding the next unused prime \(p\) to the current set until its harmonic sum exceeds \(B\), then start a new set. Because each prime \(p\in[y,x]\) satisfies \(1/p\le \delta\), each completed set \(P_i\) satisfies \[\label{eq:bucket-sum-11} B \le \sum_{p\in P_i}\frac{1}{p} < B+\delta.\tag{4}\] So 3 implies that this process produces at least \(t\) completed sets \(P_1,\dots,P_t\).

Define \[A_N :=\left\{ n=\prod_{i=1}^t\;\prod_{p\in S_i} p \;:\;S_i\subseteq P_i,\;|S_i|=r\;\text{for all }i \right\}.\] Every \(n\in A_N\) is squarefree and satisfies \(n\le x^{rt}=N\), hence \(A_N\subseteq\{1,2,\dots,N\}\).

We claim that \(A_N\) is LCM-\(k\)-free. Suppose for contradiction that \(n_1,\dots,n_k\in A_N\) is an LCM-\(k\)-tuple. Write \[n_j=\prod_{i=1}^t \Bigl(\prod_{p\in S_i^{(j)}}p\Bigr), \qquad S_i^{(j)}\subseteq P_i,\;\;|S_i^{(j)}|=r.\] Since the prime sets \(P_i\) are disjoint across different \(i\), equality of the pairwise \(\operatorname{lcm}\)’s implies that for each fixed \(i\) the unions \(S_i^{(a)}\cup S_i^{(b)}\) are independent of the pair \((a,b)\). Let \(U_i\) denote this common union. Applying Lemma 11 in each bucket \(i\) yields \(S_i^{(1)}=\cdots=S_i^{(k)}\) for every \(1\le i\le t\), hence \(n_1=\cdots=n_k\), contradicting that the \(n_j\) are distinct. Therefore \(A_N\) is LCM-\(k\)-free.

For each \(i\) define \[E_i:=\sum_{\substack{S\subseteq P_i\\ |S|=r}}\;\frac{1}{\prod_{p\in S}p}.\] Then by multiplicativity across buckets, we have \(\sum_{n\in A_N}\frac{1}{n}=\prod_{i=1}^t E_i\). Write \(J_i:=\sum_{p\in P_i}1/p\), so by 4 we have \(B\le J_i<B+\delta\) and \(\max_{p\in P_i}1/p\le 1/y\le\delta\). Expanding \(J_i^r\) we have \[J_i^r = r! E_i + R_i,\] where \(R_i\) is the contribution of \(r\)-tuples with at least one repeated index. Choosing a repeated pair of positions and bounding the remaining factors by \(J_i\) gives the crude but sufficient estimate \[R_i \le \sum_{1\le u<v\le r}\;\sum_{\substack{(p_1,\dots,p_r)\in P_i^r\\ p_u=p_v}} \frac{1}{p_1\cdots p_r} \le \binom{r}{2}\left(\max_{p\in P_i}\frac{1}{p}\right)J_i^{r-1} \le \binom{r}{2}\delta(B+\delta)^{r-1}.\] Thus \[E_i \ge \frac{J_i^r}{r!}-\frac{\binom{r}{2}}{r!} \delta(B+\delta)^{r-1} \ge \frac{B^r}{r!}\left(1-O_{r}(\delta)\right),\] uniformly in \(1\le i\le t\) (here \(r=k-2\) is fixed). Therefore we have \[\sum_{n\in A_N}\frac{1}{n} =\prod_{i=1}^t E_i \;\ge\; \left(\frac{B^r}{r!}\left(1-O_{r}(\delta)\right)\right)^t.\] Since \(\delta=L^{-1/2}\) and \(t=(1+o(1))L/B\), where \(L=\log\log N\), it follows that \[\left(1-O_r(\delta)\right)^t=\exp \left(t \log\left(1-O_{r}(\delta)\right)\right)=\exp \left(-O_r(t\delta)\right) =\exp (-O_r(L^{\frac{1}{2}}))=(\log N)^{-o(1)}.\]Moreover, \[\left(\frac{B^r}{r!}\right)^t =\exp \left(t(r\log B-\log(r!))\right) =(\log N)^{\frac{r\log B-\log(r!)}{B}-o(1)}.\]Combining these estimates yields \[\sum_{n\in A_N}\frac{1}{n} \ge (\log N)^{\frac{r\log B-\log(r!)}{B}-o(1)}.\] Since \(A_N\) is LCM-\(k\)-free, we conclude that \[f_k(N) \ge (\log N)^{\frac{r\log B-\log(r!)}{B}-o(1)}.\] Recall that \(r = k -2\). Taking \(B=e (r!)^{1/r}\) gives \[f_k(N) \ge (\log N)^{r/(e(r!)^{1/r})-o(1)}=(\log N)^{c_k-o(1)}.\] This completes the proof. ◻

4 An upper bound via sunflower-free capacity↩︎

We now prove Theorem 5 by encoding LCM-\(k\)-free sets as sunflower-free families and applying a harmonic estimate for almost primes.

Proof of Theorem 5. Fix \(k\ge 3\), write \(\mu:=\mu_k^{\mathrm S}\) and let \(F_k(n)\) denote the size of the largest \(k\)-sunflower-free family \(\mathcal{F}\subseteq 2^{[n]}\). Then for every \(\delta>0\) there exists a constant \(C_1=C_1(\delta)>0\) such that \[\label{eq:F3-capacity} F_k(n)\le C_1 (\mu+\delta)^n\qquad\text{for all }n\ge 1.\tag{5}\]

Fix a set \(A\subseteq\{1,\dots,N\}\) which is LCM-\(k\)-free and write \(\mathcal{P}(m)\) for the set of prime divisors of \(m\). For integers \(\ell,m \ge 1\), let \(r_\ell(m)\) be the number of representations \[\label{eq:r-def} m=a\prod_{p\in S} p,\tag{6}\] where \(a\in A\) and \(S\subseteq \mathcal{P}(m)\) is an \(\ell\)-element set of primes. Equivalently, define \[\mathcal{F}_m:=\left\{S\subseteq \mathcal{P}(m): |S|=\ell,\;m=a\prod_{p\in S}p\;\text{for some }a\in A\right\}.\] Note that for fixed \(m\) and \(S\), the value of \(a\) is uniquely determined, hence \(r_\ell(m)=|\mathcal{F}_m|\).

Claim 12. For every \(m\) the family \(\mathcal{F}_m\) is \(k\)-sunflower-free.

Proof of Claim 12. Suppose, for a contradiction, that \(\mathcal{F}_m\) contains a \(k\)-sunflower \(S_1,\dots,S_k\) with common kernel \(K\) and pairwise disjoint petals \(P_i := S_i\setminus K\). For each \(i\), there exists distinct \(a_i\in A\) such that \[m = a_i\prod_{p\in S_i} p.\] Since \(S_i\cap S_j = K\) for all \(1\le i<j\le k\), we deduce \[\operatorname{lcm}(a_i,a_j) = \frac{m}{\gcd(m / a_i, m / a_j)} = \frac{m}{\prod_{p\in K} p} \quad\text{for all }1\le i<j\le k.\] Thus the \(k\) elements \(a_1,\dots,a_k\in A\) are distinct and have the same pairwise lcm. This contradicts the assumption that \(A\) is LCM-\(k\)-free. ◻

The family \(\mathcal{F}_m\) lives on the ground set \(\mathcal{P}(m)\) of size \(\omega(m)\). Therefore, by Claim 12 and the bound 5 , for any fixed \(\delta>0\) we have \[\label{eq:r-ell-m-bound} r_\ell(m) = |\mathcal{F}_m| \le F_k\bigl(\omega(m)\bigr) \le C_1(\delta) \bigl(\mu+\delta\bigr)^{\omega(m)}.\tag{7}\]

Fix \(\ell\ge 1\) and set \[H_\ell(N) := \sum_{\substack{n\le N\\\omega(n)=\Omega(n)=\ell}}\frac{1}{n}.\] Consider the double sum \[T := \biggl(\sum_{a\in A}\frac{1}{a}\biggr) H_\ell(N) = \sum_{a\in A}\frac{1}{a} \sum_{\substack{n\le N\\\omega(n)=\Omega(n)=\ell}}\frac{1}{n}.\] Put \(m:=an\). Then \(m\le N^2\). Each such pair \((a,n)\) produces a representation 6 of \(m\) (with the prime factors of \(n\) as the distinct primes \(p_1,\dots,p_\ell\)), hence contributes to \(r_\ell(m)\). Consequently, \[T = \sum_{a\in A}\sum_{\substack{n\le N\\\omega(n)=\Omega(n)=\ell}}\frac{1}{an} \leq \sum_{m\le N^2}\frac{r_\ell(m)}{m}.\] Using 7 , we get \[T \le C_1(\delta)\sum_{m\le N^2} \frac{(\mu+\delta)^{\omega(m)}}{m}.\]Taking \(z=\mu+\delta\) and \(X=N^2\) in Lemma 9, we obtain \[C_1(\delta)\sum_{m\le N^2} \frac{(\mu+\delta)^{\omega(m)}}{m} \ll_{\delta} (\log N+\log 2)^{\mu+\delta}\ll_{\delta} (\log N)^{\mu+\delta}.\] This means \[\label{eq:master-ineq} \biggl(\sum_{a\in A}\frac{1}{a}\biggr) H_\ell(N) \ll_{\delta} (\log N)^{\mu+\delta}.\tag{8}\] Let \(L := \log\log N\). Let \(\eta\in(0,1)\) be fixed for the moment, and restrict to integers \(\ell\) with \(1\le \ell\le (1-\eta)L\). By Lemma 10, \(H_\ell(N)\gg_\eta L^\ell/\ell!\), so 8 implies \[\label{eq:sumA-basic} \sum_{a\in A}\frac{1}{a} \ll_{\eta,\delta} (\log N)^{\mu+\delta} \frac{\ell!}{L^\ell}.\tag{9}\]

We now choose \(\ell\) as a function of \(N\) so as to optimise the decay of the factor \(\ell!/L^\ell\). Choose \(\ell:=\lfloor(1-\eta)L\rfloor\). By Stirling’s formula, \[\ell! = \sqrt{2 \pi \ell}\left(\frac{\ell}{e}\right)^\ell \left(1+O\left(\frac{1}{\ell}\right)\right),\]and hence \[\label{eq:ell-over-L1} \frac{\ell!}{L^\ell} = \exp \Bigl(\ell(\log\ell -1 -\log L)+O(\log\ell)\Bigr).\tag{10}\] Write \(\lambda:=\ell/L\). Then \(\lambda=1-\eta+O(1/L)\) and \(\log\ell = \log L + \log\lambda\). Therefore \[\label{eq:ell-over-L2} \ell(\log\ell -1 -\log L) = \lambda L(\log\lambda -1) = (1-\eta)L\bigl(\log(1-\eta)-1\bigr) + o(L).\tag{11}\] Plugging 10 and 11 into 9 gives \[\sum_{a\in A}\frac{1}{a} \ll_{\eta,\delta} (\log N)^{\mu+\delta} \exp\Bigl( (1-\eta)\left(\log(1-\eta)-1\right)L + o(L)\Bigr).\] Recalling that \(L=\log\log N\), this may be rewritten as \[\label{eq:ell-over-L6} \sum_{a\in A}\frac{1}{a} \ll_{\eta,\delta} (\log N)^{\Psi(\eta,\delta)+o(1)},\tag{12}\] where \(\Psi(\eta,\delta) := \mu+\delta + (1-\eta)\bigl(\log(1-\eta)-1\bigr)\).

We now analyse \(\Psi(\eta,\delta)\). For fixed \(\delta>0\), the function \(\eta\mapsto\Psi(\eta,\delta)\) is continuous on \([0,1)\), and \[\lim_{\eta\to 0^+}\Psi(\eta,\delta) = \mu+\delta-1.\]Now let \(\varepsilon>0\) be arbitrary. First choose \(\delta =\varepsilon/2\). By continuity of \(\Psi(\cdot,\delta)\) at \(\eta=0\), there exists \(\eta_0=\eta_0(\varepsilon)>0\) such that for all \(0<\eta\le\eta_0\) we have \[\Psi(\eta,\delta) \le \mu+\delta-1 + \varepsilon/2.\] For such \(\eta\), \(\Psi(\eta,\delta) \le \mu -1 + \delta + \varepsilon/2 \le \mu -1 + \varepsilon\). Recalling 12 , we conclude that for every \(\varepsilon>0\), we have \[\sum_{a\in A}\frac{1}{a} \ll_\varepsilon(\log N)^{\mu-1+\varepsilon}.\] Since \(A\subseteq\{1,\dots,N\}\) was an arbitrary LCM-\(k\)-free set, it follows that \[f_k(N) \ll_\varepsilon (\log N)^{\mu-1+\varepsilon}.\]This completes the proof. ◻

5 Equivalence at full density↩︎

In this section we prove Theorem 4. The direction \(f_k(N)=(\log N)^{1-o(1)} \Rightarrow \mu_k^{\mathrm S} = 2\) is immediate from Theorem 5 by comparing exponents. The reverse direction is more involved.

Assume \(\mu_k^{\mathrm S} = 2\). We first obtain large uniform \(k\)-cosunflower-free families at an arbitrary fixed density via a tensor/padding argument of Alon–Shpilka–Umans [7]. We then upgrade this to a weighted statement under a product measure using a different “blow-up construction”, and finally encode the resulting cosunflower-free family by squarefree integers to produce a LCM-\(k\)-free set with near-maximal harmonic sum.

5.1 Blow-ups and product measures↩︎

Within a fixed ground set, taking complements swaps \(k\)-sunflowers and \(k\)-cosunflowers: for \(S_1,\dots,S_k\subseteq U\) we have \[S_i\cup S_j\;\text{is constant for all }i<j \quad\Longleftrightarrow\quad (U\setminus S_i)\cap(U\setminus S_j)\;\text{is constant for all }i<j.\] We will work with cosunflowers. The following property is easy to check.

Proposition 13. Let \(k\ge 3\) and let \(S_1,\dots,S_k\) be sets. The pairwise unions \(S_i\cup S_j\) are independent of the pair \(1\le i<j\le k\) if and only if every element belongs to either \(0\) or at least \(k-1\) of the sets \(S_1,\dots,S_k\).

Definition 14 (Blow-up). Let \(U\) be a finite set equipped with a partition \[U=U_1\sqcup\cdots\sqcup U_t\sqcup \widetilde{U}.\] For \(F\subseteq [t]\), define the blow-up of \(F\) over \((\{U_i\}_{i=1}^t,\widetilde{U})\) to be the family \[B(F,\{U_i\}_{i=1}^t,\widetilde{U}) :=\left\{P\subseteq U:\;|P\cap U_i|=\mathbf{1}_{i\in F}\;\text{for all }i\in[t],\;\text{and }P\cap \widetilde{U}=\varnothing \right\}.\] For a family \(\mathcal{F}\subseteq 2^{[t]}\), define its blow-up over \((\{U_i\}_{i=1}^t,\widetilde{U})\) by \[B(\mathcal{F},\{U_i\}_{i=1}^t,\widetilde{U}) :=\bigsqcup_{F\in\mathcal{F}} B(F,\{U_i\}_{i=1}^t,\widetilde{U}),\] where the union is disjoint by definition.

Proposition 15. Let \(k\ge 3\). In the notation of Definition 14, if \(\mathcal{F}\subseteq 2^{[t]}\) is \(k\)-cosunflower-free, then its blow-up \(B(\mathcal{F},\{U_i\}_{i=1}^t,\widetilde{U})\subseteq 2^{U}\) is also \(k\)-cosunflower-free.

Proof. Suppose for a contradiction that \(B(\mathcal{F},\{U_i\}_{i=1}^t,\widetilde{U})\) contains a \(k\)-cosunflower \(P_1,\dots,P_k\), i.e.the sets are distinct and their pairwise unions coincide. For each \(j\) define the index set \[F_j:=\{i\in[t]:\;P_j\cap U_i\neq\varnothing\}\in\mathcal{F}.\]

Fix \(i\in[t]\). Since each \(P_j\) meets \(U_i\) in either \(0\) or \(1\) element, an element of \(U_i\) belongs to exactly the number of those \(P_j\) that choose it. By Proposition 13 applied to \(P_1,\dots,P_k\), no element may belong to between \(1\) and \(k-2\) of the \(P_j\). Therefore the number of indices \(j\) with \(i\in F_j\) is either \(0\) or at least \(k-1\). Applying Proposition 13 to the sets \(F_1,\dots,F_k\subseteq[t]\) shows that their pairwise unions are constant.

If \(F_u=F_v\) for some \(u\neq v\), then \(P_u\) and \(P_v\) select the same set of blocks. Since \(P_u\neq P_v\), there is a block \(U_i\) with \(i\in F_u\) such that \(P_u\cap U_i=\{a\}\) and \(P_v\cap U_i=\{b\}\) for distinct \(a\neq b\). Both \(a\) and \(b\) belong to at least one of the sets \(P_1,\dots,P_k\), so by Proposition 13 each must belong to at least \(k-1\) of them. This is impossible because \(2(k-1)>k\) for \(k\ge 3\). Hence the sets \(F_1,\dots,F_k\) are distinct.

Therefore, \(F_1,\dots,F_k\) are distinct members of \(\mathcal{F}\) with constant pairwise union, i.e.a \(k\)-cosunflower in \(\mathcal{F}\), contradicting that \(\mathcal{F}\) is \(k\)-cosunflower-free. ◻

Definition 16 (Product measure). Let \(A\) be a finite set, and associate weights \(w_a\in[0,1]\) to each \(a\in A\). Define the product measure \(\mu_w\) on \(2^A\) by \[\mu_w(B) := \prod_{a\in B} w_a \prod_{a\in A\setminus B} (1-w_a), \qquad B\subseteq A.\] For a family \(\mathcal{A}\subseteq 2^A\), write \(\mu_w(\mathcal{A}):=\sum_{B\in\mathcal{A}}\mu_w(B)\). Equivalently, \(\mu_w(B)\) is the probability that a random subset of \(A\), formed by including each \(a\in A\) independently with probability \(w_a\), is exactly \(B\).

5.2 Uniform cosunflower-free families at fixed density↩︎

We next recall a variation of Problem 3 studied by Alon, Shpilka and Umans [7], and record a convenient “for all large \(N\)” consequence that will be used in the weighted argument.

Theorem 17. Fix an integer \(k\ge 3\). For a rational \(\beta >1\), let \(H(\beta,k)\) denote the following hypothesis:

\(H(\beta,k)\): There exists \(\eta>0\) such that for every integer \(n\) with \(\beta n\in\mathbb{Z}\), every family \(\mathcal{F}\subseteq \binom{[\beta n]}{n}\) with \(|\mathcal{F}|\ge \binom{\beta n}{n}^{\,1-\eta}\) contains a \(k\)-sunflower.

Then for any rationals \(\beta,\beta'>1\), the statements \(H(\beta,k)\) and \(H(\beta',k)\) are equivalent.

In particular, if \(\mu_k^{\mathrm S} = 2\), then \(H(\beta,k)\) fails for every rational \(\beta>1\), and thus for every fixed rational \(\alpha\in(0,1)\) and every \(\eta>0\), there exist a constant \(\widetilde{N}=\widetilde{N}(\alpha,\eta)\) such that for every integer \(N\ge \widetilde{N}\) there is an \(\lfloor \alpha N\rfloor\)-uniform, \(k\)-cosunflower-free family \[\mathcal{G}_N\subseteq \binom{[N]}{\lfloor \alpha N\rfloor} \qquad\text{with}\qquad |\mathcal{G}_N| \ge \binom{N}{\lfloor \alpha N\rfloor}^{1-\eta}.\]

Proof. The equivalence of \(H(\beta,k)\) for different rationals \(\beta>1\), as well as the stated consequence from \(\mu_k^{\mathrm S} = 2\), is proved in [7] (for \(k=3\)); the same argument applies to any fixed \(k\ge 3\) since it uses only heredity of being sunflower-free under restrictions and Cartesian products. In addition, their argument, together with 2 , easily gives the “all sufficiently large \(N\)” part of the theorem. ◻

5.3 A weighted cosunflower-free family of large product measure↩︎

We now combine Theorem 17 with the blow-up construction to obtain a new weighted version of Theorem 17.

Lemma 18. Suppose \(\mu_k^{\mathrm S} = 2\). Then for any \(\epsilon>0\), there exists \(K=K(\epsilon)>0\) such that the following holds. Let \(A\) be a finite set, and associate weights \(w_a\in[0,1]\) to each \(a\in A\). Assume:

  1. The total weight \(W:=\sum_{a\in A}w_a\) satisfies \(W\ge K\).

  2. Each weight satisfies \(w_a\le K^{-1}\).

Then there exists a \(k\)-cosunflower-free family \(\mathcal{A}\subseteq 2^A\) such that \[\mu_w(\mathcal{A}) \ge 2^{-\epsilon W}.\]

Proof. Fix \(\epsilon>0\). Since the conclusion for \(\epsilon_0\) implies the conclusion for any \(\epsilon\ge \epsilon_0\), we may assume \(0<\epsilon\le 1/10\).

1. Partition. Let \(c:=1/\lceil 1/\epsilon^2\rceil\). Then \(c\in(0,1)\cap\mathbb{Q}\) and \(c\asymp \epsilon^2\); in particular \(c\le \epsilon^2\le \epsilon/10\). We iteratively construct a partition \[A=A_1\sqcup A_2\sqcup\cdots\sqcup A_n\sqcup \widetilde{A}\] as follows: as long as there exists a subset of the remaining elements with total weight at least \(c\), take \(A_i\) to be a minimal such subset and remove it; at the end, put the remaining elements into \(\widetilde{A}\). By minimality, \[\label{eq:minimal95condition95c} \sum_{a\in A_i}w_a \in [c, c+K^{-1}],\tag{13}\] and \(\sum_{b\in \widetilde{A}}w_b\le c\). Consequently, \[\label{eq:partition95construction95wck951} n \in \left[\frac{W-c}{c+K^{-1}}, \frac{W}{c}\right].\tag{14}\] Define \[r_i:=\prod_{a\in A_i}(1-w_a),\qquad q_i:=\sum_{a\in A_i}w_a\prod_{b\in A_i\setminus\{a\}}(1-w_b),\qquad s:=\prod_{b\in\widetilde{A}}(1-w_b).\] Thus \(r_i\) is the probability that a \(\mu_w\)-random subset chooses no elements from \(A_i\), and \(q_i\) is the probability it chooses exactly one element from \(A_i\).

2. A large uniform index family. Set \[\delta:=\frac{\epsilon c}{10}.\] Apply Theorem 17 with \(\alpha=c\) and \(\eta=\delta\). By 14 we have \(n \ge \frac{W-c}{c+K^{-1}}\), so by increasing \(K\) (depending on \(\epsilon\)) we may assume that \(W\ge K \ge 100\) and \(n\ge \widetilde{N}(c,\delta)\). Hence Theorem 17 provides a \(k\)-cosunflower-free family \[\mathcal{F}\subseteq \binom{[n]}{m},\qquad m:=\lfloor cn\rfloor,\] satisfying \[\label{eq:F-size} |\mathcal{F}| \ge \binom{n}{m}^{1-\delta}.\tag{15}\]

3. Blow-up. Let \[\mathcal{A}:=B(\mathcal{F},\{A_i\}_{i=1}^n,\widetilde{A})\] be the blow-up of \(\mathcal{F}\) over \((\{A_i\}_{i=1}^n,\widetilde{A})\). By Proposition 15, \(\mathcal{A}\) is \(k\)-cosunflower-free.

4. Lower bounding \(\mu_w(\mathcal{A})\). For each \(F\in\mathcal{F}\), by independence across the blocks we have \[\mu_w\left(B(F,\{A_i\}_{i=1}^n,\widetilde{A})\right)= s\prod_{i\in F} q_i\prod_{i\notin F} r_i.\] We now lower bound \(r_i,q_i,s\). Since \(K\ge 100\), we know that \(w_a\le K^{-1} \le 0.01\) and \(1-x\ge e^{-x-x^2}\) holds for all \(x\in[0,0.01]\). Then \[r_i=\prod_{a\in A_i}(1-w_a) \ge \exp\left(-\sum_{a\in A_i}(w_a+w_a^2)\right).\] Since \(w_a^2\le K^{-1}w_a\) and 13 holds, we get \[\sum_{a\in A_i}(w_a+w_a^2)\le (1+K^{-1})\sum_{a\in A_i}w_a \le (1+K^{-1})(c+K^{-1})\le c+2 K^{-1}.\] Hence \[\label{eq:ri-lb} r_i \ge \exp\left(-c-2 K^{-1}\right).\tag{16}\] Moreover, \[\frac{q_i}{r_i} =\sum_{a\in A_i}\frac{w_a}{1-w_a} \ge \sum_{a\in A_i}w_a \ge c,\] so \[\label{eq:qi-lb} q_i \ge c\exp\left(-c-2 K^{-1}\right).\tag{17}\] Similarly, since \(\sum_{b\in \widetilde{A}}w_b\le c\), we have \[\label{eq:s-lb} s \ge \exp\left(-c-2 K^{-1}\right).\tag{18}\] Since every \(F\in\mathcal{F}\) has size \(|F|=m\), combining 16 , 17 , 18 yields \[\mu_w\left(B(F,\{A_i\}_{i=1}^n,\widetilde{A})\right) = s\prod_{i\in F} q_i\prod_{i\notin F} r_i \ge c^{m}\exp\Bigl(-\left(c+2 K^{-1}\right)(n+1)\Bigr).\] Summing over \(F\in\mathcal{F}\) and using 15 gives \[\label{eq:mu-start} \mu_w(\mathcal{A}) \ge \binom{n}{m}^{1-\delta} c^{m} \exp\left(-\left(c+2 K^{-1}\right)(n+1)\right).\tag{19}\]

5. Estimating the RHS. Since \(\binom{n}{m}\le 2^n\le e^n\), we have \[\binom{n}{m}^{1-\delta} =\binom{n}{m}\cdot \binom{n}{m}^{-\delta} \ge \binom{n}{m}\,e^{-\delta n}.\] Substituting this into 19 and choosing \(K\) so large that \(\frac{2}{K}(n+1)\le \delta n\) (for all \(n\) in our range; it suffices to take \(K\ge 4/\delta\)), we obtain \[\label{eq:mu-mid} \mu_w(\mathcal{A}) \ge \binom{n}{m}\,c^{m}\,e^{-c(n+1)}\,e^{-2\delta n}.\tag{20}\] Next we use the elementary lower bound (valid for \(0<k<n\)): \[\label{eq:binom-lb} \binom{n}{k} \ge \frac{1}{n+1} \left(\frac{n}{k}\right)^{k}\left(\frac{n}{n-k}\right)^{n-k}.\tag{21}\] Applying 21 with \(k=m\) and multiplying by \(c^m\), using \(m\le cn\), gives \[\binom{n}{m}c^m \ge \frac{1}{n+1}\left(\frac{cn}{m}\right)^m\left(\frac{n}{n-m}\right)^{n-m} \ge \frac{1}{n+1}\left(\frac{n}{n-m}\right)^{n-m}.\] Since \(m=\lfloor cn\rfloor\ge cn-1\), we have \(n-m\le (1-c)n+1\), and hence \(\frac{n}{n-m} \ge \frac{1}{1-c+1/n}\). Therefore, \[\binom{n}{m}c^m \ge \frac{1}{n+1}\left(1-c+1/n\right)^{-(n-m)} \ge \frac{1}{n+1}\exp\Bigl((c-1/n)(n-m)\Bigr),\] where we used \(1-x\le e^{-x}\). Substituting this into 20 yields \[\begin{align} \mu_w(\mathcal{A}) &\ge \frac{1}{n+1} \exp\Bigl((c-1/n)(n-m)\Bigr)\exp\Bigl(-c(n+1)\Bigr)\exp(-2\delta n)\\ &= \exp\Bigl(-c(m+1)-\frac{n-m}{n}\Bigr)\exp(-2\delta n)\\ &\ge \exp\bigl(-c(m+1)-1\bigr)\exp(-2\delta n), \end{align}\] since \((n-m)/n\le 1\). Now \(m\le cn\) implies \(c(m+1)\le c^2n+c\), and by 14 we have \(n\le W/c\) and thus \(c^2n\le cW\). By the definition of \(\delta\), we know that \[2\delta n \le 2\cdot \frac{\epsilon c}{10}\cdot \frac{W}{c}=\frac{\epsilon}{5}W.\] Thus \[\mu_w(\mathcal{A}) \ge \exp\bigl(-cW-c-1\bigr)\exp\Bigl(-\frac{\epsilon}{5}W\Bigr).\] Finally, let \(\lambda=\log 2-\frac{1}{5}>0\). Since \(c\le \epsilon^2 \le \epsilon/10\), for \(W\ge 101/\epsilon\) we have \(cW+c+1\le \lambda \epsilon W\), hence \[\exp(-cW-c-1) \ge \exp(-\lambda \epsilon W).\]Putting everything together, \[\mu_w(\mathcal{A}) \ge \exp(-\lambda \epsilon W)\exp\Bigl(-\frac{\epsilon}{5}W\Bigr) =\exp(-(\log 2)\epsilon W) =2^{-\epsilon W},\] as desired. ◻

5.4 Proof of Theorem 4↩︎

Proof of Theorem 4. “If” direction. Assume that \(f_k(N)=(\log N)^{1-o(1)}\) as \(N\to\infty\). By Theorem 5 we have \[f_k(N)\ll_k (\log N)^{\mu_k^{\mathrm S}-1+o(1)}.\] Comparing exponents forces \(\mu_k^{\mathrm S}-1\ge 1\), hence \(\mu_k^{\mathrm S}\ge 2\). Since trivially \(\mu_k^{\mathrm S}\le 2\), we conclude that \(\mu_k^{\mathrm S}=2\).

“Only if” direction. Assume that \(\mu_k^{\mathrm S} = 2\). Fix \(\epsilon>0\). We will construct, for all sufficiently large \(N\), a LCM-\(k\)-free set \(A\subseteq[N]\) with \[\sum_{a\in A}\frac{1}{a}\;\gg_{\epsilon}\;(\log N)^{1-\epsilon}.\] Since trivially \(f_k(N)\le \sum_{n\le N}\frac{1}{n}=\log N+O(1)\), this implies \(f_k(N)=(\log N)^{1-o(1)}\).

Let \(K:=K(\epsilon/2)\) be as in Lemma 18 (applied with parameter \(\epsilon/2\)). Let \(T=T(N)\to\infty\) be a threshold to be chosen later, and let \(P\) denote the set of primes in \([K,T]\). For each \(p\in P\) set \[w_p:=\frac{1}{p+1}.\] Then \(w_p\le (K+1)^{-1}\le K^{-1}\) for all \(p\in P\), and by Mertens’ theorem \[W:=\sum_{p\in P} w_p=\sum_{p\in P}\frac{1}{p+1}=\log\log T+O_{\epsilon}(1),\] so for \(T\) sufficiently large we have \(W\ge K\). Applying Lemma 18 (with \(\epsilon/2\)) to the ground set \(P\) with weights \((w_p)_{p\in P}\), we obtain a \(k\)-cosunflower-free family \(\mathcal{Q}\subseteq 2^{P}\) such that \[\mu_w(\mathcal{Q}) \ge 2^{-\epsilon W/2}.\]Define \[A_0:=\left\{ \prod_{p\in Q}p:\;Q\in\mathcal{Q}\right\}, \qquad A:=A_0\cap [N].\]

Claim 19. \(A_0\) (and hence \(A\)) is LCM-\(k\)-free.

Proof of Claim 19. Each element of \(A_0\) is squarefree and has all prime factors in \(P\). If \(a=\prod_{p\in Q}p\) and \(b=\prod_{p\in R}p\) with \(Q,R\subseteq P\), then \[\operatorname{lcm}(a,b)=\prod_{p\in Q\cup R}p.\] Thus, if \(a_1,\dots,a_k\in A_0\) are distinct and satisfy \(\operatorname{lcm}(a_i,a_j)\) constant for all \(i<j\), then their prime support sets \(Q_i\subseteq P\) satisfy \(Q_i\cup Q_j\) constant for all \(i<j\). Hence \(Q_1,\dots,Q_k\) form a \(k\)-cosunflower in \(\mathcal{Q}\), contradicting that \(\mathcal{Q}\) is \(k\)-cosunflower-free. This proves the claim. ◻

For \(Q\subseteq P\) we have \[\mu_w(Q)=\prod_{p\in Q}w_p\prod_{p\in P\setminus Q}(1-w_p), \qquad \mu_w(\emptyset)=\prod_{p\in P}(1-w_p),\] and since \(w_p/(1-w_p)=1/p\), it follows that \[\frac{\mu_w(Q)}{\mu_w(\emptyset)}=\prod_{p\in Q}\frac{w_p}{1-w_p}=\frac{1}{\prod_{p\in Q}p}.\] Therefore, \[\sum_{a\in A_0}\frac{1}{a} =\sum_{Q\in\mathcal{Q}}\frac{1}{\prod_{p\in Q}p} =\sum_{Q\in\mathcal{Q}}\frac{\mu_w(Q)}{\mu_w(\emptyset)} =\frac{\mu_w(\mathcal{Q})}{\mu_w(\emptyset)} \ge 2^{-\epsilon W/2}\cdot \frac{1}{\mu_w(\emptyset)}.\] Moreover, \[\frac{1}{\mu_w(\emptyset)}=\prod_{p\in P}\frac{1}{1-w_p}=\prod_{p\in P}\left(1+\frac{1}{p}\right) \gg_{\epsilon} \log T,\] again by Mertens’ theorem (the implied constant depends on \(K\), hence on \(\epsilon\)). Combining this with \(W=\log\log T+O_{\epsilon}(1)\) yields \[\label{eq:A0-harmonic-lb} \sum_{a\in A_0}\frac{1}{a} \gg_{\epsilon} (\log T)^{1-\frac{\log 2}{2}\epsilon}.\tag{22}\] It remains to bound the contribution of those \(a\in A_0\) with \(a>N\). Note that if \(\prod_{p\in Q}p\ge N\), then \(\sum_{p\in Q}\log p\ge \log N\), hence for \(a\in A_0\setminus [N]\) we have \[\frac{1}{\prod_{p\in Q}p} \le \frac{1}{\log N}\cdot \frac{\sum_{p\in Q}\log p}{\prod_{p\in Q}p}.\] Therefore, \[\begin{align} \sum_{a\in A_0\setminus [N]}\frac{1}{a} &\le \sum_{\substack{Q\subseteq P\\ \prod_{p\in Q}p\ge N}}\frac{1}{\prod_{p\in Q}p} \le \frac{1}{\log N}\sum_{Q\subseteq P}\frac{\sum_{p\in Q}\log p}{\prod_{p\in Q}p}\\ &= \frac{1}{\log N}\sum_{p\in P}\frac{\log p}{p}\prod_{q\in P\setminus\{p\}}\left(1+\frac{1}{q}\right)\\ &\le \frac{1}{\log N}\left(\prod_{q\in P}\left(1+\tfrac{1}{q}\right)\right)\sum_{p\in P}\frac{\log p}{p}. \end{align}\] Using \(\prod_{q\in P}(1+\frac{1}{q})\ll_{\epsilon}\log T\) and \(\sum_{p\in P}\frac{\log p}{p}=\log T+O_{\epsilon}(1)\), we obtain \[\label{eq:tail-bound} \sum_{a\in A_0\setminus [N]}\frac{1}{a} = O_{\epsilon}\left(\frac{\log^2 T}{\log N}\right).\tag{23}\]

Combining 22 and 23 gives \[\sum_{a\in A}\frac{1}{a} \ge \sum_{a\in A_0}\frac{1}{a}-\sum_{a\in A_0\setminus [N]}\frac{1}{a} \gg_{\epsilon} (\log T)^{1-\frac{\log 2}{2}\epsilon} -O_{\epsilon}\Bigl(\frac{\log^2 T}{\log N}\Bigr).\]Finally choose \(T=T(N)\) so that \[\log T = (\log N)^{1-\frac{3}{5}\epsilon}.\] Then the main term satisfies \[(\log T)^{1-\frac{\log 2}{2}\epsilon} =(\log N)^{(1-\frac{3}{5}\epsilon)(1-\frac{\log 2}{2}\epsilon)} \gg (\log N)^{1-\epsilon},\] while the error term satisfies \[\frac{\log^2 T}{\log N}=(\log N)^{1-\frac{6}{5}\epsilon} =o\bigl((\log N)^{1-\epsilon}\bigr).\] Hence for all sufficiently large \(N\) we have \(\sum_{a\in A}\frac{1}{a}\gg_\epsilon (\log N)^{1-\epsilon}\). Since \(\epsilon>0\) was arbitrary and, by Claim 19, the set \(A\) is LCM-\(k\)-free, we conclude that \(f_k(N)=(\log N)^{1-o(1)}\). ◻

6 A lower bound via sunflower-free capacity↩︎

Finally, we prove Theorem 6. Our construction is quite similar to the construction in the previous section, except for a different choice of prime bucketing.

Proof of Theorem 6. Let \(\mu:=\mu_k^{\mathrm S}\). If \(\mu\le 1\) the statement is trivial, so assume \(\mu>1\) and fix \(\varepsilon>0\).

1. A large cosunflower-free family on \([t]\). Recall that a \(k\)-sunflower is a collection of \(k\) distinct sets whose pairwise intersections are all equal. Dually, a \(k\)-cosunflower is a collection of \(k\) distinct sets whose pairwise unions are all equal. Taking complements in \([n]\) bijects \(k\)-sunflowers and \(k\)-cosunflowers.

Choose \(\lambda\) with \(1<\lambda<\mu\) and \[\label{eq:lambda-close-to-mu} \log\lambda>\log\mu-\frac{\varepsilon}{2}.\tag{24}\] By 2 , there exists \(t_0>0\) such that, for \(t \geq t_0\) there always exists a \(k\)-cosunflower-free set family \(\mathcal{F}_t \subset 2^{[t]}\) with \(| \mathcal{F}_t | \geq \lambda^t\).

2. Prime bucketing into \(t\) disjoint blocks of harmonic sum \(\ge 1\). Now fix \(N\) large (how large will be specified later) and set \[L:=\log\log N,\qquad t:=\left\lfloor L-2\log L\right\rfloor,\qquad \delta:=\frac{1}{L},\qquad y:=L^2,\qquad x:=N^{1/t}.\] For \(N\) sufficiently large we have \(t\ge t_0\), \(y<x\), and for every prime \(p>y\) we have \(1/p\le 1/y\le\delta\). By Mertens’ theorem, \[\sum_{p\le u}\frac{1}{p}=\log\log u+O(1)\qquad(u\to\infty),\] so \[\label{eq:enough-harmonic-mass} \sum_{y<p\le x}\frac{1}{p}= \left(L- \log t\right) -\log\log y + O(1) \geq t(1+\delta)\tag{25}\] for \(N\) sufficiently large.

We now construct disjoint sets of primes \(P_1,\dots,P_t\subseteq(y,x]\) greedily. List the primes in \((y,x]\) in increasing order. Start with \(P_1=\varnothing\) and keep adding the next unused prime to the current \(P_i\) until \(\sum_{p\in P_i}\frac{1}{p}\ge 1\), then start \(P_{i+1}\) and continue. Since every added prime satisfies \(1/p\le\delta\), each completed bucket satisfies \[\label{eq:bucket-sum} 1 \le \sum_{p\in P_i}\frac{1}{p} < 1+\delta.\tag{26}\] Thus 25 guarantees that at least \(t\) buckets are completed. Fix such \(P_1,\dots,P_t\) and set \[J_i:=\sum_{p\in P_i}\frac{1}{p}\in[1,1+\delta)\qquad(1\le i\le t).\]

3. Encode \(\mathcal{F}_t\) by squarefree integers \(\le N\). For each \(F\in\mathcal{F}_t\) define the set of squarefree integers \[\mathcal{A}(F):=\left\{ \prod_{i\in F}p_i: p_i\in P_i\;\text{for each }i\in F\right\}, \qquad A:=\bigcup_{F\in\mathcal{F}_t}\mathcal{A}(F).\] Because the buckets \(P_i\) are pairwise disjoint and we choose at most one prime from each, each element of \(A\) is squarefree and has all prime factors \(\le x\). Also \(|F|\le t\), hence every \(a\in A\) satisfies \(a\le x^{|F|}\le x^t=N\), so \(A\subseteq[N]\).

Claim 20. \(A\) is LCM-\(k\)-free.

Proof of Claim 20. Let \(\phi\) map a natural number to its set of prime divisors. Then \(\phi(A)\) is precisely the blow-up \(B(\mathcal{F}_t, \{P_i\}_{i = 1}^t, \emptyset)\). Since all \(a \in A\) are squarefree, \(\phi(\operatorname{lcm}(a,b))=\phi(a)\cup\phi(b)\). By Proposition 15, \(\phi(A)\) is \(k\)-cosunflower-free, so \(A\) is LCM-\(k\)-free. ◻

4. Compute the harmonic sum. For each \(a\in A\) define its index set \[I(a):=\{i\in[t]: a \text{ is divisible by some prime in }P_i\}.\] Since the buckets are disjoint and each \(a\in A\) contains at most one prime from each bucket, we have \(\mathcal{A}(F)=\{a\in A: I(a)=F\}\), and hence the families \(\{\mathcal{A}(F)\}_{F\in\mathcal{F}_t}\) are pairwise disjoint. Therefore \[\sum_{a\in A}\frac{1}{a}=\sum_{F\in\mathcal{F}_t}\;\sum_{a\in\mathcal{A}(F)}\frac{1}{a}.\] For each \(F\in\mathcal{F}_t\) we have \[\sum_{a\in \mathcal{A}(F)}\frac{1}{a} =\prod_{i\in F}\Bigl(\sum_{p\in P_i}\frac{1}{p}\Bigr) =\prod_{i\in F}J_i \;\ge\;1,\] using 26 . Hence \[\sum_{a\in A}\frac{1}{a} = \sum_{F\in\mathcal{F}_t}\sum_{a\in \mathcal{A}(F)}\frac{1}{a} \ge \sum_{F\in\mathcal{F}_t}1 = |\mathcal{F}_t|.\] Since \(A\) is LCM-\(k\)-free, we obtain \[f_k(N) \ge \sum_{a\in A}\frac{1}{a} \ge |\mathcal{F}_t| \ge \lambda^{t}.\]Recall that \(t=L-2\log L+O(1)\) with \(L=\log\log N\), hence \(t=L-o(L)\). Therefore \[\lambda^{t} =\exp\left(t \log\lambda\right) =(\log N)^{\log\lambda-o(1)}.\] By 24 , \(\log\lambda>\log\mu-\varepsilon/2\), so for \(N\) sufficiently large the \(o(1)\) term is at most \(\varepsilon/2\), and hence \[f_k(N) \ge (\log N)^{\log\mu-\varepsilon}.\] This proves the theorem. ◻

7 Proof of Lemma 10↩︎

Let \(L := \log\log N\). Fix \(0<\eta<1\). For \(\ell \ge 1\) and \(x\ge 3\) let \[A_{\ell}(x) := \#\{ n\le x : \omega(n)=\Omega(n)=\ell \}\] be the counting function of squarefree \(\ell\)-almost primes. The squarefree version of the Sathe–Selberg theorem (see for instance [8] or [9]) asserts that there exists a continuous function \(G(z)\) on \([0,2)\), given explicitly by \[G(z) = \frac{1}{\Gamma(1+z)} \prod_{p}\Bigl(1 + \frac{z}{p}\Bigr)\Bigl(1-\frac{1}{p}\Bigr)^z,\] such that for every \(\varepsilon\in(0,2)\), uniformly for integers \(\ell\) with \(1\le \ell \le (2-\varepsilon)\log\log x\), one has \[\label{eq:sathe-selberg-squarefree} A_{\ell}(x) = G\left(\frac{\ell-1}{\log\log x}\right) \frac{x}{\log x} \frac{(\log\log x)^{\ell-1}}{(\ell-1)!} \left(1 + O_\varepsilon\left(\frac{\ell}{(\log\log x)^2}\right)\right).\tag{27}\] Note that \(G(z)>0\) for all \(z\in[0,2)\), since each Euler factor and \(1/\Gamma(1+z)\) is positive on \([0,2)\).

Now fix \(N\ge 3\) large and let \(\ell\) be an integer with \(1\le \ell\le (1-\eta)L\).

The case \(\ell=1\). In this case \[H_1(N) = \sum_{\substack{n\le N\\ \omega(n)=\Omega(n)=1}}\frac{1}{n} = \sum_{p\le N} \frac{1}{p} = \log\log N + O(1) = L + O(1),\] by Mertens’ theorem. Hence \(H_1(N)\gg L = L^1/1!\), which is ?? for \(\ell=1\).

The case \(\ell\ge 2\). Then \(2\le \ell\le (1-\eta)L\). By partial summation, we have \[H_\ell(N) = \sum_{\substack{n\le N\\ \omega(n)=\Omega(n)=\ell}} \frac{1}{n} = \frac{A_\ell(N)}{N} + \int_1^N \frac{A_\ell(t)}{t^2} dt.\] Since \(A_\ell(t)/t\ge 0\) for \(t \geq 1\), we have \[\label{eq:H-ell-int} H_\ell(N) \ge \int_2^N \frac{A_\ell(t)}{t^2} dt.\tag{28}\]

We next apply 27 with \(x=t\). To ensure that the uniformity range for \(\ell\) is satisfied, we restrict the integral to a suitable subinterval where \(\log\log t\) is comparable to \(L\). Set \(I := \left\{t\in[2,N] : \tfrac12 L \le \log\log t \le L \right\}\). Thus, for \(t\in I\), \[\ell \le (1-\eta)L \le 2(1-\eta)\log\log t.\] Choose \(\varepsilon=2\eta\), so that \(2(1-\eta) = 2-\varepsilon\). Then for all \(t\in I\) and all \(2\le \ell\le (1-\eta)L\) we have \[1\le \ell\le (2-\varepsilon)\log\log t.\] Hence 27 applies to \(A_\ell(t)\) with \(x=t\) for all \(t\in I\), giving \[\label{eq:A-ell-asymp} A_\ell(t) = G\left(\frac{\ell-1}{\log\log t}\right) \frac{t}{\log t} \frac{(\log\log t)^{\ell-1}}{(\ell-1)!} \left(1 + O_{\eta}\left(\frac{\ell}{(\log\log t)^2}\right)\right)\tag{29}\] for all \(t\in I\). Substituting 29 into 28 and restricting the integral to \(t\in I\), we obtain \[\begin{align} H_\ell(N) &\ge \int_{t\in I} \frac{A_\ell(t)}{t^2} dt\\ &= \frac{1}{(\ell-1)!}\int_{t\in I} G\left(\frac{\ell-1}{\log\log t}\right) (\log\log t)^{\ell-1} \frac{dt}{t\log t} \left(1 + O_{\eta}\left(\frac{\ell}{(\log\log t)^2}\right)\right). \end{align}\]For \(t\in I\) we have \(\log\log t\asymp L\), and since \(\ell\le (1-\eta)L\), we have \[\frac{\ell}{(\log\log t)^2} \ll_\eta \frac{1}{L}.\] Thus, for \(N\) sufficiently large, the factor \(1 + O_{\eta}\bigl(\ell/(\log\log t)^2\bigr)\) is bounded below by, say, \(1/2\) on \(I\). Moreover, for \(t\in I\) we have \[0 \le \frac{\ell-1}{\log\log t} \le \frac{(1-\eta)L}{L/2} = 2(1-\eta) < 2,\] so that the argument of \(G\) stays in the compact interval \([0,2(1-\eta)]\subseteq[0,2)\). By continuity and positivity of \(G\) on \([0,2)\), there exists a constant \(c_\eta>0\) such that \[G(z) \ge c_\eta \qquad\text{for all } 0\le z\le 2(1-\eta).\]Therefore, using the substitution \(u=\log\log t\) (so \(du = dt/(t\log t)\)), we obtain \[\begin{align} H_\ell(N) &\ge \frac{1}{2(\ell-1)!} \int_{t\in I} G\left(\frac{\ell-1}{\log\log t}\right) (\log\log t)^{\ell-1} \frac{dt}{t\log t} \\&\ge \frac{c_\eta}{2(\ell-1)!} \int_{\frac{1}{2} L}^{L} u^{\ell-1} du. \end{align}\] The last integral can be evaluated explicitly: \[\int_{\frac{1}{2} L}^{L} u^{\ell-1} du = \frac{L^\ell}{\ell}\left(1 - 2^{-\ell}\right) \ge \frac{L^\ell}{2\ell}.\]Hence \[H_\ell(N) \ge \frac{c_\eta}{2(\ell-1)!}\cdot \frac{L^\ell}{2\ell} = \frac{c_\eta}{4} \frac{L^\ell}{\ell!}.\]This shows that for all sufficiently large \(N\) and all integers \(2\le \ell\le (1-\eta)L\) we have \[H_\ell(N) \ge C_\eta\,\frac{L^\ell}{\ell!}\] with \(C_\eta = c_\eta/4>0\) depending only on \(\eta\). Together with the case \(\ell=1\) treated above, this proves that \[H_\ell(N) \gg_\eta \frac{L^\ell}{\ell!}\] uniformly for \(1\le\ell\le(1-\eta)L\) as \(N\to\infty\). This is ?? , and the lemma is proved.0◻

References↩︎

[1]
no. theory, in: Mathematical Essays Dedicated to A. J. Macintyre, 1970, pp. 123–133.
[2]
.
[3]
.
[4]
.
[5]
.
[6]
.
[7]
.
[8]
no. Theory I: Classical Theory , Cambridge University Press, 2006.
[9]
no. Theory 211(2020), 513–529.

  1. Here is a concise description of the argument. Let \(\mathcal{F}_n\subseteq 2^{[n]}\) be a \(k\)-sunflower-free family. Choose \(r\in\{0,1,\dots,n\}\) maximizing \(|\mathcal{F}_n\cap\binom{[n]}{r}|\), and set \(\mathcal{F}_n':=\mathcal{F}_n\cap\binom{[n]}{r}\), so that \(|\mathcal{F}_n'|\ge \frac{1}{n+1}|\mathcal{F}_n|\). For each integer \(t\ge 2\), partition \([tn]\) into \(t\) subsets \(S_1\sqcup\cdots\sqcup S_t\) with \(|S_i|=n\). For each \(i\) fix a bijection \(\pi_i:[n]\to S_i\) and define a copy of \(\mathcal{F}_n'\) on \(S_i\) by \(\mathcal{F}_n'^{(i)}:=\{\pi_i(F):F\in\mathcal{F}_n'\}\subseteq 2^{S_i}\). Then one checks that \(\mathcal{F}_{n}^{\otimes t}:=\{F_1\sqcup\cdots\sqcup F_t:\;F_i\in\mathcal{F}_n'^{(i)}\}\subseteq 2^{[tn]}\) is \(k\)-sunflower-free and satisfies \(|\mathcal{F}_{n}^{\otimes t}|=|\mathcal{F}_n'|^t\ge (|\mathcal{F}_n|/(n+1))^t\).↩︎