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We define the function: $$\sigma_k{(n)}=\sum_{d \mid n} d^k$$ as the sum of divisors function of the $k$th power, where $k \in \mathbb{N_0}$, for $n \in \mathbb{N}$. Now, we define: $$S_k=\{a \space | \space \exists \space m \in \mathbb{N} \space ; \sigma_k{(m)}=a\}$$ It is clear that $S_0$ is the same as $\mathbb{N}$ since for any $n \in \mathbb{N}$, we have $\sigma_0{(2^{n-1})}=n$. However, it is clear than this is not true for $S_k$ where $k>0$.

What is the density of $S_k$ in $\mathbb{N}$ for $k \in \mathbb{N}$?

Edit: As pointed out by @ThomasAndrews in the comments below, $k>1$ has zero density by bounding. Now, the problem is solved if anybody is able to find the density of the sum of divisors function $\sigma(x)$ ($1$st power).

Haran
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  • Let $S_{\alpha}(\mathbb{N}) := {\sigma_{\alpha}(n): n \in \mathbb{Z}^{+}}$. To be clear, you are looking for the desities: $$S_{\alpha} = \lim_{x \rightarrow \infty} \frac{1}{x} \cdot #{1 \leq n \leq x: n \in S_{\alpha}(\mathbb{N})}.$$ – mds Jun 02 '19 at 13:55
  • Kevin Ford has some pretty well-known work on this type of problem for the Euler totient function: see article link. Perhaps you could adapt his method? – mds Jun 02 '19 at 13:57
  • Also, since you have $$\sigma_{\alpha}(X) = \prod_{p^{\beta} || x} \frac{p^{\beta+1}-1}{p-1},$$ this might (sort of) look like a sieve-type method by which you can rule out some definite cases for small cases of $\alpha \geq 1$. Just another suggestion for what to try. – mds Jun 02 '19 at 13:59
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    For $K = 1$ you're asking about http://oeis.org/A002191. The $n$th entry of this sequence appears to be around $0.5 n \log n$, meaning the density would be zero, but with the amount of data available there (1000 terms) I wouldn't even dignify this with the name of "conjecture". – Michael Lugo Jun 03 '19 at 13:38
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    For $k>1$ we have that $\sigma_k(n)\geq n^k,$ so you necessarily get a density of zero in that case. So you are left with $k=1.$ – Thomas Andrews Jun 06 '19 at 00:49
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    @MichaelLugo You're close! Have a look here https://en.wikipedia.org/wiki/Divisor_function#Growth_rate – Deb Nandy Jun 07 '19 at 02:36

4 Answers4

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The following answer is incorrect. The OP asked for the density of $S_1$, which is unambiguous. The following answer shows it's not the case that $\frac{1}{N}\sum_{n \le N} w(n)$ goes to $0$ as $N \to \infty$, where $w(n) := \#\{m \ge 1 : \sigma(m) = n\}$.


The density of $\{ \sigma_1(n), n \ge 1\}$ can't be zero because $$F(s)=\sum_{n=1}^\infty \frac{n}{\sigma_1(n)} n^{-s} =\prod_p(1+\sum_{k=1}^\infty \frac{p^k}{\sigma_1(p^k)}p^{-sk})= \prod_p (1+\frac{1}{1+p^{-1}}p^{-s}+O(p^{-2s}))\\= \exp(\sum_p p^{-s} + O(p^{-2s})+O(p^{-s-1}))$$ has a pole at $s=1$, if the density of $\{ \sigma_1(n), n \ge 1\}$ was $0$ since $\frac{n}{\sigma_1(n)} \in [0,1]$ we would have $$f(x)=\sum_{n \le x} \frac{n}{\sigma_1(n)}= o(x)$$ with $g(y) = \sup_{x > y} \frac{f(x)}{x}$ we'd have $\lim_{y \to \infty}g(y)=0$ and $$F(s) = s \int_1^\infty f(x)x^{-s-1}dx=O(s \int_1^y x x^{-\Re(s)-1}dx)+ O(s\int_y^\infty g(y)x x^{-\Re(s)-1}dx) \\ = O(|s| y) + O(\frac{|s|\, g(y)}{\Re(s)-1}) $$ wouldn't have a pole at $s=1$, since $g(y)$ can be taken arbitrary small.


That $\lim_{y \to \infty} g(y)$ converges to $Res(F(s),s=1)$ and that it is the density is a matter of the same Tauberian theorems as in the proof of the PNT (maybe applying the argument above as well as the tauberian theorems to $\sum_{n=1}^\infty \sigma_1(n)^{-s} = \prod_p (1+\sum_{k=1}^\infty (p+1)^{-s} + O(p^{-2s})$ is a better idea)

mathworker21
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reuns
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  • I don't get the last part. If you take $y$ large so that $g(y)$ is small, then the $O(|s|y)$ term is large. I do think there is still a pole at $s=1$. – mathworker21 Jun 08 '19 at 04:08
  • The pole is of order 1 say it is of residue $C$, the last part shows $\forall y, |C| \le g(y)$. Thus $g(y) \to 0$ implies $C= 0$ which contradicts there was a pole. – reuns Jun 08 '19 at 04:09
  • yea, you're right, my bad. hmmmm, I'm trying to see where my solution is wrong. I'll continue to think about yours as well – mathworker21 Jun 08 '19 at 04:13
  • Also, I don't think you prove the density is non-zero; I think you just show it doesn't have density $0$. The leftover case is non-existent density – mathworker21 Jun 08 '19 at 04:14
  • Sure, we need the tauberian theorems to show that – reuns Jun 08 '19 at 04:16
  • Ok, I finally found the flaw in this answer (I knew there had to be a flaw due to my answer, and more convincingly, the paper that Martin cited). Why is $\sum_{n \le x} \frac{n}{\sigma_1(n)} = o(x)$? It seems like you make the following general claim. Let $f: \mathbb{N} \to \mathbb{N}$ be such that $f(n) \ge n$ for each $n$ and ${f(n) : n \ge 1}$ is a density $0$ subset of $\mathbb{N}$; then $\sum_{n \le x} \frac{n}{f(n)} = o(x)$. To disprove this, take $f(1) = 1$ and $f(n) = 2^k$ if $2^{k-1} < n \le 2^k$ (nothing in your answer prevents $\sigma$ from being like this). A quick computation – mathworker21 Oct 15 '19 at 21:52
  • shows that $\sum_{n \le 2^k} \frac{n}{\sigma(n)}$ is about $2^k$ (which is not $o(2^k)$). Indeed, the sum is $1+\sum_{j=0}^{k-1}+\sum_{2^j < n \le 2^{j+1}} \frac{n}{2^{j+1}} \approx 1+\sum_{j=0}^{k-1}\frac{1}{2^{j+1}}\frac{1}{2}[(2^{j+1})^2-(2^j)^2] = 2^k$. – mathworker21 Oct 15 '19 at 21:54
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The point is that $\sigma(n)$, as $n$ ranges, is usually very even (i.e. many powers of $2$ divide it).

Fix $M \ge 1$ large. Since $\sigma(n) \ge n$ for each $n$, $$\#\{1 \le m \le M : m = \sigma(n) \text{ for some } n\} \le \#\{\sigma(n) : 1 \le n \le M\} \cap [M].$$ Up to a set of density 0, every positive integer $n$ has at least $\frac{1}{2}\log\log n$ prime divisors. Therefore, we expect there to be at least $\frac{1}{4}\log\log n$ prime divisors of $n$ with highest exponent dividing $n$ being odd. The point is that for such prime divisors, since $\sigma$ is multiplicative, they contribute a power of $2$ to $\sigma(n)$, so we expect $\frac{1}{2}\log\log n$ powers of $2$ dividing $\sigma(n)$, so $$\#\{\sigma(n) : 1 \le n \le M\} \cap [M] \le \#\{m \le M : 2^{\frac{1}{4}\log\log M} \mid m\}$$ has density $0$. I don't think it should be hard to make this more rigorous, but I'm watching the finals.

mathworker21
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    Implicitely I'm telling to the OP it makes more sense to weight ${ \sigma_1(n)}$ by how many times each value is taken because we have a generating function for it. I agree it is not obvious the weighted and non-weigthed densities are the same, which seems like a difficult general problem for multiplicative functions, and that for the particular case of $\sigma(n)$ your idea of using that $[1,2^{-\omega(n)}m]$ is a smaller set than $[1,m]$ is good (where $n= \sup \sigma^{-1}(m)$) – reuns Oct 16 '19 at 21:44
  • @reuns thanks. you should edit your answer to clarify. and for $\sigma$, the weighted and non-weighted densities are not the same, as our answers show. – mathworker21 Oct 17 '19 at 00:41
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This result can be found in the paper R. Sita Rama Chandra Rao and G. Sri Rama Chandra Murty: On a Theorem of Niven, Canad. Math. Bull. 22 (1979), no. 1, 113–115. DOI: 10.4153/CMB-1979-018-5, Zbl: 0401.10069, MR532280

The paper relies on some results from the paper Ivan Niven: The asymptotic density of sequences. Bull. Amer. Math. Soc., 57(6):420-434, 1951; Zbl: 0044.03603, MR0044561.


The proof $k=1$ is short enough to be reproduced here.

We want to show that the set $$C=\{\sigma(n); n\in\mathbb N\}$$ has zero density.

We will denote \begin{align*} d(A)&=\lim_{n\to\infty} \frac{A(n)}n\\ \overline d(A)&=\limsup_{n\to\infty} \frac{A(n)}n\\ \end{align*} for $A\subseteq \mathbb N$, where $A(n)=|\{k\in A; k\le n\}|$ denotes the number of the element os $A$ which are less than or equal to $n$. I.e, $d(A)$ denotes the asymptotic density and $\overline d(A)$ denotes the upper asymptotic density. (You can notice that $d(A)$ is defined only for some sets, while $\overline d(A)$ exists for each set. However, if $\overline d(A)=0$, then we get also $d(A)=0$. It is also useful to notice that $\overline d(A\cup B)\le \overline d(A)+\overline d(B)$.)

Let us fix an integer $k$. We divide the set $C$ into \begin{align*} C_1&=\{s\in C; 2^k\mid C\}\\ C_2&=\{s\in C; 2^k\nmid C\} \end{align*} It is clear that $\overline d(C_1)\le\frac1{2^k}$.

If $s\in C_2$, then $s=\sigma(t)$ for some $t$ which has at most $k$ prime factors with exponent one.1 Moreover, we have $t\le s$.

Let $D$ be the of all positive integers which have at most $k$ primes factors with exponent one. We see that $C_2(n)\le D(n)$, since if $s\in C_2$ and $s\le n$, then for the corresponding $t\in D$ we also have $t\le n$.

Since $d(D)=0$ (Niven, Corollary 2), we get $$d(C_2)=\lim_{n\to\infty} \frac{C_2(n)}n \le \lim_{n\to\infty} \frac{D(n)}n=0.$$ Consequently, we have $$\overline d(C)\le \overline d(C_1)+\overline d(C_2) = \frac1{2^k}.$$

Since the inequality $\overline d(C)\le\frac1{2^k}$ is true for every $k$, we get $\overline d(C)=0$ and, consequently, $d(C)=0$.

1Recall that if $n=p_1^{a_1}p_2^{a_2}\dots p_t^{a_t}$, then $\sigma(n)=\prod\limits_{i=1}^t\sigma(p_i^{a_i})$. If $a_i=1$ and $p_i$ is odd, then $\sigma(p_i^{a_i})=p_i+1$ is even. So if $n$ contains at least $k+1$ prime factors in first power, then at least $k$ of them is odd and we get $2^k\mid \sigma(n)$.

-1

Below shows that $\sigma_k(n) > n^k$ for $n>1$ and $k>0$. $\sigma_1(n) = \sum_{d|n}d = \sigma(n)$ is the very well known divisor function. Basic properties of $\sigma_k(n)$ and fundamental theorem of arithmetic will lead us to the result.

$\textbf{Property 1:}$ If $p$ is a prime number and $q \in \mathbb{N}$, then

$\sigma_k(p^q) = 1+p^k+p^{2k}+...+p^{qk}$

Proof of above property is straight forward as any integer of the form $p^i$ for $i \in \mathbb{N}$ and $i \leq q $ will divide $p^q$ with a quotient of $p^{q-i}$

$\textbf{Property 2:}$ If $gcd(a,b)=1$ then $\sigma_k(ab) = \sigma_k(a)\sigma_k(b)$

Proof: Let $d_a,d_b$ be such that $d_a|a$ and $d_b|b$. As $gcd(a,b) =1$ we also have $gcd(d_a,d_b) =1$ and thus there's a bijection between the sets $(d_a,d_b)\rightarrow d_ad_b$. Denote $d_{ab} = d_ad_b$ and we also have $d_{ab}|ab$.

Now $$\sigma_k(a)\sigma_k(b) = (\sum_{d_a | a} d_a^k)(\sum_{d_b | b} d_b^k) = \sum_{d_a | a, \ d' | b} (d_ad_b)^k = \sum_{d_{ab} | ab} d_{ab}^k=\sigma_k(ab)$$

Look at a different approach for $k=1$ here: The sigma function (sum of divisors ) multiplicative proof

Let me know in the comments if the bijection is not obvious, I write some more on that if needed.

Now using the fundamental theorem of arithmetic, for any $n\in \mathbb{N}$, there exists $p_1,p_2,...,p_q,a_1,a_2,...,a_q$ where $p_1,p_2,...,p_q$ are prime numbers and $a_1,a_2,...,a_q$ are positive integers such that,

$$n = p_1^{a_1}p_2^{a_2}...p_q^{a_q}$$

Then, $\sigma_k(n) = \sigma_k(p_1^{a_1}p_2^{a_2}...p_q^{a_q}) = \sigma_k(p_1^{a_1})\sigma_k(p_2^{a_2})...\sigma_k(p_q^{a_q})$

$=(1+p_1^k+p_1^{2k}+...+p_1^{a_1k})(1+p_2^k+p_2^{2k}+...+p_2^{a_2k})...(1+p_q^k+p_q^{2k}+...+p_q^{qk}) > p_1^{a_1k}p_2^{a_2k}...p_q^{a_qk}$

$= (p_1^{a_1}p_2^{a_2}...p_q^{a_q})^k = n^k$

Note that the inequality holds true only if $k \neq 0$ and $n \neq 1$.

Thus the Natural Density (https://en.wikipedia.org/wiki/Natural_density) of $\sigma_k(n)$ is $0$ for $k>0$

Deb Nandy
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  • Also for $k \ge 2$, $\frac{\sigma_k(n)}{n^k} = \sigma_{-k}(n) \in [1,\zeta(k)]$ so the distribution of ${ \sigma_k(n), n \ge 1}$ is close to ${C_k n^k, n \ge 1}$ – reuns Jun 07 '19 at 02:58
  • why "thus the natural density is 0" if $k = 1$? I don't get it. Also, obviously $\sigma_k(n) > n^k$, since $n \mid n$. – mathworker21 Jun 07 '19 at 04:05
  • First off, it is clear than $\sigma_k$, we have $\sigma_k(n)>n^k$ for $n>1$ as one of the divisors in the sum is $n$ itself. Moreover, this is only sufficient to show that density is $0$ for $k>1$. That is why I have added the edit to my question that $\sigma_1(n)$ is the only value which remains to be solved. – Haran Jun 08 '19 at 03:24