Prime Number Theorem And ...

11 Tertiary explicit estimates

11.1 The least common multiple sequence is not highly abundant for large \(n\)

11.1.1 Problem statement and notation

Definition 11.1.1
#

\(\sigma (n)\) is the sum of the divisors of \(n\).

Definition 11.1.2
#

A positive integer \(N\) is called highly abundant (HA) if

\[ \sigma (N) {\gt} \sigma (m) \]

for all positive integers \(m {\lt} N\), where \(\sigma (n)\) denotes the sum of the positive divisors of \(n\).

Informally, a highly abundant number has an unusually large sum of divisors.

Definition 11.1.3
#

For each integer \(n \ge 1\), define

\[ L_n := \mathrm{lcm}(1,2,\dots ,n). \]

We call \((L_n)_{n \ge 1}\) the least common multiple sequence.

Clearly \(L_n\) has a lot of divisors, and numerical experiments for small \(n\) suggests that \(L_n\) is often highly abundant. This leads to the following question:

Original MathOverflow question. Is it true that every value in the sequence \(L_n = \mathrm{lcm}(1,2,\dots ,n)\) is highly abundant? Equivalently,
\[ \{ L_n : n \ge 1\} \subseteq HA? \]

Somewhat surprisingly, the answer is no: not every \(L_n\) is highly abundant.

It has previously been verified in Lean that \(L_n\) is highly aboundant for \(n \leq 70\), \(81 \leq n \leq 96\), \(125 \leq n \leq 148\), \(169 \leq n \leq 172\), and not highly abondant for all other \(n ≤ 10^{10}\). The arguments here establish the non-highly-abundance of \(L_n\) for all \(n \geq 89683^2\) sufficiently large \(n\), thus completing the determination in Lean of all \(n\) for which \(L_n\) is highly abundant. This argument was taken from this MathOverflow answer.

11.1.2 A general criterion using three medium primes and three large primes

The key step in the proof is to show that, if one can find six primes \(p_1,p_2,p_3,q_1,q_2,q_3\) obeying a certain inequality, then one can find a competitor \(M {\lt} L_n\) to \(L_n\) with \(\sigma (M) {\gt} \sigma (L_n)\), which will demonstrate that \(L_n\) is not highly abundant. More precisely:

Definition 11.1.4
#

In the next few subsections we assume that \(n \geq 1\) and that \(p_1,p_2,p_3,q_1,q_2,q_3\) are primes satisfiying

\[ \sqrt{n} {\lt} p_1 {\lt} p_2 {\lt} p_3 {\lt} q_1 {\lt} q_2 {\lt} q_3 {\lt} n \]

and the key criterion

\begin{equation} \label{eq:main-ineq} \prod _{i=1}^3\Bigl(1+\frac{1}{q_i}\Bigr) \le \Biggl( \prod _{i=1}^3 \Bigl(1+\frac{1}{p_i(p_i+1)}\Bigr) \Biggr) \Bigl(1 + \frac{3}{8n}\Bigr) \Biggl(1 - \frac{4 p_1 p_2 p_3}{q_1 q_2 q_3}\Biggr). \end{equation}
1

NOTE: In the Lean formalization of this argument, we index the primes from 0 to 2 rather than from 1 to 3.

Lemma 11.1.1
#

We have \(4 p_1 p_2 p_3 {\lt} q_1 q_2 q_3\).

Proof

Obvious from the non-negativity of the left-hand side of 1.

11.1.3 Factorisation of \(L_n\) and construction of a competitor

Lemma 11.1.2 Factorisation of \(L_n\)

There exists a positive integer \(L'\) such that

\[ L_n = q_1 q_2 q_3 \, L' \]

and each prime \(q_i\) divides \(L_n\) exactly once and does not divide \(L'\).

Proof

Since \(q_i {\lt} n\), the prime \(q_i\) divides \(L_n\) exactly once (as \(q_i^2 {\gt} n\)). Hence we may write \(L_n = q_1 q_2 q_3 L'\) where \(L'\) is the quotient obtained by removing these prime factors. By construction, \(q_i \nmid L'\) for each \(i\).

Lemma 11.1.3 Normalised divisor sum for \(L_n\)

Let \(L'\) be as in Lemma 11.1.2. Then

\begin{equation} \label{eq:sigmaLn} \frac{\sigma (L_n)}{L_n} \; =\; \frac{\sigma (L')}{L'} \prod _{i=1}^3 \Bigl(1 + \frac{1}{q_i}\Bigr). \end{equation}
2

Proof

Use the multiplicativity of \(\sigma (\cdot )\) and the fact that each \(q_i\) occurs to the first power in \(L_n\). Then

\[ \sigma (L_n) = \sigma (L') \prod _{i=1}^3 \sigma (q_i) = \sigma (L') \prod _{i=1}^3 (1+q_i). \]

Dividing by \(L_n = L' \prod _{i=1}^3 q_i\) gives

\[ \frac{\sigma (L_n)}{L_n} = \frac{\sigma (L')}{L'} \prod _{i=1}^3 \frac{1+q_i}{q_i} = \frac{\sigma (L')}{L'} \prod _{i=1}^3 \Bigl(1 + \frac{1}{q_i}\Bigr). \]

There exist integers \(m \ge 0\) and \(r\) satisfying \(0 {\lt} r {\lt} 4 p_1 p_2 p_3\) and

\[ q_1 q_2 q_3 = 4 p_1 p_2 p_3 m + r \]
Proof

This is division with remainder.

Definition 11.1.5
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With \(m,r\) as above, define the competitor

\[ M := 4 p_1 p_2 p_3 m L'. \]

With notation as above, we have:

  1. \(M {\lt} L_n\).

  2. \[ 1 {\lt} \frac{L_n}{M} = \Bigl(1 - \frac{r}{q_1 q_2 q_3}\Bigr)^{-1} {\lt} \Bigl(1 - \frac{4 p_1 p_2 p_3}{q_1 q_2 q_3}\Bigr)^{-1}. \]
Proof

The first item is by construction of the division algorithm. For the second, note that

\[ L_n = q_1 q_2 q_3 L' = (4 p_1 p_2 p_3 m + r) L' {\gt} 4 p_1 p_2 p_3 m L' = M, \]

since \(r{\gt}0\). For the third,

\[ \frac{L_n}{M} = \frac{4 p_1 p_2 p_3 m + r}{4 p_1 p_2 p_3 m} = 1 + \frac{r}{4 p_1 p_2 p_3 m} = \Bigl(1 - \frac{r}{4 p_1 p_2 p_3 m + r}\Bigr)^{-1} = \Bigl(1 - \frac{r}{q_1 q_2 q_3}\Bigr)^{-1}. \]

Since \(0 {\lt} r {\lt} 4p_1p_2p_3\) and \(4p_1p_2p_3 {\lt} q_1q_2q_3\), we have

\[ 0{\lt}\frac{r}{q_1 q_2 q_3}{\lt}\frac{4p_1p_2p_3}{q_1 q_2 q_3}, \]

so

\[ \Bigl(1-\frac{r}{q_1 q_2 q_3}\Bigr)^{-1} {\lt} \Bigl(1-\frac{4p_1p_2p_3}{q_1 q_2 q_3}\Bigr)^{-1}. \]

11.1.4 A sufficient condition

We give a sufficient condition for \(\sigma (M) \geq \sigma (L_n)\).

Suppose

\[ \frac{\sigma (M)}{M} \Bigl(1 - \frac{4 p_1 p_2 p_3}{q_1 q_2 q_3}\Bigr) \; \ge \; \frac{\sigma (L_n)}{L_n}. \]

Then \(\sigma (M) \ge \sigma (L_n)\), and so \(L_n\) is not highly abundant.

Proof

By Lemma 11.1.5,

\[ \frac{L_n}{M} {\lt} \Bigl(1 - \frac{4 p_1 p_2 p_3}{q_1 q_2 q_3}\Bigr)^{-1}. \]

Hence

\[ \frac{\sigma (M)}{M} \ge \frac{\sigma (L_n)}{L_n} \Bigl(1 - \frac{4 p_1 p_2 p_3}{q_1 q_2 q_3}\Bigr)^{-1} {\gt} \frac{\sigma (L_n)}{L_n} \cdot \frac{M}{L_n}. \]

Multiplying both sides by \(M\) gives

\[ \sigma (M) {\gt} \sigma (L_n) \cdot \frac{M}{L_n} \]

and hence

\[ \sigma (M) \ge \sigma (L_n), \]

since \(M/L_n{\lt}1\) and both sides are integers.

Combining Lemma 11.1.6 with Lemma 11.1.3, we see that it suffices to bound \(\sigma (M)/M\) from below in terms of \(\sigma (L')/L'\):

Lemma 11.1.7 Reduction to a lower bound for \(\sigma (M)/M\)

If

\begin{equation} \label{eq:sigmaM-lower} \frac{\sigma (M)}{M} \; \ge \; \frac{\sigma (L')}{L'} \Biggl( \prod _{i=1}^3 \Bigl(1+\frac{1}{p_i(p_i+1)}\Bigr) \Biggr) \Bigl(1 + \frac{3}{8n}\Bigr), \end{equation}
3

then \(L_n\) is not highly abundant.

Proof

Insert 3 and 2 into the desired inequality and compare with the assumed bound 1; this is a straightforward rearrangement.

11.1.5 Conclusion of the criterion

Lemma 11.1.8 Lower bound for \(\sigma (M)/M\)

With notation as above,

\[ \frac{\sigma (M)}{M} \ge \frac{\sigma (L')}{L'} \Biggl( \prod _{i=1}^3 \Bigl(1 + \frac{1}{p_i(p_i+1)}\Bigr) \Biggr) \Bigl(1 + \frac{3}{8n}\Bigr). \]
Proof

By multiplicativity, we have

\[ \frac{\sigma (M)}{M} = \frac{\sigma (L')}{L'} \prod _p \frac{1+p^{-1}+\dots +p^{-\nu _p(M)}}{1+p^{-1}+\dots +p^{-\nu _p(L')}}. \]

The contribution of \(p=p_i\) is

\[ \frac{(1+p_i^{-1}+p_i^{-2})}{1+p^{-1}_i} = 1 + \frac{1}{p_i(p_i+1)}. \]

The contribution of \(p=2\) is

\[ \frac{1+2^{-1}+\dots +2^{-k-2}}{1+2^{-1}+\dots +2^{-k}}, \]

where \(k\) is the largest integer such that \(2^k \le n\). A direct calculation yields

\[ \frac{(1+2^{-1}+\dots +2^{-k-2})}{1+2^{-1}+\dots +2^{-k}} = \frac{2^{k+3}-1}{2^{k+3}-4} = 1 + \frac{3}{2^{k+3}-4}, \]

Finally, since \(2^k \le n {\lt} 2^{k+1}\), we have \(2^{k+3} {\lt} 8n\), so

\[ \frac{3}{2^{k+3}-4} \ge \frac{3}{8n}, \]

So the contribution from the prime \(2\) is at least \(1 + 3/(8n)\).

Finally, the contribution of all other primes is at least \(1\).

We have thus completed the key step of demonstrating a sufficient criterion to establish that \(L_n\) is not highly abundant:

Let \(n \geq 1\). Suppose that primes \(p_1,p_2,p_3,q_1,q_2,q_3\) satisfy

\[ \sqrt{n} {\lt} p_1 {\lt} p_2 {\lt} p_3 {\lt} q_1 {\lt} q_2 {\lt} q_3 {\lt} n \]

and the key criterion 1. Then \(L_n\) is not highly abundant.

Proof

By Lemma 11.1.8, the condition 3 holds. By Lemma 11.1.7 this implies

\[ \frac{\sigma (M)}{M} \Bigl(1 - \frac{4 p_1 p_2 p_3}{q_1 q_2 q_3}\Bigr) \ge \frac{\sigma (L_n)}{L_n}. \]

Applying Lemma 11.1.6, we obtain \(\sigma (M) \ge \sigma (L_n)\) with \(M {\lt} L_n\), so \(L_n\) cannot be highly abundant.

Remark 11.1.1
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Analogous arguments allow other pairs \((c,\alpha )\) in place of \((4,3/8)\), such as \((2,1/4)\), \((6,17/36)\), \((30,0.632\dots )\); or even \((1,0)\) provided more primes are used on the \(p\)-side than the \(q\)-side to restore an asymptotic advantage.

11.1.6 Choice of six primes \(p_i,q_i\) for large \(n\)

To finish the proof we need to locate six primes \(p_1,p_2,p_3,q_1,q_2,q_3\) obeying the required inequality. Here we will rely on the prime number theorem of Dusart [ 13 ] .

Lemma 11.1.9 Choice of medium primes \(p_i\)
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Let \(n \ge X_0^2\). Set \(x := \sqrt{n}\). Then there exist primes \(p_1,p_2,p_3\) with

\[ p_i \le x \Bigl(1 + \frac{1}{\log ^3 x}\Bigr)^i \]

and \(p_1 {\lt} p_2 {\lt} p_3\). Moreover, \(\sqrt{n} {\lt} p_1\)

Proof

Apply Proposition 10.12.4 successively with \(x, x(1+1/\log ^3 x), x(1+1/\log ^3 x)^2\), keeping track of the resulting primes and bounds. For \(n\) large and \(x = \sqrt{n}\), we have \(\sqrt{n} {\lt} p_1\) as soon as the first interval lies strictly above \(\sqrt{n}\); this can be enforced by taking \(n\) large enough.

Lemma 11.1.10 Choice of large primes \(q_i\)
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Let \(n \ge X_0^2\). Then there exist primes \(q_1 {\lt} q_2 {\lt} q_3\) with

\[ q_{4-i} \ge n \Bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\Bigr)^{-i} \]

for \(i = 1,2,3\), and \(q_1 {\lt} q_2 {\lt} q_3 {\lt} n\).

Proof

Apply Theorem 10.12.4 with suitable values of \(x\) slightly below \(n\), e.g. \(x = n(1+1/\log ^3\sqrt{n})^{-i}\), again keeping track of the intervals. For \(n\) large enough, these intervals lie in \((\sqrt{n},n)\) and contain primes \(q_i\) with the desired ordering.

11.1.7 Bounding the factors in 1

Lemma 11.1.11 Bounds for the \(q_i\)-product
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With \(p_i,q_i\) as in Lemmas 11.1.9 and 11.1.10, we have

\begin{equation} \label{eq:qi-upper} \prod _{i=1}^3 \Bigl(1 + \frac{1}{q_i}\Bigr) \le \prod _{i=1}^3 \Bigl(1 + \frac{\bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\bigr)^i}{n} \Bigr). \end{equation}
4

Proof

By Lemma 11.1.10, each \(q_i\) is at least

\[ n\Bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\Bigr)^{-j} \]

for suitable indices \(j\), so \(1/q_i\) is bounded above by

\[ \frac{\bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\bigr)^i}{n} \]

after reindexing. Multiplying the three inequalities gives 4.

Lemma 11.1.12 Bounds for the \(p_i\)-product
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With \(p_i\) as in Lemma 11.1.9, we have for large \(n\)

\begin{equation} \label{eq:pi-lower} \prod _{i=1}^3 \Bigl(1 + \frac{1}{p_i(p_i+1)}\Bigr) \ge \prod _{i=1}^3 \Bigl( 1 + \frac{1}{\bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\bigr)^{2i} (n + \sqrt{n})} \Bigr). \end{equation}
5

Proof

By Lemma 11.1.9, \(p_i \le \sqrt{n} (1+1/\log ^3\sqrt{n})^i\). Hence

\[ p_i^2 \le n\bigl(1 + \tfrac {1}{\log ^3 \sqrt{n}}\bigr)^{2i} \quad \text{and}\quad p_i+1 \le p_i(1 + 1/\sqrt{n}) \le (1+1/\sqrt{n}) p_i. \]

From these one gets

\[ p_i(p_i+1) \le \bigl(1 + \tfrac {1}{\log ^3 \sqrt{n}}\bigr)^{2i} (n + \sqrt{n}), \]

and hence

\[ \frac{1}{p_i(p_i+1)} \ge \frac{1}{\bigl(1 + \tfrac {1}{\log ^3 \sqrt{n}}\bigr)^{2i} (n + \sqrt{n})}. \]

Taking \(1+\cdot \) and multiplying over \(i=1,2,3\) gives 5.

Lemma 11.1.13 Lower bound for the product ratio \(p_i/q_i\)
# Discussion

With \(p_i,q_i\) as in Lemmas 11.1.9 and 11.1.10, we have

\begin{equation} \label{eq:pq-ratio} 1 - \frac{4 p_1 p_2 p_3}{q_1 q_2 q_3} \ge 1 - \frac{4 \bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\bigr)^{12}}{n^{3/2}}. \end{equation}
6

Proof

We have \(p_i \le \sqrt{n} (1+1/\log ^3 \sqrt{n})^i\), so

\[ p_1 p_2 p_3 \le n^{3/2} \bigl(1 + \tfrac {1}{\log ^3 \sqrt{n}}\bigr)^{6}. \]

Similarly, \(q_i \ge n(1+1/\log ^3 \sqrt{n})^{-i}\), so

\[ q_1 q_2 q_3 \ge n^3 \bigl(1 + \tfrac {1}{\log ^3 \sqrt{n}}\bigr)^{-6}. \]

Combining,

\[ \frac{p_1 p_2 p_3}{q_1 q_2 q_3} \le \frac{n^{3/2} \bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\bigr)^{6}}{n^3 \bigl(1 + \frac{1}{\log ^3\sqrt{n}}\bigr)^{-6}} = \frac{\bigl(1 + \frac{1}{\log ^3 \sqrt{n}}\bigr)^{12}}{n^{3/2}}. \]

This implies 6.

11.1.8 Reduction to a small epsilon-inequality

Lemma 11.1.14 Uniform bounds for large \(n\)

For all \(n \ge X_0^2 = 89693^2\) we have

\[ \frac{1}{\log ^3 \sqrt{n}} \le 0.000675, \qquad \frac{1}{n^{3/2}} \le \frac{1}{89693}\cdot \frac{1}{n}. \]

and

\[ \frac{1}{n+\sqrt{n}} \ge \frac{1}{1 + 1/89693}\cdot \frac{1}{n}. \]
Proof

This is a straightforward calculus and monotonicity check: the left-hand sides are decreasing in \(n\) for \(n \ge X_0^2\), and equality (or the claimed upper bound) holds at \(n=X_0^2\). One can verify numerically or symbolically.

Lemma 11.1.15 Polynomial approximation of the inequality
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For \(0 \le \varepsilon \le 1/89693^2\), we have

\[ \prod _{i=1}^3 (1 + 1.000675^i \varepsilon ) \le \Bigl(1 + 3.01\varepsilon + 3.01\varepsilon ^2 + 1.01\varepsilon ^3\Bigr), \]

and

\[ \prod _{i=1}^3 \Bigl(1 + \frac{\varepsilon }{1.000675^{2i}}\frac{1}{1 + 1/89693}\Bigr) \Bigl(1 + \frac{3}{8}\varepsilon \Bigr) \Bigl(1 - \frac{4 \times 1.000675^{12}}{89693}\varepsilon \Bigr) \ge 1 + 3.36683\varepsilon - 0.01\varepsilon ^2. \]
Proof

Expand each finite product as a polynomial in \(\varepsilon \), estimate the coefficients using the bounds in Lemma 11.1.14, and bound the tails by simple inequalities such as

\[ (1+C\varepsilon )^k \le 1 + k C\varepsilon + \dots \]

for small \(\varepsilon \). All coefficients can be bounded numerically in a rigorous way; this step is a finite computation that can be checked mechanically.

Lemma 11.1.16 Final polynomial comparison
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For \(0 \le \varepsilon \le 1/89693^2\), we have

\[ 1 + 3.01\varepsilon + 3.01\varepsilon ^2 + 1.01\varepsilon ^3 \le 1 + 3.36683\varepsilon - 0.01\varepsilon ^2. \]
Proof

This is equivalent to

\[ 3.01\varepsilon + 3.01\varepsilon ^2 + 1.01\varepsilon ^3 \le 3.36683\varepsilon - 0.01\varepsilon ^2, \]

or

\[ 0 \le (3.36683 - 3.01)\varepsilon - (3.01+0.01)\varepsilon ^2 - 1.01\varepsilon ^3. \]

Factor out \(\varepsilon \) and use that \(0{\lt}\varepsilon \le 1/89693^2\) to check that the resulting quadratic in \(\varepsilon \) is nonnegative on this interval. Again, this is a finite computation that can be verified mechanically.

Proposition 11.1.1 Verification of 1 for large \(n\)

For every integer \(n \ge X_0^2 = 89693^2 \approx 8.04\times 10^9\), the primes \(p_i,q_i\) constructed in Lemmas 11.1.9 and 11.1.10 satisfy the inequality 1.

Proof

Combine Lemma 11.1.11, Lemma 11.1.12, and Lemma 11.1.13. Then apply Lemma 11.1.14 and set \(\varepsilon = 1/n\). The products are bounded by the expressions in Lemma 11.1.15, and the inequality in Lemma 11.1.16 then ensures that 1 holds.

11.1.9 Conclusion for large \(n\)

Theorem 11.1.2 Non-highly abundant for large \(n\)

For every integer \(n \ge 89693^2\), the integer \(L_n\) is not highly abundant.

Proof

By Proposition 11.1.1, there exist primes \(p_1,p_2,p_3,q_1,q_2,q_3\) satisfying the hypotheses of Theorem 11.1.1. Hence \(L_n\) is not highly abundant.

11.1.10 Bonus material

The following result is not needed for this application, but is worth recording nevertheless.

Sublemma 11.1.1 Formula for log of L equals Chebyshev psi
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For every \(n\), \(\log L_n = \sum _{p \leq n} \lfloor \log n / \log p \rfloor \log p\).

Proof

Compute the number of times \(p\) divides \(L_n\) and use the fundamental theorem of arithmetic.

Sublemma 11.1.2 Formula for Chebyshev psi
#

For every \(n\), \(\psi (n) = \sum _{p \leq n} \lfloor \log n / \log p \rfloor \log p\), where \(\psi \) is the Chebyshev psi function.

Proof

Compute the number of times \(p\) divides \(L_n\) and use the fundamental theorem of arithmetic.

Proposition 11.1.2 Log of L equals Chebyshev psi

For every \(n\), \(\log L_n = \psi (n)\), where \(\psi \) is the Chebyshev psi function.

Proof

Combine the previous results.

11.2 Erdos problem 392

The proof here is adapted from https://www.erdosproblems.com/forum/thread/392#post-2696 which in turn is inspired by the arguments in https://arxiv.org/abs/2503.20170.

Definition 11.2.1
#

We work with (approximate) factorizations \(a_1 \dots a_t\) of a factorial \(n!\).

Definition 11.2.2
#

The waste of a factorizations \(a_1 \dots a_t\) is defined as \(\sum _i \log (n / a_i)\).

The balance of a factorization \(a_1 \dots a_t\) at a prime \(p\) is defined as the number of times \(p\) divides \(a_1 \dots a_t\), minus the number of times \(p\) divides \(n!\).

If a factorization has zero total imbalance, then it exactly factors \(n!\).

Proof

The waste of a factorization is equal to \(t \log n - \log n!\), where \(t\) is the number of elements.

Proof
Definition 11.2.4

The score of a factorization (relative to a cutoff parameter \(L\)) is equal to its waste, plus \(\log p\) for every surplus prime \(p\), \(\log (n/p)\) for every deficit prime above \(L\), \(\log L\) for every deficit prime below \(L\) and an additional \(\log n\) if one is not in total balance.

If one is in total balance, then the score is equal to the waste.

Proof

If there is a prime \(p\) in surplus, one can remove it without increasing the score.

Proof

Locate a factor \(a_i\) that contains the surplus prime \(p\), then replace \(a_i\) with \(a_i/p\).

If there is a prime \(p\) in deficit larger than \(L\), one can remove it without increasing the score.

Proof

Add an additional factor of \(p\) to the factorization.

If there is a prime \(p\) in deficit less than \(L\), one can remove it without increasing the score.

Proof

Without loss of generality we may assume that one is not in the previous two situations, i.e., wlog there are no surplus primes and all primes in deficit are at most \(L\). If all deficit primes multiply to \(n\) or less, add that product to the factorization (this increases the waste by at most \(\log n\), but we save a \(\log n\) from now being in balance). Otherwise, greedily multiply all primes together while staying below \(n\) until one cannot do so any further; add this product to the factorization, increasing the waste by at most \(\log L\).

One can bring any factorization into balance without increasing the score.

Proof

Apply strong induction on the total imbalance of the factorization and use the previous three sublemmas.

Starting from any factorization \(f\), one can find a factorization \(f'\) in balance whose cardinality is at most \(\log n!\) plus the score of \(f\), divided by \(\log n\).

Proof

Combine Lemma 11.2.4, Lemma 11.2.3, and Lemma 11.2.2.

Definition 11.2.5
#

Now let \(M,L\) be additional parameters with \(n {\gt} L^2\); we also need the minor variant \(\lfloor n/L \rfloor {\gt} \sqrt{n}\).

Definition 11.2.6

We perform an initial factorization by taking the natural numbers between \(n-n/M\) (inclusive) and \(n\) (exclusive) repeated \(M\) times, deleting those elements that are not \(n/L\)-smooth (i.e., have a prime factor greater than or equal to \(n/L\)).

Sublemma 11.2.4

The number of elements in this initial factorization is at most \(n\).

Proof

The total waste in this initial factorization is at most \(n \log \frac{1}{1-1/M}\).

Proof

A large prime \(p \geq n/L\) cannot be in surplus.

Proof

No such prime can be present in the factorization.

A large prime \(p \geq n/L\) can be in deficit by at most \(n/p\).

Proof

This is the number of times \(p\) can divide \(n!\).

A medium prime \(\sqrt{n} {\lt} p ≤ n/L\) can be in surplus by at most \(M\).

Proof

Routine computation using Legendre’s formula.

A medium prime \(\sqrt{n} {\lt} p ≤ n/L\) can be in deficit by at most \(M\).

Proof

The number of times \(p\) divides \(a_1 \dots a_t\) is at least \(M \lfloor n/Mp \rfloor ≥ n/p - M\) (note that the removal of the non-smooth numbers does not remove any multiples of \(p\)). Meanwhile, the number of times \(p\) divides \(n!\) is at most \(n/p\).

A small prime \(p \leq \sqrt{n}\) can be in surplus by at most \(M\log n\).

Proof

Routine computation using Legendre’s formula, noting that at most \(\log n / \log 2\) powers of \(p\) divide any given number up to \(n\).

A small prime \(L {\lt} p \leq \sqrt{n}\) can be in deficit by at most \(M\log n\).

Proof

Routine computation using Legendre’s formula, noting that at most \(\log n / \log 2\) powers of \(p\) divide any given number up to \(n\).

A tiny prime \(p \leq L\) can be in deficit by at most \(M\log n + ML\pi (n)\).

Proof

In addition to the Legendre calculations, one potentially removes factors of the form \(plq\) with \(l \leq L\) and \(q \leq n\) a prime up to \(M\) times each, with at most \(L\) copies of \(p\) removed at each factor.

The initial score is bounded by

\[ n \log (1-1/M)^{-1} + \sum _{p \leq n/L} M \log n + \sum _{p \leq \sqrt{n}} M \log ^2 n / \log 2 + \sum _{n/L {\lt} p \leq n} \frac{n}{p} \log \frac{n}{p} + \sum _{p \leq L} (M \log n + M L \pi (n)) \log L. \]
Proof

Combine Lemma 11.2.5, Sublemma 11.2.5, Sublemma 11.2.6, Sublemma 11.2.7, Sublemma 11.2.8, Sublemma 11.2.9, Sublemma 11.2.10, and Sublemma 11.2.11, and combine \(\log p\) and \(\log (n/p)\) to \(\log n\).

Sublemma 11.2.12

If \(M\) is sufficiently large depending on \(\varepsilon \), then \(n \log (1-1/M)^{-1} \leq \varepsilon n\).

Proof

Use the fact that \(\log (1-1/M)^{-1}\) goes to zero as \(M \to \infty \).

Sublemma 11.2.13

If \(L\) is sufficiently large depending on \(M, \varepsilon \), and \(n\) sufficiently large depending on \(L\), then \(\sum _{p \leq n/L} M \log n \leq \varepsilon n\).

Proof

Use the prime number theorem (or the Chebyshev bound).

Sublemma 11.2.14

If \(n\) sufficiently large depending on \(M, \varepsilon \), then \(\sum _{p \leq \sqrt{n}} M \log ^2 n / \log 2 \leq \varepsilon n\).

Proof

Crude estimation.

Lemma 11.2.6
#
\[ \pi (n) = o(n) \quad \text{as } n \to \infty . \]
Proof

Given \(\varepsilon {\gt} 0\), choose \(a \neq 0\) with \(\varphi (a)/a {\lt} \varepsilon /2\) (using \(\prod _{p \leq n}(1 - 1/p) \to 0\)). For \(n \geq a + 2\),

\[ \pi (n) \leq \frac{\varphi (a)}{a} \cdot n + \varphi (a) + \pi (a+1) + 1. \]

Since \(\varphi (a)/a {\lt} \varepsilon /2\), for \(n\) large enough the constant terms are absorbed, giving \(\pi (n) {\lt} \varepsilon n\).

Sublemma 11.2.15

If \(n\) sufficiently large depending on \(L, \varepsilon \), then \(\sum _{n/L {\lt} p \leq n} \frac{n}{p} \log \frac{n}{p} \leq \varepsilon n\).

Proof

Bound \(\frac{n}{p}\) by \(L\) and use the prime number theorem (or the Chebyshev bound).

Sublemma 11.2.16
#

For all \(n \geq 2\), one has

\[ \pi (n) \leq \sqrt{n} + \frac{2n \log 4}{\log n}. \]
Proof

By Chebyshev’s bound, \(\prod _{p \leq n} p \leq 4^n\), so \(\sum _{p \leq n} \log p \leq n \log 4\). The number of primes \(p \leq \sqrt{n}\) is trivially at most \(\sqrt{n}\). For primes \(p {\gt} \sqrt{n}\), we have \(\log p {\gt} \frac{1}{2} \log n\), hence

\[ \bigl(\pi (n) - \pi (\sqrt{n})\bigr) \cdot \tfrac {1}{2} \log n {\lt} \sum _{\sqrt{n} {\lt} p \leq n} \log p \leq n \log 4, \]

giving \(\pi (n) - \pi (\sqrt{n}) {\lt} \frac{2n \log 4}{\log n}\). Adding \(\pi (\sqrt{n}) \leq \sqrt{n}\) yields the result.

Sublemma 11.2.17

If \(n\) sufficiently large depending on \(M, L, \varepsilon \), then \(\sum _{p \leq L} (M \log n + M L \pi (n)) \log L \leq \varepsilon n\).

Proof

Use the prime number theorem (or the Chebyshev bound).

The score of the initial factorization can be taken to be \(o(n)\).

Proof

Pick \(M\) large depending on \(\varepsilon \), then \(L\) sufficiently large depending on \(M, \varepsilon \), then \(n\) sufficiently large depending on \(M,L,\varepsilon \), so that the bounds in Sublemma 11.2.12, Sublemma 11.2.13, Sublemma 11.2.14, Sublemma 11.2.15, and Sublemma 11.2.17 each contribute at most \((\varepsilon /5) n\). Then use Proposition 11.2.2.

One can find a balanced factorization of \(n!\) with cardinality at most \(n - n / \log n + o(n / \log n)\).-

Proof

Combine Proposition 11.2.3 with Proposition 11.2.1 and the Stirling approximation.

Theorem 11.2.2
# Discussion

One can factorize \(n!\) into at most \(n/2 - n / 2\log n + o(n / \log n)\) numbers of size at most \(n^2\).-

Proof

Group the factorization arising in Theorem 11.2.1 into pairs, using Lemma 11.2.1.

11.3 Numerical verification of Goldbach

We record here a simple way to convert prime in short interval theorems, together with numerical verification of even Goldbach, to numerical verification of odd Goldbach.

Definition 11.3.1 Even Goldbach conjecture up to a given height
#

We say that the even Goldbach conjecture is verified up to height \(H\) if every even integer between \(4\) and \(H\) is the sum of two primes.

Proposition 11.3.1 Even Goldbach conjecture - unit test

The even Goldbach conjecture is verified up to height 30.

Proof

This is a simple unit test, which can be verified by hand.

Definition 11.3.2 Odd Goldbach conjecture up to a given height
#

We say that the odd Goldbach conjecture is verified up to height \(H\) if every odd integer between \(5\) and \(H\) is the sum of three primes.

Proposition 11.3.2 Even Goldbach implies odd Goldbach

If the even Goldbach conjecture is verified up to height \(H\), then the odd Goldbach conjecture is verified up to height \(H+3\).

Proof

If \(n\) is an odd integer between \(7\) and \(H+3\), then \(n-3\) is an even integer between \(4\) and \(H\), so we can write \(n-3 = p + q\) for some primes \(p\) and \(q\), and hence \(n = p + q + 3\).

Proposition 11.3.3 Even Goldbach plus PNT in short interval implies odd Goldbach

If every interval \((x(1-1/\Delta ), x]\) contains a prime for \(x \geq x_0\), the even Goldbach conjecture is verified up to height \(H\), and the odd Goldbach conjecture is verified up to height \(x_0+4\), then the odd Goldbach conjecture is verified up to height \((H-4)\Delta + 4\).

Proof

If \(x \leq x_0+4\) then we are done by hypothesis, so assume \(x_0+4 {\lt} x \leq H\Delta \). By hypothesis, there is a prime \(p\) with \((x-4)(1-1/\Delta ) {\lt} p \leq x-4\). Then \(x-p\) is even, at least \(4\), and at most \((x-4)/\Delta + 4 \leq H\), so is the sum of two primes, giving the claim.

Proposition 11.3.4 Richstein’s verification of even Goldbach
#

[ 25 ] The even Goldbach conjecture is verified up to \(4 \times 10^{14}\).

Proof

Numerical verification.

Proposition 11.3.5 Ramaré and Saouter’s verification of odd Goldbach

[ 24 , Corollary 1 ] The odd Goldbach conjecture is verified up to \(1.13256 \times 10^{22}\).

Proof

Combine Proposition 11.3.4, Proposition 11.3.2, and Theorem 10.13.6.

Proposition 11.3.6 e Silva–Herzog–Piranian verification of even Goldbach

[ 22 ] The even Goldbach conjecture is verified up to \(4 \times 10^{18}\).

Proof

Numerical verification.

Proposition 11.3.7 Helfgott’s verification of odd Goldbach for small \(n\)

[ 17 , Appendix C ] The odd Goldbach conjecture is verified up to \(1.1325 \times 10^{26}\).

Proof

Combine Proposition 11.3.6, Proposition 11.3.2, and Theorem 10.13.6.

The arguments in [ 17 , Appendix C ] push the bound further than this, but require unpublished estimates of Ramare. However, similar arguments were established in [ 19 ] , and we present them here.

Proposition 11.3.8 e Silva–Herzog–Piranian verification of even Goldbach (extended)

[ 22 ] The even Goldbach conjecture is verified up to \(4 \times 10^{18} + 4\).

Proof

If \(N = 4 \times 10^{18}\), use the fact that \(211, 313, N-209, N-309\) are all prime.

Proposition 11.3.9 Kadiri–Lumley’s verification of odd Goldbach for small \(n\)

[ 19 , Corollary 1.2 ] The odd Goldbach conjecture is verified up to \(1966196911 \times 4 \times 10^{18}\).

Proof

Combine Proposition 11.3.8, Proposition 11.3.2, and Theorem 10.13.19 with \(x_0 = e^{60}\) and \(\Delta = 1966090061\). (Actually, if one is only allowed to use the previous results listed here, one first needs to use the values \(x_0 = e^{59}\) and \(\Delta = 1946282821\) to cover an intermediate range of values.)

11.4 Ramanujan’s inequality

Use of prime number theorems to establish Ramanujan’s inequality

\[ \pi (x)^2 {\lt} \frac{e x}{\log x} \pi \Big(\frac{x}{e}\Big) \]

for sufficiently large \(x\), following [ 12 ] .

Sublemma 11.4.1 Criterion for Ramanujan’s inequality, substep 1
# Discussion

Let \(M_a \in \mathbb {R}\) and suppose that for \(x{\gt}x_a\) we have

\[ \pi (x) {\lt} x \sum _{k=0}^{4} \frac{k!}{\log ^{k+1}x}+\frac{M_a x}{\log ^6 x}. \]

Then for \(x {\gt} x_a\) we have

\begin{equation} \label{pipi} \pi ^2(x) {\lt} x^2 \Big\{ \frac{1}{\log ^2 x}+ \frac{2}{\log ^3 x}+ \frac{5}{\log ^4 x}+ \frac{16}{\log ^5 x}+ \frac{64}{\log ^6 x} + \frac{\epsilon _{M_a}(x)}{\log ^7 x} \Big\} \end{equation}
7

where

\[ \epsilon _{M_a} (x) = 72 + 2 M_a + \frac{2M_a+132}{\log x} + \frac{4M_a+288}{\log ^2 x} + \frac{12 M_a+576}{\log ^3 x}+\frac{48M_a}{\log ^4 x} + \frac{M_a^2}{\log ^5 x}. \]
Proof

Direct calculation

Sublemma 11.4.2 Criterion for Ramanujan’s inequality, substep 2
# Discussion

Let \(m_a \in \mathbb {R}\) and suppose that for \(x{\gt}x_a\) we have

\[ \pi (x) {\gt} x \sum _{k=0}^{4} \frac{k!}{\log ^{k+1}x}+\frac{m_a x}{\log ^6 x}. \]

Then for \(x {\gt} e x_a\) we have

\[ \frac{ex}{\log x} \pi \Big(\frac{x}{e} \Big) {\gt} x^2 \Big\{ \frac{1}{\log ^2 x}+ \frac{2}{\log ^3 x}+ \frac{5}{\log ^4 x}+ \frac{16}{\log ^5 x}+ \frac{64}{\log ^6 x} + \frac{\epsilon '_{m_a}(x)}{\log ^7 x} \Big\} , \]

where

\[ \epsilon '_{m_a}(x) = 206+m_a+\frac{364}{\log x} + \frac{381}{\log ^2 x}+\frac{238}{\log ^3 x} + \frac{97}{\log ^4 x} + \frac{30}{\log ^5 x} + \frac{8}{\log ^6 x}. \]
Proof

We have

\[ \frac{ex}{\log x} \pi \Big(\frac{x}{e} \Big) {\gt} \frac{x^2}{\log x} \Big( \sum _{k=0}^{4} \frac{k!}{(\log x - 1)^{k+1}}\Big) + \frac{m_a x}{(\log x-1)^{6}} \]

Substituting

\begin{eqnarray*} \frac{1}{(\log x - 1)^{k+1}} & = & \frac{1}{\log ^{k+1} x} \Big(1+ \frac{1}{\log x} + \frac{1}{\log ^2 x} + \frac{1}{\log ^3 x} + \cdots \Big)^{k+1} \\ & {\gt} & \frac{1}{\log ^{k+1} x} \Big(1+ \frac{1}{\log x}+ \cdots + \frac{1}{\log ^{5-k} x} \Big)^{k+1} \end{eqnarray*}

we obtain the claim.

Proposition 11.4.1 Criterion for Ramanujan’s inequality
# Discussion

[ 12 , Lemma 2.1 ] Let \(m_a, M_a \in \mathbb {R}\) and suppose that for \(x{\gt}x_a\) we have

\[ x \sum _{k=0}^{4} \frac{k!}{\log ^{k+1}x}+ \frac{m_a x}{\log ^6 x} {\lt} \pi (x) {\lt} x \sum _{k=0}^{4} \frac{k!}{\log ^{k+1}x}+\frac{M_a x}{\log ^6 x}. \]

Then Ramanujan’s inequality is true if

\[ x {\gt} \max ( e x_{a},x_{a}' ) \]

where \(x'_a := \exp ( \epsilon _{M_a} (x_{a}) - \epsilon '_{m_a} (x_{a}) )\).

Proof

Combine the previous two sublemmas.

Lemma 11.4.1 Integral identity for pi - Li

If \(x \geq 2\), then

\[ \pi (x) - \textrm{Li}(x) = \frac{\theta (x) - x}{\log x} + \frac{2}{\log 2} + \int _{2}^{x} \frac{\theta (t) -t}{t \log ^{2}t}\, dt. \]
Proof

Follows from Sublemma 10.5.6 and the fundamental theorem of calculus.

Sublemma 11.4.3 Upper bound for pi

Suppose that for \(x \geq 2\) we have \(|\theta (x)-x|\log ^{5} x\leq x a(x)\). Then

\[ \pi (x)\leq \frac{x}{\log x} +a(x)\frac{x}{\log ^6 x}+\int _2^x\frac{d t}{\log ^2 t}+\int _2^x\frac{a(t)}{\log ^7 t}\ dt. \]

(cf. [ 23 , § 5 ] )

Proof

Follows from Lemma 11.4.1 and the triangle inequality.

Sublemma 11.4.4 Lower bound for pi

Suppose that for \(x \geq 2\) we have \(|\theta (x)-x|\log ^{5} x\leq x a(x)\). Then

\[ \pi (x)\geq \frac{x}{\log x} -a(x)\frac{x}{\log ^6 x}+\int _2^x\frac{d t}{\log ^2 t}-\int _2^x\frac{a(t)}{\log ^7 t}\ dt. \]

(cf. [ 23 , § 5 ] )

Proof

Follows from Lemma 11.4.1 and the triangle inequality.

Lemma 11.4.2 Bound for integral of an inverse power of log
# Discussion

For \(x \geq 2\) we have

\[ \int _2^x \frac{dt}{\log ^7 t} {\lt} \frac{x}{\log ^7 x} + 7 \Big( \frac{\sqrt{x}}{\log ^8 2} + \frac{2^8 x}{\log ^8 x} \Big). \]
Proof

Integrate by parts to write the left-hand side as \(\frac{x}{\log ^7 x} - \frac{2}{\log ^7 2} + 7 \int _2^x \frac{t}{\log ^8 t} dt\). Discard the middle term. For the final term, split between \(\int _2^{\sqrt{x}}\) and \(\int _{\sqrt{x}}^x\). For the first, use the bound \(\int _2^{\sqrt{x}} \frac{t}{\log ^8 t} dt {\lt} \int _2^{\sqrt{x}} \frac{t}{\log ^8 2} dt\), and for the second, use the bound \(\int _{\sqrt{x}}^x \frac{t}{\log ^8 t} dt {\lt} \int _{\sqrt{x}}^x \frac{t}{\log ^8 x} dt\).

Sublemma 11.4.5 Error estimate for theta, range 1
# Discussion

For \(2 \leq x {\lt} 599\) we have

\[ E_\theta (x) \leq 1 - \frac{\log 2}{3}. \]
Proof

For \(x \in [2, 3)\) we have \(\theta (x) = \log 2\), so \(E_\theta (x) = 1 - \log 2 / x {\lt} 1 - \log 2 / 3\) since \(x {\lt} 3\). For \(x \in [3, 599)\) we use the LeanCert ChebyshevTheta engine: checkAllThetaRelErrorReal 3 599 (768/1000) 20 via native_decide gives \(|\theta (x) - x| \leq 0.768 x\), hence \(E_\theta (x) \leq 0.768 \leq 1 - \log 2 / 3\).

Sublemma 11.4.6 Error estimate for theta, range 2
#

For \(599 {\lt} x \leq \exp (58)\) we have

\[ E_\theta (x) \leq \frac{\log ^2 x}{8\pi \sqrt{x}}. \]
Proof

This is [ 23 , Lemma 6 ] .

Sublemma 11.4.7 Error estimate for theta, range 3
# Discussion

For \(\exp (58) {\lt} x {\lt} \exp (1169)\) we have

\[ E_\theta (x) \leq \sqrt\frac {8}{17\pi }\left(\frac{\log x}{6.455}\right)^{\frac{1}{4}}\exp \left(-\sqrt{\frac{\log x}{6.455}}\right). \]
Proof

This follows from Corollary 10.13.1.

Sublemma 11.4.8 Error estimate for theta, range 4

For \(\exp (1169) \leq x {\lt} \exp (2000)\) we have

\[ E_\theta (x) \leq 462.0\left(\frac{\log x}{5.573412}\right)^{1.52}\exp \left(-1.89\sqrt{\frac{\log x}{5.573412}}\right). \]
Proof

This follows from Corollary 10.13.1.

Sublemma 11.4.9 Error estimate for theta, range 5

For \(\exp (2000) \leq x {\lt} \exp (3000)\) we have

\[ E_\theta (x) \leq 411.5\left(\frac{\log x}{5.573412}\right)^{1.52}\exp \left(-1.89\sqrt{\frac{\log x}{5.573412}}\right). \]
Proof

This follows from Corollary 10.13.1.

Proposition 11.4.2 Equation (18) of Platt-Trudgian
# Discussion

For \(x \geq 2\) we have

\[ E_\theta (x) (\log x)^5 \leq a(x). \]
Proof

This follows from the previous five sublemmas.

Lemma 11.4.3 Monotonicity of a(x)
# Discussion

The function \(a(x)\) is nonincreasing for \(x \geq x_a\).

Proof

Follows from Lemma 2.0.1.

Lemma 11.4.4 Specific upper bound on pi

For \(x \geq x_a\),

\[ \pi (x) {\lt} x \sum _{k=0}^{4} \frac{k!}{\log ^{k+1}x}+\frac{M_a x}{\log ^6 x}. \]

.

Proof

This follows from the previous lemmas and calculations, including Lemma 11.4.2.

Lemma 11.4.5 Specific lower bound on pi

For \(x \geq x_a\),

\[ \pi (x) {\gt} x \sum _{k=0}^{4} \frac{k!}{\log ^{k+1}x}+\frac{m_a x}{\log ^6 x}. \]

.

Proof

This follows from the previous lemmas and calculations, including Lemma 11.4.2.

Lemma 11.4.6 Bound for εMₐ - εmₐ
# Discussion

We have \(\epsilon _{M_a} - \epsilon '_{m_a} {\lt} 0\).

Proof

This is a direct calculation.

Theorem 11.4.1 Ramanujan’s inequality

For \(x \geq e x_a\) we have \(\pi (x)^2 {\lt} \frac{e x}{\log x} \pi \Big(\frac{x}{e}\Big)\).

Proof

[ 23 , Theorem 2 ] This follows from the previous lemmas and calculations, including the criterion for Ramanujan’s inequality.