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An inequality related to
the sieve of Eratosthenes

Kai (Steve) Fan Mathematics Department, Dartmouth College, Hanover, NH 03755 [email protected]  and  Carl Pomerance Mathematics Department, Dartmouth College, Hanover, NH 03755 [email protected]
Abstract.

Let Φ(x,y)\Phi(x,y) denote the number of integers n[1,x]n\in[1,x] free of prime factors y\leq y. We show that but for a few small cases, Φ(x,y)<.6x/logy\Phi(x,y)<.6x/\log y when yxy\leq\sqrt{x}.

Key words and phrases:
Buchstab’s function, Selberg’s sieve
2010 Mathematics Subject Classification:
11N25

1. Introduction

The sieve of Eratosthenes removes the multiples of the primes pyp\leq y from the set of positive integers nxn\leq x. Let Φ(x,y)\Phi(x,y) denote the number of integers remaining. Answering a question of Ford, the first-named author [7] recently proved the following theorem.

Theorem A. When 2yx2\leq y\leq x, Φ(x,y)<x/logy\Phi(x,y)<x/\log y.

If y>xy>\sqrt{x}, then Φ(x,y)=π(x)π(y)+1\Phi(x,y)=\pi(x)-\pi(y)+1 (where π(t)\pi(t) is the number of primes in [1,t][1,t]), and so by the prime number theorem, Theorem A is essentially best possible when x1ϵ<y<ϵxx^{1-\epsilon}<y<\epsilon x. When yxy\leq\sqrt{x}, there is a long history in estimating Φ(x,y)\Phi(x,y), and in particular, we have the following theorem, essentially due to Buchstab (see [13, Theorem III.6.4]).

Theorem B. For ω(u)\omega(u) the Buchstab function and u=logx/logy2u=\log x/\log y\geq 2 and y2y\geq 2,

Φ(x,y)=xlogy(ω(u)+O(1logy)).\Phi(x,y)=\frac{x}{\log y}\left(\omega(u)+O\left(\frac{1}{\log y}\right)\right).

The Buchstab function ω(u)\omega(u) is defined as the unique continuous function on [1,)[1,\infty) such that

uω(u)=1 on [1,2],(uω(u))=ω(u1) on (2,).u\omega(u)=1\hbox{ on }[1,2],\quad(u\omega(u))^{\prime}=\omega(u-1)\hbox{ on }(2,\infty).

Below is a graph of ω(u)\omega(u) for u[1,8]u\in[1,8] generated by Mathematica.

[Uncaptioned image]

It is known that limuω(u)=eγ=0.561459483566885\lim_{u\to\infty}\omega(u)=e^{-\gamma}=0.561459483566885\dots and that ω(u)\omega(u) oscillates above and below its limiting value infinitely often. The minimum value of ω(u)\omega(u) on [2,)[2,\infty) is 1/21/2 at u=2u=2 and the maximum value M0M_{0} is 0.5671432904097830.567143290409783\dots, occurring at u=2.76322283417162u=2.76322283417162\dots. In particular, it follows from Theorem B that if c>M0c>M_{0} and yxy\leq\sqrt{x} with yy sufficiently large depending on the choice of cc, that Φ(x,y)<cx/logy\Phi(x,y)<cx/\log y. In addition, using an inclusion–exclusion argument plus the fact that the Mertens product py(11/p)<M0/logy\prod_{p\leq y}(1-1/p)<M_{0}/\log y for all y2y\geq 2, the inequality Φ(x,y)<cx/logy\Phi(x,y)<cx/\log y can be extended to all 2yx2\leq y\leq\sqrt{x}, but now with xx sufficiently large depending on cc.

In light of Theorem A and given that Φ(x,y)\Phi(x,y) is a fundamental (and ancient) function, it seems interesting to try and make these consequences of Theorem B numerically explicit. We prove the following theorem.

Theorem 1.

For 3yx3\leq y\leq\sqrt{x}, we have Φ(x,y)<.6x/logy\Phi(x,y)<.6x/\log y. The same inequality holds when 2yx2\leq y\leq\sqrt{x} and x10x\geq 10.

To prove this we use some numerically explicit estimates of primes due to Rosser–Schoenfeld, Büthe, and others. In addition we use a numerically explicit version of the upper bound in Selberg’s sieve.

Theorem B itself is also appealing. It provides a simple asymptotic formula for Φ(x,y)\Phi(x,y) as yy\to\infty which is applicable in a wide range. Writing

Φ(x,y)=xlogy(ω(u)+Δ(x,y)logy),\Phi(x,y)=\frac{x}{\log y}\left(\omega(u)+\frac{\Delta(x,y)}{\log y}\right),

one may attempt to establish numerically explicit lower and upper bounds for Δ(x,y)\Delta(x,y) in the range yxy\leq\sqrt{x} for suitably large yy0y\geq y_{0}, where y02y_{0}\geq 2 is some numerically computable constant. More precisely, de Bruijn [3] essentially showed that for any given ϵ>0\epsilon>0, one has

Φ(x,y)=μy(u)eγxlogypy(11p)+O(xexp((logy)3/5ϵ))\Phi(x,y)=\mu_{y}(u)e^{\gamma}x\log y\prod_{p\leq y}\left(1-\frac{1}{p}\right)+O(x\exp(-(\log y)^{3/5-\epsilon}))

for all xy2x\geq y\geq 2, where

μy(u)\colonequals0u1ω(uv)yv𝑑v.\mu_{y}(u)\colonequals\int_{0}^{u-1}\omega(u-v)y^{-v}\,dv.

Recently, the first-named author [8] proved numerically explicit versions of this result applicable for yy in wide ranges.

2. A prime lemma

Let π(x)\pi(x) denote, as usual, the number of primes pxp\leq x. Let

li(x)=0xdtlogt,{\rm li}(x)=\int_{0}^{x}\frac{dt}{\log t},

where the principal value is taken for the singularity at t=1t=1. There is a long history in trying to find the first point when π(x)li(x)\pi(x)\geq{\rm li}(x), which we now know is beyond 101910^{19}. We prove a lemma based on this research.

Lemma 1.

Let β0=2.3×108\beta_{0}=2.3\times 10^{-8}. For x2x\geq 2, we have π(x)<(1+β0)li(x)\pi(x)<(1+\beta_{0}){\rm li}(x).

Proof.

The result is true for x10x\leq 10, so assume x10x\geq 10. Consider the Chebyshev function

θ(x)=pxlogp.\theta(x)=\sum_{p\leq x}\log p.

We use [10, Prop. 2.1], which depends strongly on extensive calculations of Büthe [4, 5] and Platt [11]. This result asserts in part that θ(x)x.05x\theta(x)\leq x-.05\sqrt{x} for 1427x10191427\leq x\leq 10^{19} and for larger xx, θ(x)<(1+β0)x\theta(x)<(1+\beta_{0})x. One easily checks that θ(x)<x\theta(x)<x for x<1427x<1427, so we have

θ(x)<(1+β0)x,x>0.\theta(x)<(1+\beta_{0})x,\quad x>0.

By partial summation, we have

π(x)\displaystyle\pi(x) =θ(x)logx+2xθ(t)t(logt)2𝑑t\displaystyle=\frac{\theta(x)}{\log x}+\int_{2}^{x}\frac{\theta(t)}{t(\log t)^{2}}\,dt
<(1+β0)xlogx+210θ(t)t(logt)2𝑑t+(1+β0)10xdt(logt)2.\displaystyle<\frac{(1+\beta_{0})x}{\log x}+\int_{2}^{10}\frac{\theta(t)}{t(\log t)^{2}}\,dt+(1+\beta_{0})\int_{10}^{x}\frac{dt}{(\log t)^{2}}.

Since 𝑑t/(logt)2=t/logt+li(t)\int dt/(\log t)^{2}=-t/\log t+{\rm li}(t), we have

π(x)\displaystyle\pi(x) <(1+β0)li(x)+210θ(t)t(logt)2𝑑t+(1+β0)(10/log10li(10))\displaystyle<(1+\beta_{0}){\rm li}(x)+\int_{2}^{10}\frac{\theta(t)}{t(\log t)^{2}}\,dt+(1+\beta_{0})(10/\log 10-{\rm li}(10))
(1) <(1+β0)li(x).144.\displaystyle<(1+\beta_{0}){\rm li}(x)-.144.

This gives the lemma. ∎

After checking for x10x\leq 10, we remark that an immediate corollary of (2) is the inequality

(2) π(x)k<(1+β0)(li(x)k),2kπ(x),k107.\pi(x)-k<(1+\beta_{0})({\rm li}(x)-k),\quad 2\leq k\leq\pi(x),~{}k\leq 10^{7}.

3. Inclusion–exclusion

For small values of y2y\geq 2 we can do a complete inclusion–exclusion to compute Φ(x,y)\Phi(x,y). Let P(y)P(y) denote the product of the primes pyp\leq y. We have

(3) Φ(x,y)=dP(y)μ(d)xd.\Phi(x,y)=\sum_{d\mid P(y)}\mu(d)\left\lfloor\frac{x}{d}\right\rfloor.

As a consequence, we have

(4) Φ(x,y)dP(y)μ(d)xd+dP(y)μ(d)=11=xpy(11p)+2π(y)1.\Phi(x,y)\leq\sum_{d\mid P(y)}\mu(d)\frac{x}{d}+\sum_{\begin{subarray}{c}d\mid P(y)\\ \mu(d)=1\end{subarray}}1=x\prod_{p\leq y}\left(1-\frac{1}{p}\right)+2^{\pi(y)-1}.

We illustrate how this elementary inequality can be used in the case when π(y)=5\pi(y)=5, that is, 11y<1311\leq y<13. Then the product in (4) is 16/77<.20779316/77<.207793. The remainder term in (4) is 16. And we have

Φ(x,y)<.207793x+16<.6x/log13\Phi(x,y)<.207793x+16<.6x/\log 13

when x613x\geq 613. There remains the problem of dealing with smaller values of xx, which we address momentarily. We apply this method for y<71y<71.

Table 1. Small yy.
yy interval xx bound max
[2,3)[2,3) 22 .61035
[3,5)[3,5) 51 .57940
[5,7)[5,7) 96 .55598
[7,11)[7,11) 370 .56634
[11,13)[11,13) 613 .55424
[13,17)[13,17) 1603 .56085
[17,19)[17,19) 2753 .54854
[19,23)[19,23) 6296 .55124
[23,29)[23,29) 17539 .55806
[29,31)[29,31) 30519 .55253
[31,37)[31,37) 76932 .55707
[37,41)[37,41) 1.6×1051.6\times 10^{5} .55955
[41,43)[41,43) 2.9×1052.9\times 10^{5} .55648
[43,47)[43,47) 5.9×1055.9\times 10^{5} .55369
[47,53)[47,53) 1.4×1061.4\times 10^{6} .55972
[53,59)[53,59) 3.0×1063.0\times 10^{6} .55650
[59,61)[59,61) 5.4×1065.4\times 10^{6} .55743
[61,67)[61,67) 1.2×1071.2\times 10^{7} .55685
[67,71)[67,71) 2.4×1072.4\times 10^{7} .55641

Pertaining to Table 1, for xx beyond the “xx bound” and yy in the given interval, we have Φ(x,y)<.6x/logy\Phi(x,y)<.6x/\log y. The column “max” in Table 1 is the supremum of Φ(x,y)/(x/logy)\Phi(x,y)/(x/\log y) for yy in the given interval and xy2x\geq y^{2} with xx below the xx bound. The max statistic was computed by creating a table of the integers up to the xx bound with a prime factor y\leq y, taking the complement of this set in the set of all integers up to the xx bound, and then computing (jlogp)/n(j\log p)/n where nn is the jjth member of the set and pp is the upper bound of the yy interval. The max of these numbers is recorded as the max statistic.

As one can see, for y3y\geq 3 the max statistic in Table 1 is below .6.6. However, for the interval [2,3)[2,3) it is above .6.6. One can compute that it is <.6<.6 once x10x\geq 10.

This method can be extended to larger values of yy, but the xx bound becomes prohibitively large. With a goal of keeping the xx bound smaller than 3×1073\times 10^{7}, we can extend a version of inclusion-exclusion to y<241y<241 as follows.

First, we “pre-sieve” with the primes 2, 3, and 5. For any x0x\geq 0 the number of integers nxn\leq x with gcd(n,30)=1\gcd(n,30)=1 is (4/15)x+r(4/15)x+r, where |r|14/15|r|\leq 14/15, as can be easily verified by looking at values of x[0,30]x\in[0,30]. We change the definition of P(y)P(y) to be the product of the primes in (5,y](5,y]. Then for y5y\geq 5, we have

Φ(x,y)415dP(y)μ(d)xd+14152π(y)3.\Phi(x,y)\leq\frac{4}{15}\sum_{d\mid P(y)}\mu(d)\frac{x}{d}+\frac{14}{15}2^{\pi(y)-3}.

However, it is better to use the Bonferroni inequalities in the form

Φ(x,y)415j4dP(y)ν(d)=j(1)jxd+i=04(π(y)3i)=xs(y)+b(y),\Phi(x,y)\leq\frac{4}{15}\sum_{j\leq 4}\sum_{\begin{subarray}{c}d\mid P(y)\\ \nu(d)=j\end{subarray}}(-1)^{j}\frac{x}{d}+\sum_{i=0}^{4}\binom{\pi(y)-3}{i}=xs(y)+b(y),

say, where ν(d)\nu(d) is the number of distinct prime factors of dd. (We remark that the expression b(y)b(y) could be replaced with 1415b(y)\frac{14}{15}b(y).) The inner sums in s(y)s(y) can be computed easily using Newton’s identities, and we see that

Φ(x,y).6x/logy for x>b(y)/(.6/logys(y)).\Phi(x,y)\leq.6x/\log y\hbox{ for }x>b(y)/(.6/\log y-s(y)).

We have verified that this xx bound is smaller than 30,000,00030{,}000{,}000 for y<241y<241 and we have verified that Φ(x,y)<.6x/logy\Phi(x,y)<.6x/\log y for xx up to this bound and y<241y<241.

This completes the proof of Theorem 1 for y<241y<241.

4. When uu is large: Selberg’s sieve

In this section we prove Theorem 1 in the case that u=logx/logy7.5u=\log x/\log y\geq 7.5 and y241y\geq 241. Our principal tool is a numerically explicit form of Selberg’s sieve.

Let 𝒜\mathcal{A} be a set of positive integers axa\leq x and with |𝒜|X|\mathcal{A}|\approx X. Let 𝒫=𝒫(y)\mathcal{P}=\mathcal{P}(y) be a set of primes pyp\leq y. For each p𝒫p\in\mathcal{P} we have a collection of α(p)\alpha(p) residue classes mod pp, where α(p)<p\alpha(p)<p. Let P=P(y)P=P(y) denote the product of the members of 𝒫\mathcal{P}. Let gg be the multiplicative function defined for numbers dPd\mid P where g(p)=α(p)/pg(p)=\alpha(p)/p when p𝒫p\in\mathcal{P}. We let

V:=p𝒫(1g(p))=p𝒫(1α(p)p).V:=\prod_{p\in\mathcal{P}}(1-g(p))=\prod_{p\in\mathcal{P}}\left(1-\frac{\alpha(p)}{p}\right).

We define rd(𝒜)r_{d}(\mathcal{A}) via the equation

a𝒜da1=g(d)X+rd(𝒜).\sum_{\begin{subarray}{c}a\in\mathcal{A}\\ d\mid a\end{subarray}}1=g(d)X+r_{d}(\mathcal{A}).

The thought is that rd(𝒜)r_{d}(\mathcal{A}) should be small. We are interested in S(𝒜,𝒫)S(\mathcal{A},\mathcal{P}), the number of those a𝒜a\in\mathcal{A} such that aa is coprime to PP.

We will use Selberg’s sieve as given in [9, Theorem 7.1]. This involves an auxiliary parameter D<XD<X which can be freely chosen. Let hh be the multiplicative function supported on divisors of PP such that h(p)=g(p)/(1g(p))h(p)=g(p)/(1-g(p)). In particular if each α(p)=1\alpha(p)=1, then each g(p)=1/pg(p)=1/p and h(p)=1/(p1)h(p)=1/(p-1), so h(d)=1/φ(d)h(d)=1/\varphi(d) for dPd\mid P, where φ\varphi is Euler’s function. Henceforth we will make this assumption (that each α(p)=1\alpha(p)=1). Let

J=JD=dPd<Dh(d),R=RD=dPd<Dτ3(d)|rd(𝒜)|,J=J_{D}=\sum_{\begin{subarray}{c}d\mid P\\ d<\sqrt{D}\end{subarray}}h(d),\quad R=R_{D}=\sum_{\begin{subarray}{c}d\mid P\\ d<D\end{subarray}}\tau_{3}(d)|r_{d}(\mathcal{A})|,

where τ3(d)\tau_{3}(d) is the number of ordered factorizations d=abcd=abc, where a,b,ca,b,c are positive integers. Selberg’s sieve gives in this situation that

(5) S(𝒜,𝒫)X/J+R.S(\mathcal{A},\mathcal{P})\leq X/J+R.

Note that if DP2D\geq P^{2}, then

J=dPh(d)=p𝒫(1+h(p))=p𝒫(1g(p))1=V1,J=\sum_{d\mid P}h(d)=\prod_{p\in\mathcal{P}}(1+h(p))=\prod_{p\in\mathcal{P}}(1-g(p))^{-1}=V^{-1},

so that X/J=XVX/J=XV. This is terrific, but if DD is so large, the remainder term RR in (5) is also large, making the estimate useless. So, the trick is to choose DD judiciously so that RR is under control with JJ being near to V1V^{-1}.

Consider the case when each |rd(𝒜)|r|r_{d}(\mathcal{A})|\leq r, for a constant rr. In this situation the following lemma is useful.

Lemma 2.

For y241y\geq 241, we have

Rrd<DdP(y)τ3(d)rD(logy)2pyp𝒫(1+2p)1.R\leq r\sum_{\begin{subarray}{c}d<D\\ d\mid P(y)\end{subarray}}\tau_{3}(d)\leq rD(\log y)^{2}\prod_{\begin{subarray}{c}p\leq y\\ p\notin\mathcal{P}\end{subarray}}\left(1+\frac{2}{p}\right)^{-1}.
Proof.

Let τ(d)=τ2(d)\tau(d)=\tau_{2}(d) denote the number of positive divisors of dd. Note that

dP(y)τ(d)d=p𝒫(1+2p)=py(1+2p)pyp𝒫(1+2p)1.\sum_{d\mid P(y)}\frac{\tau(d)}{d}=\prod_{p\in\mathcal{P}}\left(1+\frac{2}{p}\right)=\prod_{p\leq y}\left(1+\frac{2}{p}\right)\prod_{\begin{subarray}{c}p\leq y\\ p\notin\mathcal{P}\end{subarray}}\left(1+\frac{2}{p}\right)^{-1}.

One can show that for y241y\geq 241 the first product on the right is smaller than .95(logy)2.95(\log y)^{2}, but we will only use the “cleaner” bound (logy)2(\log y)^{2} (which holds when y53y\geq 53). Thus,

d<DdP(y)τ3(d)\displaystyle\sum_{\begin{subarray}{c}d<D\\ d\mid P(y)\end{subarray}}\tau_{3}(d) =d<DdP(y)jdτ(j)j<DjP(y)τ(j)d<D/jdP(y)1\displaystyle=\sum_{\begin{subarray}{c}d<D\\ d\mid P(y)\end{subarray}}\sum_{j\mid d}\tau(j)\leq\sum_{\begin{subarray}{c}j<D\\ j\mid P(y)\end{subarray}}\tau(j)\sum_{\begin{subarray}{c}d<D/j\\ d\mid P(y)\end{subarray}}1
<Dj<DjP(y)τ(j)j<D(logy)2pyp𝒫(1+2p)1.\displaystyle<D\sum_{\begin{subarray}{c}j<D\\ j\mid P(y)\end{subarray}}\frac{\tau(j)}{j}<D(\log y)^{2}\prod_{\begin{subarray}{c}p\leq y\\ p\notin\mathcal{P}\end{subarray}}\left(1+\frac{2}{p}\right)^{-1}.

This completes the proof. ∎

To get a lower bound for JJ in (5) we proceed as in [9, Section 7.4]. Recall that we are assuming each α(p)=1\alpha(p)=1 and so h(d)=1/φ(d)h(d)=1/\varphi(d) for dPd\mid P.

Let

I=dDdP1φ(d),I=\sum_{\begin{subarray}{c}d\geq\sqrt{D}\\ d\mid P\end{subarray}}\frac{1}{\varphi(d)},

so that I+J=V1I+J=V^{-1}. Hence

(6) J=V1I=V1(1IV),J=V^{-1}-I=V^{-1}(1-IV),

so we want an upper bound for IVIV. Let ε\varepsilon be arbitrary with ε>0\varepsilon>0. We have

I<DεdPd2εφ(d)=Dεpy(1+p2εp1),I<D^{-\varepsilon}\sum_{d\mid P}\frac{d^{2\varepsilon}}{\varphi(d)}=D^{-\varepsilon}\prod_{p\leq y}\left(1+\frac{p^{2\varepsilon}}{p-1}\right),

and so, assuming each α(p)=1\alpha(p)=1,

(7) IV<Dεp𝒫(1+p2ε1p)=:f(D,𝒫,ε).IV<D^{-\varepsilon}\prod_{p\in\mathcal{P}}\left(1+\frac{p^{2\varepsilon}-1}{p}\right)=:f(D,\mathcal{P},\varepsilon).

In particular, if y241y\geq 241 and each rd(𝒜)rr_{d}(\mathcal{A})\leq r, then

(8) S(𝒜,𝒫)XV(1f(D,𝒫,ε))1+rD(logy)2pyp𝒫(1+2p)1.S(\mathcal{A},\mathcal{P})\leq XV\big{(}1-f(D,\mathcal{P},\varepsilon)\big{)}^{-1}+rD(\log y)^{2}\prod_{\begin{subarray}{c}p\leq y\\ p\notin\mathcal{P}\end{subarray}}\left(1+\frac{2}{p}\right)^{-1}.

We shall choose DD so that the remainder term is small in comparison to XVXV, and once DD is chosen, we shall choose ε\varepsilon so as to minimize f(D,𝒫,ε)f(D,\mathcal{P},\varepsilon).

4.1. The case when y500,000y\leq 500{,}000 and u7.5u\geq 7.5.

We wish to apply (8) to estimate Φ(x,y)\Phi(x,y) when u7.5u\geq 7.5, that is, when xy7.5x\geq y^{7.5}. We have a few choices for 𝒜\mathcal{A} and 𝒫\mathcal{P}. The most natural choice is that 𝒜\mathcal{A} is the set of all integers x\leq x, X=xX=x, and 𝒫\mathcal{P} is the set of all primes y\leq y. In this case, each rd(𝒜)1r_{d}(\mathcal{A})\leq 1, so that we can take r=1r=1 in (8) (since rd(𝒜)0r_{d}(\mathcal{A})\geq 0 in this case). Instead we choose (as in the last section) 𝒜\mathcal{A} as the set of all integers x\leq x that are coprime to 30 and we choose 𝒫\mathcal{P} as the set of primes pp with 7py7\leq p\leq y. Then X=4x/15X=4x/15 and one can check that each |rd(𝒜)|14/15|r_{d}(\mathcal{A})|\leq 14/15, so we can take r=14/15r=14/15 in (8). Also,

pyp𝒫(1+2p)1=314,\prod_{\begin{subarray}{c}p\leq y\\ p\notin\mathcal{P}\end{subarray}}\left(1+\frac{2}{p}\right)^{-1}=\frac{3}{14},

when y5y\geq 5. With this choice of 𝒜\mathcal{A} and 𝒫\mathcal{P}, (8) becomes

(9) Φ(x,y)XV(1Dε7py(1+p2ε1p))1+15D(logy)2,\Phi(x,y)\leq XV\left(1-D^{-\varepsilon}\prod_{7\leq p\leq y}\left(1+\frac{p^{2\varepsilon}-1}{p}\right)\right)^{-1}+\frac{1}{5}D(\log y)^{2},

when y241y\geq 241.

Our “target” for Φ(x,y)\Phi(x,y) is .6x/logy.6x/\log y. We choose DD here so that our estimate for the remainder term is 1% of the target, namely .006x/logy.006x/\log y. Thus, in light of Lemma 2, we choose

D=.03x/(logy)3.D=.03x/(\log y)^{3}.

We have verified that for every value of y500,000y\leq 500{,}000 and xy7.5x\geq y^{7.5} that the right side of (9) is smaller than .6x/logy.6x/\log y. Note that to verify this, if p,qp,q are consecutive primes with 241p<q241\leq p<q, then S(𝒜,𝒫)S(\mathcal{A},\mathcal{P}) is constant for py<qp\leq y<q, and so it suffices to show the right side of (9) is smaller than .6x/logq.6x/\log q. Further, it suffices to take x=p7.5x=p^{7.5}, since as xx increases beyond this point with 𝒫\mathcal{P} and ε\varepsilon fixed, the expression f(D,𝒫,ε)f(D,\mathcal{P},\varepsilon) decreases. For smaller values of yy in the range, we used Mathematica to choose the optimal choice of ε\varepsilon. For larger values, we let ε\varepsilon be a judicious constant over a long interval. As an example, we chose ε=.085\varepsilon=.085 in the top half of the range.

4.2. When y500,000y\geq 500{,}000 and u7.5u\geq 7.5.

As in the discussion above we have a few choices to make, namely for the quantities DD and ε\varepsilon. First, we choose x=y7.5x=y^{7.5}, since the case xy7.5x\geq y^{7.5} follows from the proof of the case of equality. We choose DD as before, namely .03x/(logy)3.03x/(\log y)^{3}. We also choose

ε=1/logy.\varepsilon=1/\log y.

Our goal is to prove a small upper bound for f(D,𝒫,ε)f(D,\mathcal{P},\varepsilon) given in (7). We have

f(D,𝒫,ε)<Dεexp(7pyp2ε1p).f(D,\mathcal{P},\varepsilon)<D^{-\varepsilon}\exp\left(\sum_{7\leq p\leq y}\frac{p^{2\varepsilon}-1}{p}\right).

We treat the two sums separately. First, by Rosser–Schoenfeld [12, Theorems 9, 20], one can show that

py1p<loglogy.26-\sum_{p\leq y}\frac{1}{p}<-\log\log y-.26

for all y2y\geq 2, so that

(10) 7py1p<loglogy.26+31/30-\sum_{7\leq p\leq y}\frac{1}{p}<-\log\log y-.26+31/30

for y7y\geq 7. For the second sum we have

7pyp2ε1=72ε1+(π(y)4)y2ε1+11y(12ε)(π(t)4)t2ε2𝑑t.\sum_{7\leq p\leq y}p^{2\varepsilon-1}=7^{2\varepsilon-1}+(\pi(y)-4)y^{2\varepsilon-1}+\int_{11}^{y}(1-2\varepsilon)(\pi(t)-4)t^{2\varepsilon-2}\,dt.

At this point we use (2) , so that

11+β0\displaystyle\frac{1}{1+\beta_{0}} 11pyp2ε1<(li(y)4)y2ε1+11y(12ε)(li(t)4)t2ε2𝑑t\displaystyle\sum_{11\leq p\leq y}p^{2\varepsilon-1}<({\rm li}(y)-4)y^{2\varepsilon-1}+\int_{11}^{y}(1-2\varepsilon)({\rm li}(t)-4)t^{2\varepsilon-2}\,dt
=(li(y)4)y2ε1(li(t)4)t2ε1|11y+11yt2ε1logt𝑑t\displaystyle=({\rm li}(y)-4)y^{2\varepsilon-1}-({\rm li}(t)-4)t^{2\varepsilon-1}\Big{|}_{11}^{y}+\int_{11}^{y}\frac{t^{2\varepsilon-1}}{\log t}\,dt
=(li(11)4)112ε1+li(t2ε)|11y\displaystyle=({\rm li}(11)-4)11^{2\varepsilon-1}+{\rm li}(t^{2\varepsilon})\Big{|}_{11}^{y}
=(li(11)4)112ε1+li(y2ε)li(112ε),\displaystyle=({\rm li}(11)-4)11^{2\varepsilon-1}+{\rm li}(y^{2\varepsilon})-{\rm li}(11^{2\varepsilon}),

and so

(11) 11+β07pyp2ε1<72ε1+(li(11)4)112ε1+li(y2ε)li(112ε).\displaystyle\frac{1}{1+\beta_{0}}\sum_{7\leq p\leq y}p^{2\varepsilon-1}<7^{2\varepsilon-1}+({\rm li}(11)-4)11^{2\varepsilon-1}+{\rm li}(y^{2\varepsilon})-{\rm li}(11^{2\varepsilon}).

There are a few things to notice, but we will not need them. For example, li(y2ε)=li(e2){\rm li}(y^{2\varepsilon})={\rm li}(e^{2}) and li(112ε)log(112ε1)+γ{\rm li}(11^{2\varepsilon})\approx\log(11^{2\varepsilon}-1)+\gamma.

Let S(y)S(y) be the sum of the right side of (10) and 1+β01+\beta_{0} times the right side of (11). Then

f(D,𝒫,ε)<DεeS(y).f(D,\mathcal{P},\varepsilon)<D^{-\varepsilon}e^{S(y)}.

The expression XVXV in (9) is

xpy(11p).x\prod_{p\leq y}\left(1-\frac{1}{p}\right).

We know from [10] that this product is <eγ/logy<e^{-\gamma}/\log y for y2×109y\leq 2\times 10^{9}, and for larger values of yy, it follows from [6, Theorem 5.9] (which proof follows from [6, Theorem 4.2] or [2, Corollary 11.2]) that it is <(1+2.1×105)eγ/logy<(1+2.1\times 10^{-5})e^{-\gamma}/\log y. We have

(12) Φ(x,y)\displaystyle\Phi(x,y) XV(1f(D,𝒫,ε))1+15D(logy)2\displaystyle\leq XV\big{(}1-f(D,\mathcal{P},\varepsilon)\big{)}^{-1}+\frac{1}{5}D(\log y)^{2}
<(1+2.1×105)xeγlogy(1DεeS(y))1+.006xlogy.\displaystyle<(1+2.1\times 10^{-5})\frac{x}{e^{\gamma}\log y}\big{(}1-D^{-\varepsilon}e^{S(y)}\big{)}^{-1}+\frac{.006x}{\log y}.

We have verified that (1DεeS(y))1(1-D^{-\varepsilon}e^{S(y)})^{-1} is decreasing in yy, and that at y=500,000y=500{,}000 it is smaller than 1.0571.057. Thus, (12) implies that

Φ(x,y)<(1+2.1×105)1.057xeγlogy+.006xlogy<.5995xlogy.\Phi(x,y)<(1+2.1\times 10^{-5})\frac{1.057x}{e^{\gamma}\log y}+\frac{.006x}{\log y}<\frac{.5995x}{\log y}.

This concludes the case of u7.5u\geq 7.5.

5. Small uu

In this section we prove that Φ(x,y)<.57163x/logy\Phi(x,y)<.57163x/\log y when u[2,3)u\in[2,3), that is, when y2x<y3y^{2}\leq x<y^{3}.

For small values of yy, we calculate the maximum of Φ(x,y)/(x/logy)\Phi(x,y)/(x/\log y) for y2x<y3y^{2}\leq x<y^{3} directly, as we did in Section 3 when we checked below the xx bounds in Table 1 and the bound 3×1073\times 10^{7}. We have done this for 241y1100241\leq y\leq 1100, and in this range we have

Φ(x,y)<.56404xlogy,y2x<y3,241y1100.\Phi(x,y)<.56404\frac{x}{\log y},\quad y^{2}\leq x<y^{3},\quad 241\leq y\leq 1100.

Suppose now that y>1100y>1100 and y2x<y3y^{2}\leq x<y^{3}. We have

(13) Φ(x,y)=π(x)π(y)+1+y<px1/2(π(x/p)π(p)+1).\Phi(x,y)=\pi(x)-\pi(y)+1+\sum_{y<p\leq x^{1/2}}(\pi(x/p)-\pi(p)+1).

Indeed, if nn is counted by Φ(x,y)\Phi(x,y), then nn has at most 2 prime factors (counted with multiplicity), so n=1n=1, nn is a prime in (y,x](y,x] or n=pqn=pq, where p,qp,q are primes with y<pqx/py<p\leq q\leq x/p.

Let pjp_{j} denote the jjth prime. Note that

ptπ(p)=jπ(t)j=12π(t)2+12π(t).\sum_{p\leq t}\pi(p)=\sum_{j\leq\pi(t)}j=\frac{1}{2}\pi(t)^{2}+\frac{1}{2}\pi(t).

Thus,

y<px1/2(π(p)1)=12π(x1/2)212π(x1/2)12π(y)2+12π(y),\sum_{y<p\leq x^{1/2}}(\pi(p)-1)=\frac{1}{2}\pi(x^{1/2})^{2}-\frac{1}{2}\pi(x^{1/2})-\frac{1}{2}\pi(y)^{2}+\frac{1}{2}\pi(y),

and so

(14) Φ(x,y)=π(x)M(x,y)+y<px1/2π(x/p),\Phi(x,y)=\pi(x)-M(x,y)+\sum_{y<p\leq x^{1/2}}\pi(x/p),

where

M(x,y)=12π(x1/2)212π(x1/2)12π(y)2+32π(y)1.M(x,y)=\frac{1}{2}\pi(x^{1/2})^{2}-\frac{1}{2}\pi(x^{1/2})-\frac{1}{2}\pi(y)^{2}+\frac{3}{2}\pi(y)-1.

We use Lemma 1 on various terms in (14). In particular, we have (assuming y5y\geq 5)

(15) Φ(x,y)<(1+β0)li(x)+y<px1/2(1+β0)li(x/p)M(x,y).\Phi(x,y)<(1+\beta_{0}){\rm li}(x)+\sum_{y<p\leq x^{1/2}}(1+\beta_{0}){\rm li}(x/p)-M(x,y).

Via partial summation, we have

(16) y<px1/2li(x/p)=x1/2li(x1/2)y<px1/21pyx1/2(li(x/t)x/tlog(x/t))y<pt1pdt.\begin{split}\sum_{y<p\leq x^{1/2}}{\rm li}(x/p)=&~{}x^{1/2}{\rm li}(x^{1/2})\sum_{y<p\leq x^{1/2}}\frac{1}{p}\\ &~{}~{}-\int_{y}^{x^{1/2}}\left({\rm li}(x/t)-\frac{x/t}{\log(x/t)}\right)\sum_{y<p\leq t}\frac{1}{p}\,dt.\end{split}

For 1100t1041100\leq t\leq 10^{4} we have checked numerically that

0<pt1ploglogtB<.00624,0<\sum_{p\leq t}\frac{1}{p}-\log\log t-B<.00624,

where B=.261497B=.261497\dots is the Meissel–Mertens constant. Further, for 104t10610^{4}\leq t\leq 10^{6},

0<pt1ploglogtB<.00161.0<\sum_{p\leq t}\frac{1}{p}-\log\log t-B<.00161.

(The lower bounds here follow as well from [12, Theorem 20].) It thus follows for 1100y1041100\leq y\leq 10^{4} that

(17) y<px1/21p<loglog(x1/2)logy+β1,y<pt1p>loglogtlogyβ1,\sum_{y<p\leq x^{1/2}}\frac{1}{p}<\log\frac{\log(x^{1/2})}{\log y}+\beta_{1},\quad\sum_{y<p\leq t}\frac{1}{p}>\log\frac{\log t}{\log y}-\beta_{1},

where β1=.00624\beta_{1}=.00624. Now suppose that y104y\geq 10^{4}. Using [6, Eq. (5.7)] and the value 4.4916 for “η3\eta_{3}” from [2, Table 15], we have that

|pt1ploglogtB|<1.9036/(logt)3,t106.\Big{|}\sum_{p\leq t}\frac{1}{p}-\log\log t-B\Big{|}<1.9036/(\log t)^{3},~{}~{}t\geq 10^{6}.

Thus, (17) continues to hold for y104y\geq 10^{4} with .00624 improved to .00322. We thus have from (16)

(18) y<px1/2li(x/p)<x1/2li(x1/2)(loglog(x1/2)logy+β1)yx1/2(li(x/t)x/tlog(x/t))(loglogtlogyβ1)𝑑t.\begin{split}\sum_{y<p\leq x^{1/2}}{\rm li}(x/p)<&~{}x^{1/2}{\rm li}(x^{1/2})\left(\log\frac{\log(x^{1/2})}{\log y}+\beta_{1}\right)\\ &~{}~{}-\int_{y}^{x^{1/2}}\left({\rm li}(x/t)-\frac{x/t}{\log(x/t)}\right)\left(\log\frac{\log t}{\log y}-\beta_{1}\right)\,dt.\end{split}

Let R(t)=(1+β0)li(t)/(t/logt)R(t)=(1+\beta_{0}){\rm li}(t)/(t/\log t), so that R(t)1+β0R(t)\to 1+\beta_{0} as tt\to\infty. We write the first term on the right side of (15) as

xulogyR(x)=R(yu)uxlogy,\frac{x}{u\log y}R(x)=\frac{R(y^{u})}{u}\frac{x}{\log y},

and note that the first term on the right of (18) is less than

R(yu/2)2u(log(u/2)+β1)xlogy.R(y^{u/2})\frac{2}{u}(\log(u/2)+\beta_{1})\frac{x}{\log y}.

For the expression 12π(x1/2)212π(x1/2)\frac{1}{2}\pi(x^{1/2})^{2}-\frac{1}{2}\pi(x^{1/2}) in M(x,y)M(x,y) we use the inequality π(t)>t/logt+t/(logt)2\pi(t)>t/\log t+t/(\log t)^{2} when t599t\geq 599, which follows from [1, Lemma 3.4] and a calculation (also see [6, Corollary 5.2]). Further, we use π(y)R(y)y/logy\pi(y)\leq R(y)y/\log y for the rest of M(x,y)M(x,y).

Using these estimates and numerical integration for the integral in (18) we find that

Φ(x,y)<.57163xlogy,y1100,y2x<y3.\Phi(x,y)<.57163\frac{x}{\log y},\quad y\geq 1100,\quad y^{2}\leq x<y^{3}.

6. Iteration

Suppose kk is a positive integer and we have shown that

(19) Φ(x,y)ckxlogy\Phi(x,y)\leq c_{k}\frac{x}{\log y}

for all y241y\geq 241 and u=logx/logy[2,k)u=\log x/\log y\in[2,k). We can try to find some ck+1c_{k+1} not much larger than ckc_{k} such that

Φ(x,y)ck+1xlogy\Phi(x,y)\leq c_{k+1}\frac{x}{\log y}

for y241y\geq 241 and u<k+1u<k+1. We start with c3c_{3}, which by the results of the previous section we can take as .57163. In this section we attempt to find ckc_{k} for k8k\leq 8 such that c8<.6c_{8}<.6. It would then follow from Section 4 that Φ(x,y)<.6x/logy\Phi(x,y)<.6x/\log y for all u2u\geq 2 and y241y\geq 241.

Suppose that (19) holds and that yy is such that x1/(k+1)<yx1/kx^{1/(k+1)}<y\leq x^{1/k}. We have

(20) Φ(x,y)=Φ(x,x1/k)+y<px1/kΦ(x/p,p).\Phi(x,y)=\Phi(x,x^{1/k})+\sum_{y<p\leq x^{1/k}}\Phi(x/p,p^{-}).

Indeed the sum counts all nxn\leq x with least prime factor p(y,x1/k]p\in(y,x^{1/k}], and Φ(x,x1/k)\Phi(x,x^{1/k}) counts all nxn\leq x with least prime factor >x1/k>x^{1/k}. As we have seen, it suffices to deal with the case when y=q0y=q_{0}^{-} for some prime q0q_{0}.

Note that if (19)\eqref{eq:levelk} holds, then it also holds for y=x1/ky=x^{1/k}. Indeed, if yy is a prime, then Φ(x,y)=Φ(x,y+ϵ)\Phi(x,y)=\Phi(x,y+\epsilon) for all 0<ϵ<10<\epsilon<1, and in this case Φ(x,y)ckx/log(y+ϵ)\Phi(x,y)\leq c_{k}x/\log(y+\epsilon), by hypothesis. Letting ϵ0\epsilon\to 0 shows we have Φ(x,y)ckx/logy\Phi(x,y)\leq c_{k}x/\log y as well. If yy is not prime, then for all sufficiently small ϵ>0\epsilon>0, we again have Φ(x,y)=Φ(x,y+ϵ)\Phi(x,y)=\Phi(x,y+\epsilon) and the same proof works.

Thus, we have (19) holding for all of the terms on the right side of (20). This implies that

(21) Φ(x,q0)ckx(1log(x1/k)+q0px1/k1plogp).\Phi(x,q_{0}^{-})\leq c_{k}x\Bigg{(}\frac{1}{\log(x^{1/k})}+\sum_{q_{0}\leq p\leq x^{1/k}}\frac{1}{p\log p}\Bigg{)}.

We expect that the parenthetical expression here is about the same as 1/logq01/\log q_{0}, so let us try to quantify this. Let

ϵk(q0)=max{1logq0+1log(x1/k)+q0px1/k1plogp:yk<xyk+1}.\epsilon_{k}(q_{0})=\max\Bigg{\{}\frac{-1}{\log q_{0}}+\frac{1}{\log(x^{1/k})}+\sum_{q_{0}\leq p\leq x^{1/k}}\frac{1}{p\log p}:y^{k}<x\leq y^{k+1}\Bigg{\}}.

Let q1q_{1} be the largest prime x1/k\leq x^{1/k}, so that

ϵk(q0)=max{1logq0+1logq1+q0pq11plogp:q0<q1q01+1/k}.\epsilon_{k}(q_{0})=\max\Bigg{\{}\frac{-1}{\log q_{0}}+\frac{1}{\log q_{1}}+\sum_{q_{0}\leq p\leq q_{1}}\frac{1}{p\log p}:q_{0}<q_{1}\leq q_{0}^{1+1/k}\Bigg{\}}.

It follows from (21) that

Φ(x,y)=Φ(x,q0)ckx(1logq0+ϵk(q0))=ckxlogy(1+ϵk(q0)logq0).\Phi(x,y)=\Phi(x,q_{0}^{-})\leq c_{k}x\left(\frac{1}{\log q_{0}}+\epsilon_{k}(q_{0})\right)=\frac{c_{k}x}{\log y}(1+\epsilon_{k}(q_{0})\log q_{0}).

Note that as kk grows, ϵk(q0)\epsilon_{k}(q_{0}) is non-increasing since the max is over a smaller set of primes q1q_{1}. Thus, we have the inequality

(22) Φ(x,q0)c3(1+ϵ3(q0)logq0)jxlogy,x1/3<q0x1/(3+j).\Phi(x,q_{0}^{-})\leq c_{3}(1+\epsilon_{3}(q_{0})\log q_{0})^{j}\frac{x}{\log y},\quad x^{1/3}<q_{0}\leq x^{1/(3+j)}.

Thus, we would like

(23) c3(1+ϵ3(q0)logq0)5<.6c_{3}(1+\epsilon_{3}(q_{0})\log q_{0})^{5}<.6

We have checked (23) numerically for primes q0<1000q_{0}<1000 and it holds for q0241q_{0}\geq 241.

This leaves the case of primes >1000>1000. We have the identity

q0pq1\displaystyle\sum_{q_{0}\leq p\leq q_{1}} 1plogp\displaystyle\frac{1}{p\log p}
=\displaystyle= θ(q0)q0(logq0)2+θ(q1)q1(logq1)2+q0q1θ(t)(1t2(logt)2+2t2(logt)3)𝑑t,\displaystyle\frac{-\theta(q_{0}^{-})}{q_{0}(\log q_{0})^{2}}+\frac{\theta(q_{1})}{q_{1}(\log q_{1})^{2}}+\int_{q_{0}}^{q_{1}}\theta(t)\left(\frac{1}{t^{2}(\log t)^{2}}+\frac{2}{t^{2}(\log t)^{3}}\right)\,dt,

via partial summation, where θ\theta is again Chebyshev’s function. First assume that q1<1019q_{1}<10^{19}. Then, using [4], [5], we have θ(t)t\theta(t)\leq t, so that

q0pq11plogp<q0θ(q0)q0(logq0)2+1logq01logq1.\sum_{q_{0}\leq p\leq q_{1}}\frac{1}{p\log p}<\frac{q_{0}-\theta(q_{0}^{-})}{q_{0}(\log q_{0})^{2}}+\frac{1}{\log q_{0}}-\frac{1}{\log q_{1}}.

We also have [4], [5] that q0θ(q0)<1.95q0q_{0}-\theta(q_{0}^{-})<1.95\sqrt{q_{0}}, so that one can verify that

ϵ3(q0)<1.95q0(logq0)2\epsilon_{3}(q_{0})<\frac{1.95}{\sqrt{q_{0}}(\log q_{0})^{2}}

and so (23) holds for q0>1000q_{0}>1000. It remains to consider the cases when q1>1019q_{1}>10^{19}, which implies q0>1014q_{0}>10^{14}. Here we use |θ(t)t|<3.965t/(logt)2|\theta(t)-t|<3.965t/(\log t)^{2}, which is from [6, Theorem 4.2] or [2, Corollary 11.2]. This shows that (23) holds here as well, completing the proof of Theorem 1.

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