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The irrationality exponent of pi is 2

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Abstract

We prove the conjecture that the irrationality exponent of π is 2. As a consequence, the classical Flint–Hills series ∑n≥11/(n3sin⁡2n)\sum_{n\ge1}1/(n^3\sin^2 n) converges, with angles in radians.

Introduction

For an irrational real number xx, its irrationality exponent (also called its irrationality measure) is

μ(x)=sup⁡{ν>0:0<∣x−pq∣<q−ν for infinitely many coprime p,q∈Z, q≥2}.\mu(x)=\sup\left\{\nu>0:0<\left|x-\frac{p}{q}\right|<q^{-\nu}\text{ for infinitely many coprime }p,q\in\mathbb{Z},\ q\ge2\right\}.

The pigeonhole principle gives μ(x)≥2\mu(x)\ge2. An upper bound limits how frequently rational numbers can approximate xx exceptionally closely; irrationality alone supplies no finite upper bound. The expected value for the usual positive circle constant is 2. Waldschmidt records the corresponding epsilon-dependent approximation conjecture in [23], p. 265. Our main result proves it.

Theorem 1.1. The irrationality exponent of π\pi is 2. More precisely, for every real ν>2\nu>2, there is an integer Q(ν)Q(\nu) such that

∣π−pq∣≥q−ν(p∈Z, q∈Z, q≥Q(ν)).\left|\pi-\frac{p}{q}\right|\ge q^{-\nu}\qquad(p\in\mathbb{Z},\ q\in\mathbb{Z},\ q\ge Q(\nu)).

The inequality applies to all integer numerators and denominators, whether or not the fraction is reduced. The threshold may depend on ν\nu, and the argument does not give it effectively. In particular, an exponent of 2 is different from a uniform positive lower bound of the form c/q2c/q^2, or equivalently from bounded continued-fraction partial quotients.

The related Flint–Hills problem, popularized by Pickover and discussed by Alekseyev [1], asks whether

∑n≥11n3sin⁡2n\sum_{n\ge1}\frac{1}{n^3\sin^2 n}

converges, with angles in radians. Integers very close to multiples of π\pi make individual denominators small. A rational-approximation bound controls how often such small values can occur, not just their individual size.

Corollary 1.2. The classical Flint–Hills series converges.

Alekseyev showed that convergence requires μ(π)≤5/2\mu(\pi)\le5/2 [1], Corollary 4; Meiburg proved the sufficient strict condition μ(π)<5/2\mu(\pi)<5/2 [15], Theorem 2.5. Theorem 1.1 supplies this condition.

Section 5 includes a short dyadic proof of the implication needed here. Neither cited criterion settles its equality boundary at 5/25/2.

More generally, for fixed real numbers a,b>0a,b > 0, consider the family

∑n=1∞1na∣sin⁡n∣b\sum_{n=1}^{\infty}\frac{1}{n^{a}|\sin n|^{b}}

Theorem 1.1 and the spacing argument in Section 5 show that, with angles in radians, this series converges if and only if a>max⁡{1,b}a > \max\{1,b\}; see Corollary 5.2.

Mahler’s 1953 paper [13] established a finite irrationality exponent for π\pi by constructing polynomial-coefficient combinations of powers of logarithms and proving determinant nonvanishing. It gave the explicit exponent 42 for all denominators at least two and also stated an eventual improvement to 30. Mignotte refined that construction, obtaining exponent 21 for all such denominators and 20 eventually [16 Theorem 1]. Chudnovsky developed Hermite–Padé approximation to exponential functions with precise asymptotic estimates [4].

Hata’s integral constructions led to the bound μ(π)≤8.01604539…\mu(\pi) \le8.01604539\ldots [8]; Zudilin gives an account of the simultaneous logarithmic approximation and denominator arithmetic behind this value [25 Theorem 2]. Salikhov’s symmetric-integral method improved it to 7.606308…7.606308\ldots [20, 21]. Zeilberger and Zudilin combined parameter experiments with a rigorous arithmetic and asymptotic analysis to obtain 7.103205334137…7.103205334137\ldots [24]. Bai’s September 2026 preprint claims the further bound μ(π)<7.101862832357\mu(\pi) < 7.101862832357 by a two-exponent variation of the latter integral [2]. These quantitative bounds are context, not inputs to our proof.

The connection with trigonometric series also has a longer history: Mahler applied approximation estimates to sine-denominator Dirichlet series in [13], Section 16. For the classical Flint–Hills question, recent work of Dan on generalized series [5] and López Zapata’s continued-fraction criterion [12] leaves convergence undecided. The earlier convergence claim of Mantzakouras and López Zapata was withdrawn in September 2026 because its proof did not establish convergence or the asserted irrationality bound [14]. Carella claims both exponent two and the stronger bounded-partial-quotient property [3]. Neither claim is used here. The displayed proof of the stronger assertion contains a sign obstruction.1

The proof in outline

The proof uses a multivariable interpolation theorem to construct a nonzero determinant, then compares two incompatible estimates for its absolute value. This organization is related to the interpolation-determinant method discussed by Laurent [9], Section 6. Successively separated approximation denominators already play a central role in Roth’s many-variable method [19], Sections 2–3. Our application requires a different interpolation statement, adapted to logarithmic curves and with thresholds independent of their centers.

Prescribing coefficients. A jet here means a finite packet of Taylor coefficients. Give the coordinates Y,X1,…,XmY, X_1, \ldots, X_m positive weights and retain polynomial monomials satisfying one weighted degree inequality. Their exponent vectors fill a simplex. At each point (1,cj1,…,cjm)(1,c_{j1},\ldots,c_{jm}), expand after the substitution

Y=1+t,Xi=cji+ui+log⁡(1+t).Y = 1 + t,\qquad X_i = c_{ji} + u_i + \log(1+t).

The variable tt follows the logarithmic curve; the variables uiu_i are transverse displacements. Theorem 2.1 states that every packet below the prescribed weighted cutoff can be realized, at finitely many centers whose XiX_i-coordinates are pairwise distinct for each ii, simultaneously. The weights of X1,…,XmX_1,\ldots,X_m are chosen successively before the center locations are known. The weights leave more polynomial coefficients than prescribed Taylor coefficients, but that dimension count alone does not prove full rank at these special centers.

The proof in Section 2 starts from a local multiplicity comparison between coordinate directions and commuting differential directions. Derivative persistence and separated scales restrict any algebraic obstruction; logarithmic residues then force coordinate constancy. This stage is related to the zero-estimate methods of Philippon [18] and the separated multidegrees in Farhi’s Roth lemma [7], Section 5.2. The resulting curve inequality bounds total weighted contact at the centers by the weighted degree of the curve. It gives positivity on an ordinary blowup, and vanishing yields all the requested coefficients. The relation between curvewise positivity and asymptotic jet generation is familiar from Demailly’s work [6], Section 6; the weighted, multiple-center statement on the possibly singular schemes used here is proved explicitly.

Two ways to make the determinant small. Suppose that a fixed exponent ν>2\nu> 2 permits exceptionally close approximations with unbounded denominators. Choose finitely many of these successively and set cji=2ijpi/qic_{ji}=2\mathrm{i}j p_i/q_i. They approximate the common logarithmic periods 2πij2\pi\mathrm{i}j. After truncating the logarithms by a filtration-preserving change, interpolation gives a matrix over Q(i)\mathbb{Q}(\mathrm{i}) with independent rows. A square minor using all rows is nonzero. Clearing its denominators gives an arithmetic lower bound.

For the analytic bound, translate each row to the exact periods and expand in the transverse variables. The index aa denotes the chosen transverse coefficient. For a polynomial column PP,

[ua]P(ez,z+u1,…,z+um)[u^a]P(e^z,z+u_1,\ldots,z+u_m)

is an entire function of zz. Rows test its Taylor coefficients after z=2πij+log⁡(1+t)z=2\pi\mathrm{i}j+\log(1+t). Rows with the same aa therefore test the same entire functions. On expanding those functions in zz, repeated Taylor degrees within that group annihilate a determinant term. Distinct degrees then force a quadratic saving in the group size. This uses the Taylor-expansion mechanism also appearing in [10 Theorem 1]. If many rows have small weighted transverse index, there are too few groups to avoid this saving. If few do, the many large indices instead supply powers of the small rational-approximation errors. Section 3 proves uniform bounds for both alternatives before summing the expansion.

Why full simplices and separated choices matter. The polynomial degree of YY and those of the XiX_i share one budget. Both the interpolation volume and the arithmetic column cost therefore come from full simplices. Comparing the row count in dimension m+1m+1 with the transverse-index count in dimension mm produces a collision saving that can grow with mm, while the other errors decrease. Section 4 arranges this for each fixed ν>2\nu> 2, then chooses approximation denominators meeting all the interpolation thresholds. Their independence from centers prevents a circular choice. Only after dimension, weights, and centers have been fixed does the polynomial degree tend to infinity. The final section proves Corollary 1.2 using a fixed exponent between 2 and 5/2, and establishes the exact convergence criterion in Corollary 5.2.

Conventions and inputs. All logarithms are natural; log⁡(1+t)\log(1+t) denotes its power series at zero. Write i2=−1i^2=-1, and let multi-indices have nonnegative integer entries. For them, α!=∏iαi!\alpha! = \prod_i \alpha_i! and (αβ)=∏i(αiβi)\binom{\alpha}{\beta}=\prod_i\binom{\alpha_i}{\beta_i}, with the latter zero unless β≤α\beta\leq\alpha coordinatewise. Geometry is over C\mathbb{C}, and a curve means an integral algebraic curve. We use polynomial Bézout with isolated local multiplicities, ordinary blowups, nef-plus-ample, eventual Proj recovery, Serre vanishing, and smooth projective models of curves. Their exact hypotheses are checked at use; no prior irrationality bound for π\pi is assumed.

Interpolation with separated weights

We prove the interpolation statement used in the determinant argument. Its essential uniformity is that the weights can be chosen before the interpolation points: each coordinate weight has a lower threshold depending on the earlier weights, but not on the locations of the points. The degree at which interpolation becomes surjective is allowed to depend on all the fixed data.

All multi-indices below have nonnegative integer entries. For a positive rational vector W=(w0,…,wm)W=(w_0,\ldots,w_m), the WW-degree of the monomial YhX1α1⋯XmαmY^hX_1^{\alpha_1}\cdots X_m^{\alpha_m} is w0h+∑iwiαiw_0h+\sum_iw_i\alpha_i. Write PW(H)\mathcal{P}_W(H) for the complex vector space of polynomials of WW-degree at most HH. For a positive rational vector V=(v0,…,vm)V=(v_0,\ldots,v_m), let JV(H)\mathcal{J}_V(H) be the quotient of C[[t,u1,…,um]]\mathbb{C}[[t,u_1,\ldots,u_m]] by the ideal of series whose monomials all have VV-weight at least HH. Thus a vector in JV(H)\mathcal{J}_V(H) is a packet of coefficients indexed by

v0s+∑i=1mviβi<H.v_0s+\sum_{i=1}^{m}v_i\beta_i<H.

The strict inequality in this definition will be used throughout.

Theorem 2.1 (Separated-weight interpolation). Fix integers m,K≥1m,K\geq1 and positive rational numbers w0,v0,θw_0,v_0,\theta such that 0<θ<10<\theta<1 and

Kθm<1,Kw0v0θm<1.(2.1)K\theta^m<1,\qquad K\frac{w_0}{v_0}\theta^m<1. \tag*{(2.1)}

There are successive lower thresholds for positive rational numbers w1,…,wmw_1,\ldots,w_m, depending only on these fixed data and the previously chosen weights, with the following property. Put

W=(w0,w1,…,wm),V=(v0,w1/θ,…,wm/θ).W=(w_0,w_1,\ldots,w_m),\qquad V=(v_0,w_1/\theta,\ldots,w_m/\theta).

For any points

aj=(1,cj1,…,cjm)∈Cm+1,0≤j<K,a_j=(1,c_{j1},\ldots,c_{jm})\in\mathbb{C}^{m+1},\qquad0\leq j<K,

whose coordinates c0i,…,cK−1,ic_{0i},\ldots,c_{K-1,i} are pairwise distinct for each ii, the map

PW(H)⟶⨁j=0K−1JV(H),\mathcal{P}_W(H)\longrightarrow\bigoplus_{j=0}^{K-1}\mathcal{J}_V(H),
P⟼(P(1+t,(cji+ui+log⁡(1+t))i=1m))j=0K−1.(2.2)P\longmapsto\left(P\left(1+t,(c_{ji}+u_i+\log(1+t))_{i=1}^{m}\right)\right)_{j=0}^{K-1}. \tag*{(2.2)}

is surjective for all sufficiently large, sufficiently divisible integers HH. The divisibility requirement can be chosen using only the weights. The remaining lower threshold for HH may depend on the points.

We first establish a numerical inequality on algebraic curves, and then use it to obtain all the jets in (2.2). The local estimate driving the curve argument is recorded separately.

A local multiplicity comparison

A collection of vector fields is called a normal basis to a smooth subvariety at a point if its images form a basis of the ambient tangent space modulo the tangent space of the subvariety. For an irreducible subvariety, this terminology will refer to a general smooth point. There are only finitely many possible index sets in the applications below, so all their generic rank conditions can be checked on one common open subset.

Lemma 2.2 (Weighted transverse multiplicity). Give the coordinates x1,…,xdx_1,\ldots,x_d positive rational degree weights ρ1,…,ρd\rho_1,\ldots,\rho_d. On an open subset of Cd\mathbb{C}^d, let D1,…,DdD_1,\ldots,D_d be commuting analytic vector fields forming a frame, and assign them positive rational costs κ1,…,κd\kappa_1,\ldots,\kappa_d. Fix ε>0\varepsilon>0. Let N>0N>0. Suppose that polynomials f1,…,frf_1,\ldots,f_r have weighted degree at most NN, that ZZ is an irreducible component of their common zero set of codimension k≥1k\geq1, and that

Dγfℓ∣Z=0whenever∑bκbγb<εN.(2.3)D^\gamma f_\ell\big|_Z=0 \qquad\text{whenever} \qquad\sum_b \kappa_b\gamma_b<\varepsilon N. \tag*{(2.3)}

For any coordinate normal basis AA and any DD-field normal basis BB, each of cardinality kk, one has

∏a∈Aρa≤2k! ε−k∏b∈Bκb.(2.4)\prod_{a\in A}\rho_a\leq2k!\,\varepsilon^{-k}\prod_{b\in B}\kappa_b. \tag*{(2.4)}

The bound is uniform in the equations, the component ZZ, and the analytic frame; no lower threshold for NN is required.

Proof. Choose a smooth point xx of ZZ where both normal-basis conditions hold and which lies on no other irreducible component of the common zero set. Flowing from ZZ along the fields indexed by BB gives local analytic coordinates (z,b)(z,b), where zz parametrizes ZZ and b=(b1,…,bk)b=(b_1,\ldots,b_k) consists of transverse flow parameters. Commutativity implies that the chosen fields are the derivatives in the bb-directions. Thus (2.3) says that in the expansion

fℓ(z,b)=∑α∈Z≥0kfℓ,α(z)bα,f_\ell(z,b)=\sum_{\alpha\in\mathbb{Z}_{\geq0}^k}f_{\ell,\alpha}(z)b^\alpha,

every coefficient function of BB-weight less than εN\varepsilon N vanishes identically on the chosen neighborhood in ZZ.

Let SS be the affine coordinate slice through xx obtained by fixing the coordinates outside AA. It is transverse to ZZ, and the zero set of the restricted equations is isolated at xx. The flow parameters bb give regular analytic coordinates on SS; the coordinates zz become analytic functions z(b)z(b). Substitution cannot generate a missing term of smaller BB-weight. Indeed, each surviving summand already contains a monomial bαb^\alpha of weight at least εN\varepsilon N, and its analytic coefficient has only nonnegative powers of bb. Consequently the ideal of the restricted equations is contained in the monomial ideal of weight at least εN\varepsilon N. Its quotient therefore has length at least

#{α∈Z≥0k:∑b∈Bκbαb<εN}≥(εN)k2k!∏b∈Bκb.(2.5)\#\left\{\alpha\in\mathbb{Z}_{\geq0}^k:\sum_{b\in B}\kappa_b\alpha_b<\varepsilon N\right\}\geq\frac{(\varepsilon N)^k}{2k!\prod_{b\in B}\kappa_b}. \tag*{(2.5)}

In fact the factor 1/21/2 can be omitted: the simplex {x∈R≥0k:∑b∈Bκbxb<εN}\{x \in\mathbb{R}_{\ge0}^{k} : \sum_{b \in B} \kappa_b x_b < \varepsilon N\} is covered by the disjoint half-open unit cubes α+[0,1)k\alpha+ [0,1)^k indexed by the admissible multi-indices α=⌊x⌋\alpha= \lfloor x \rfloor. Its volume is (εN)k/(k!∏b∈Bκb)(\varepsilon N)^k/(k! \prod_{b \in B} \kappa_b). Thus the displayed bound holds for every N>0N > 0. Analytic local coordinates preserve finite length, so no radius or coefficient bound for the flow map is needed.

In the regular local ring of the kk-dimensional slice, the ideal generated by the restricted equations is primary to the maximal ideal. Over the infinite field C\mathbb{C}, kk sufficiently general constant linear combinations of these equations still have an isolated common zero at xx: successive generic combinations avoid the finitely many positive-dimensional components that remain. Their ideal is contained in the original ideal. Their quotient length is therefore an upper bound for the length in (2.5).

Each of the kk combinations has weighted degree at most NN in the variables indexed by AA. We claim that their local intersection length is at most

Nk∏a∈Aρa.(2.6)\frac{N^k}{\prod_{a \in A} \rho_a}. \tag*{(2.6)}

Choose an integer M0M_0 clearing the denominators of the ρa\rho_a, and make the substitutions

xa=λa+zaM0ρa(a∈A).x_a = \lambda_a + z_a^{M_0 \rho_a} \qquad(a \in A).

Choose the constants λa\lambda_a so that no preimage of the given point is ramified. There are ∏a∈A(M0ρa)\prod_{a \in A}(M_0 \rho_a) such preimages, each with the same local intersection length. The substituted polynomials have ordinary total degree at most M0NM_0N. The ordinary Bézout bound for isolated complete-intersection zeros, with their local multiplicities, bounds the sum of these lengths by (M0N)k(M_0N)^k; see [17 Corollary VIII.3, p. 144]. The multiplicities there are local quotient lengths, unchanged by completion [17 Section IV.4.2]. Dividing gives (2.6). This application concerns isolated zeros only and permits other components elsewhere.

Combining (2.5) and (2.6) proves the result. Neither the polynomials nor the possibly varying component enters the constant in (2.4).

The curve inequality

Choose a positive rational number σ\sigma sufficiently small that

(1+3σ)m+1K(w0/v0)θm<1,(1+3σ)mKθm<1,(1+σ)θ<1.(2.7)\begin{aligned} (1 + 3\sigma)^{m+1} K (w_0/v_0)\theta^m &< 1,\\ (1 + 3\sigma)^m K\theta^m &< 1,\\ (1 + \sigma)\theta&< 1. \tag*{(2.7)} \end{aligned}

This choice is possible by (2.1). Set vi=wi/θv_i = w_i/\theta for i>0i > 0. Fix L0=m+2L_0 = m + 2 and put

C∗=max⁡1≤k≤m2k!(L0/σ)k.(2.8)C_* = \max_{1 \le k \le m} 2k!(L_0/\sigma)^k. \tag*{(2.8)}

We choose the positive weights successively so that for every pair of subsets A,B⊆{0,…,m}A, B \subseteq\{0,\ldots,m\} of the same cardinality between 11 and mm,

∏a∈Awa>C∗∏b∈Bvb(2.9)\prod_{a \in A} w_a > C_* \prod_{b \in B} v_b \tag*{(2.9)}

whenever the largest positive index in their symmetric difference belongs to AA.

Here and below a condition involving that largest index is imposed only when a positive index does differ. The successive choice is possible: if this largest index is ii, the ratio in (2.9) is wiw_i times a positive expression in the already chosen lower weights and the fixed zeroth weights. Every higher index occurs in both sets or in neither; in the former case its ratio is wj/vj=θw_j/v_j=\theta. Hence the expression is independent of all higher weights. There are finitely many pairs of sets. A sufficiently large choice of wiw_i enforces all conditions whose largest differing index is ii, and subsequent choices do not disturb them. This construction involves no interpolation point.

Let CC be an irreducible algebraic curve whose generic point lies in the affine coordinate chart. Such a curve has a smooth projective model over C\mathbb{C}; see [22], Theorem 53.2.6 and Lemma 53.2.8, Tag 0BXX. On that model define

deg⁡WC=∑Pmax⁡{0,−ord⁡PYw0,−ord⁡PX1w1,…,−ord⁡PXmwm}.(2.10)\deg_W C=\sum_P\max\left\{0,-\frac{\operatorname{ord}_P Y}{w_0},-\frac{\operatorname{ord}_P X_1}{w_1},\ldots,-\frac{\operatorname{ord}_P X_m}{w_m}\right\}. \tag*{(2.10)}

The order of an identically zero coordinate is understood as +∞+\infty; it contributes no pole. At a branch PP through aja_j, set

hP=min⁡{ord⁡P(Y−1)v0,ord⁡P(X1−cj1−log⁡Y)v1,…,ord⁡P(Xm−cjm−log⁡Y)vm}.(2.11)h_P=\min\left\{\frac{\operatorname{ord}_P(Y-1)}{v_0},\frac{\operatorname{ord}_P(X_1-c_{j1}-\log Y)}{v_1},\ldots,\frac{\operatorname{ord}_P(X_m-c_{jm}-\log Y)}{v_m}\right\}. \tag*{(2.11)}

The logarithm here is its formal expansion at Y=1Y=1. All entries have positive order, possibly infinite, and their minimum is finite on a nonconstant curve.

Proposition 2.3 (Curve inequality). With the weights chosen above, every such curve satisfies

deg⁡WC≥(1+σ)∑P↦ajhP,(2.12)\deg_W C\ge(1+\sigma)\sum_{P\mapsto a_j}h_P, \tag*{(2.12)}

where the sum includes all branches through the prescribed points.

Proof. There is nothing to prove if the curve misses all the points. Suppose instead that (2.12) fails. For every sufficiently large auxiliary integer NN, linear algebra gives a nonzero polynomial FNF_N of WW-degree at most NN whose expansions at all the points have VV-order at least (1+3σ)N(1+3\sigma)N. Indeed, the number of its coefficients has leading term

Nm+1(m+1)!∏a=0mwa.\frac{N^{m+1}}{(m+1)!\prod_{a=0}^{m}w_a}.

whereas the number of conditions has leading term

K(1+3σ)m+1Nm+1(m+1)!∏a=0mva.\frac{K(1+3\sigma)^{m+1}N^{m+1}}{(m+1)!\prod_{a=0}^{m}v_a}.

Their comparison is the first inequality in (2.7). This argument requires no independence among the conditions.

On the open set Y≠0Y\ne0 consider the commuting frame

D0=Y∂Y+∑i=1m∂Xi,Di=∂Xi(1≤i≤m).(2.13)D_0=Y\partial_Y+\sum_{i=1}^{m}\partial_{X_i},\qquad D_i=\partial_{X_i}\quad(1\le i\le m). \tag*{(2.13)}

It preserves polynomial degree at most NN. In the formal coordinates of (2.2),

D0=(1+t)∂t,Di=∂ui.D_0=(1+t)\partial_t,\qquad D_i=\partial_{u_i}.

Thus differentiation by DaD_a decreases weighted order by at most vav_a. Every DγFND^\gamma F_N with ∑avaγa≤σN\sum_a v_a\gamma_a \le\sigma N retains order at least (1+2σ)N(1+2\sigma)N at each point. On a branch PP, its order is consequently at least (1+2σ)NhP(1+2\sigma)Nh_P.

A polynomial of WW-degree at most NN restricts to a rational function on the complete model of CC with total pole degree at most Ndeg⁡WCN\deg_W C. Since we assumed that (2.12) fails, the just obtained total zero order exceeds this pole bound. The ordinary divisor equality for a nonzero rational function therefore forces

DγFN∣C=0(∑avaγa≤σN).(2.14)D^\gamma F_N|_C=0 \qquad\left(\sum_a v_a\gamma_a \le\sigma N\right). \tag*{(2.14)}

All the assertions about branch orders hold for formal power series: each monomial has order at least its weight times hPh_P, and cancellation can only increase the order.

We have converted excess contact into vanishing of many derivatives on CC. We next find a component on which that vanishing persists, as in the derivative-ideal method of zero estimates [18], Section 5, and compare all its normal bases. Put δ=σN/L0\delta=\sigma N/L_0. For 0≤r≤L00\le r\le L_0, let VrV_r be the common zero set in Y≠0Y\ne0 of the derivatives of cost at most rδr\delta. Let C∘C^\circ be the part of CC in this affine open set. The VrV_r form a decreasing chain, and (2.14) puts C∘C^\circ in VL0V_{L_0}. Choose an irreducible component of VL0V_{L_0} containing C∘C^\circ, and extend it backwards to nested irreducible components of the earlier VrV_r. Every selected component has dimension between 1 and mm: it contains a curve, and it lies in the proper zero set of FNF_N. Since there are L0+1=m+3L_0+1=m+3 levels, two adjacent selected components coincide. Denote this persistent component by ZZ, and write k=codim⁡Zk=\operatorname{codim} Z.

Take the derivatives of cost at most rδr\delta as the equations of the earlier of these two levels. Any further derivative of cost less than δ\delta vanishes along ZZ, because the fields commute and ZZ is also a component at the next level. Lemma 2.2, with ε=σ/L0\varepsilon=\sigma/L_0, gives

∏a∈Awa≤C∗∏b∈Bvb(2.15)\prod_{a\in A} w_a \le C_* \prod_{b\in B} v_b \tag*{(2.15)}

for every coordinate normal basis AA and every frame normal basis BB. The equations and ZZ may vary with NN; the uniformity proved in Lemma (2.2) is exactly what permits this use.

We show that YY is constant on ZZ, working on the common smooth open subset where all the normal-basis conditions hold. Suppose first that some positive coordinate direction is nontangent to ZZ, and choose the largest such index ii. Every larger positive index occurs in neither kind of normal basis, since Dj=∂XjD_j=\partial_{X_j} for j>0j>0. Some coordinate normal basis AA contains ii. If a frame normal basis BB omitted ii, the largest positive index where these sets differ would be ii. Then (2.9) would contradict (2.15). Thus every frame normal basis contains DiD_i.

The other frame vectors consequently fail to span the normal quotient. Their ambient span is the hyperplane

ker⁡(dXi−dY/Y).\ker(dX_i-dY/Y).

For an ambient hyperplane QQ and a tangent space TT, the image of QQ in the quotient by TT fails to be surjective precisely when T⊆QT\subseteq Q. We obtain

dXi=dY/Yon Z.(2.16)dX_i=dY/Y\quad\text{on }Z. \tag*{(2.16)}

This identity forces YY to be constant on the algebraic variety ZZ. Indeed, if YY were nonconstant, choose a smooth point where dY≠0dY\ne0 and intersect with general algebraic hyperplanes through that point until a curve remains on which YY is nonconstant. On the smooth complete model of this curve, (2.16) is an identity of meromorphic differentials. A nonconstant meromorphic function YY has a zero or pole, where dY/YdY/Y has nonzero residue ord⁡PY\operatorname{ord}_{P}Y. An exact differential dXidX_i has zero residue at every point. This is a contradiction. It follows also that XiX_i is constant, since dXi=0dX_i = 0 in characteristic zero.

If instead every positive coordinate direction is tangent, the mm independent vectors ∂Xi\partial X_i all lie in the tangent space of ZZ. Properness forces that tangent space to be their span, and dY=0dY = 0 on ZZ again. We conclude in all cases that YY is constant on ZZ. Since C∘⊆ZC^\circ\subseteq Z meets a prescribed point with Y=1Y = 1, we have Y=1Y = 1 on C∘C^\circ, and hence on CC by density.

It remains to rule out a violating curve in that fiber. We work with C∘C^\circ in the affine fiber Y=1Y = 1, while computing orders and degrees on the complete model of CC as before. In this fiber, the degree weights are wiw_i, the order weights are vi=wi/θv_i = w_i/\theta, and hP=min⁡iord⁡P(Xi−cji)/vih_P = \min_i \operatorname{ord}_P(X_i - c_{ji})/v_i. Choose a new auxiliary polynomial in these mm variables. The ratio of the number of vanishing conditions to the number of coefficients now tends to K(1+3σ)mθm<1K(1 + 3\sigma)^m\theta^m < 1, by the second inequality in (2.7). Thus, for sufficiently large NN, there is a nonzero polynomial GN(X1,…,Xm)G_N(X_1,\ldots,X_m) of weighted degree at most NN and order at least (1+3σ)N(1 + 3\sigma)N at every center.

An ordinary partial derivative of cost at most σN\sigma N still has order at least (1+2σ)N(1 + 2\sigma)N at every center and degree at most NN. The same zero–pole comparison on CC therefore gives

∂XγGN∣C=0(∑i=1mviγi≤σN).\left.\partial_X^\gamma G_N\right|_C = 0 \qquad\left(\sum_{i=1}^{m} v_i\gamma_i \le\sigma N\right).

If m=1m = 1, this is already impossible: a nonzero polynomial on the affine line cannot vanish on a curve. Suppose henceforth that m≥2m \ge2. For 0≤r≤L00 \le r \le L_0, let UrU_r be the common zero set in this fiber of the partial derivatives of GNG_N of cost at most rδr\delta, with δ=σN/L0\delta= \sigma N/L_0 as before. The curve C∘C^\circ lies in UL0U_{L_0}. Choose nested irreducible components containing C∘C^\circ backwards through this chain. Their dimensions lie between 11 and m−1m - 1, since GNG_N is nonzero, so two adjacent components coincide in a component Z′Z'. Its codimension in the fiber satisfies 1≤k≤m−11 \le k \le m - 1.

For the equations at the earlier of these two levels, every further partial derivative of cost less than δ\delta vanishes on Z′Z'. Lemma (2.2), again with ε=σ/L0\varepsilon= \sigma/L_0, therefore gives (2.15) for Z′Z', with the same C∗C_* and with normal-basis index sets contained in {1,…,m}\{1,\ldots,m\}.

Here the coordinate and frame bases are the same. They must have a unique index set: two different basis sets could be ordered so that the largest differing index belongs to AA, contradicting (2.9). The codimension is positive, so this unique normal basis has some index ii. The other coordinate directions fail to span the normal quotient; hence the tangent space is contained in ker⁡dXi\ker dX_i, and XiX_i is constant on Z′Z'. Coordinatewise distinctness shows that Z′Z' meets at most one prescribed point. Every prescribed point of CC belongs to C∘⊆Z′C^\circ\subseteq Z', so the same holds for CC.

Let that point be aja_j. Choose a coordinate XlX_l nonconstant on CC. The nonzero rational function Xl−cjlX_l - c_{jl} has total pole degree at most wldeg⁡WCw_l\deg_W C, and at each branch through aja_j it has order at least (wl/θ)hP(w_l/\theta)h_P. Therefore

deg⁡WC≥θ−1∑P→ajhP>(1+σ)∑P→ajhP,\deg_W C \ge\theta^{-1}\sum_{P\to a_j} h_P > (1+\sigma)\sum_{P\to a_j} h_P,

by the last inequality in (2.7). This final contradiction proves (2.12).

From the curve inequality to all coefficient packets

We complete the proof of Theorem 2.1. The argument uses ordinary projective schemes and the ordinary blow-up; smoothness or normality of the compactification will not be needed. Curve positivity and asymptotic jet generation are closely related in the Seshadri-constant approach of [6], Section 6. Here we supply the passage for our weighted ideals at several points, including the eventual ordinary-power comparison required on a possibly singular scheme.

Choose an integer RR sufficiently large that R/waR/w_a and R/vaR/v_a are positive integers for every index. Embed affine space by all monomials of WW-degree at most RR, including the constant monomial, and let XX be the projective closure of the image. Since these monomials include each coordinate, the chart of the constant monomial is precisely the original affine space. Let L=OX(1)L = \mathcal{O}_X(1), a very ample line bundle.

For any curve meeting this chart,

deg⁡(L∣C)=Rdeg⁡WC.(2.17)\deg(L|_C) = R\deg_W C. \tag*{(2.17)}

To see this on its smooth complete model, at each point clear the largest pole of the homogeneous monomial coordinates. Every monomial has pole order at most RR times the maximum in (2.10). A pure power of one coordinate attains that bound whenever the maximum is positive, and the constant monomial attains it when the maximum is zero. The resulting sections have no common zero, proving (2.17).

To make the local data algebraic, replace log⁡(1+t)\log(1+t) in each coordinate by a fixed Taylor polynomial Gi(t)G_i(t) whose omitted terms have tt-weight strictly greater than viv_i. Then

t=Y−1,ui′=Xi−cji−Gi(t)t = Y - 1,\qquad u_i' = X_i - c_{ji} - G_i(t)

are regular local coordinates at aja_j. This replacement preserves hPh_P. Indeed, if tt is not identically zero on a branch, each omitted term has order divided by viv_i strictly larger than ord⁡P(t)/v0\operatorname{ord}_P(t)/v_0; if tt is identically zero, its tail vanishes. It also preserves interpolation surjectivity for every threshold: the formal coordinate change fixes tt and changes uiu_i only by terms of weight greater than viv_i. It and its inverse preserve the weighted filtration and induce inverse triangular maps on each finite coefficient packet.

At aja_j form the finite-colength ideal

Ij=(tR/v0,(u1′)R/v1,…,(um′)R/vm).I_j = \left(t^{R/v_0},(u_1')^{R/v_1},\ldots,(u_m')^{R/v_m}\right).

The points are distinct. These local ideals, together with the unit ideal away from the points, define a coherent ideal sheaf II on XX. For a branch through a center,

ord⁡PI=min⁡a{(R/va)ord⁡Pza}=RhP,z0=t,zi=ui′.(2.18)\operatorname{ord}_P I = \min_a\{(R/v_a)\operatorname{ord}_P z_a\} = Rh_P,\qquad z_0=t,\quad z_i=u_i'. \tag*{(2.18)}

Let p:X′→Xp:X'\to X be the ordinary blow-up of II, namely the relative Proj of its Rees algebra, and write

IOX′=OX′(−E).I\mathcal{O}_{X'}=\mathcal{O}_{X'}(-E).

The scheme XX is integral and Noetherian, II is a coherent nonzero ideal, and EE is an effective Cartier divisor. The tautological bundle OX′(−E)\mathcal{O}_{X'}(-E) is relatively ample; these are the standard blow-up properties in [22], Tags 02OS, 02ND, and 02NS.

Write A=p∗LA=p^*L in additive divisor notation. We claim that

A−(1+σ)E is nef.(2.19)A-(1+\sigma)E\ \text{is nef}. \tag*{(2.19)}

For a noncontracted integral curve Γ\Gamma upstairs whose image meets the affine chart, the map to its image is birational, since pp is an isomorphism away from the finite center. On the complete normalizations, (2.17) and (2.18) give

A⋅Γ=Rdeg⁡Wp(Γ),E⋅Γ=R∑P↦ajhP.A \cdot\Gamma= R \deg_W p(\Gamma), \qquad E \cdot\Gamma= R \sum_{P \mapsto a_j} h_P.

Proposition 2.3 gives the desired nonnegative degree. A curve whose image misses the affine chart avoids the exceptional divisor. A contracted curve has AA-degree zero and positive degree for −E-E by relative ampleness. These cases account for every integral curve, proving (2.19).

For sufficiently large a>1a>1, the divisor aA−EaA-E is ample. One can see this directly: choose bb so that I⊗LbI \otimes L^b is globally generated. The Rees construction embeds X′X' in a product X×PrX \times\mathbb{P}^r, with the second hyperplane bundle restricting to bA−EbA-E. Tensoring with the first very ample bundle makes (b+1)A−E(b+1)A-E ample. Now the identity

A−E=a−1a(1+σ)−1(A−(1+σ)E)+σa(1+σ)−1(aA−E)(2.20)A-E=\frac{a-1}{a(1+\sigma)-1}\left(A-(1+\sigma)E\right)+\frac{\sigma}{a(1+\sigma)-1}(aA-E) \tag*{(2.20)}

expresses A−EA-E as a positive multiple of a nef class plus a positive multiple of an ample class. It is therefore ample; see [11], Corollary 1.4.10. This theorem applies to projective schemes and does not require a smooth blow-up.

For all sufficiently large nn, the graded-piece and relative vanishing theorems for the ordinary Rees algebra give

p∗OX′(−nE)=In,Rqp∗OX′(−nE)=0(q>0).(2.21)p_*\mathcal{O}_{X'}(-nE)=I^n,\qquad R^q p_*\mathcal{O}_{X'}(-nE)=0\quad(q>0). \tag*{(2.21)}

Indeed, on any affine open of the Noetherian base the Rees algebra is a Noetherian graded algebra generated in degree one. Its sufficiently high graded pieces recover the sections of its associated sheaf on Proj⁡\operatorname{Proj}, and the higher cohomology of those twists vanishes. A finite affine cover gives one common threshold; see [22], Tags 0AG6 and 0AG7. In particular, (2.21) uses ordinary powers InI^n, not their integral closures, and makes no assertion about small nn.

By the projection formula, Leray, and Serre vanishing for the ample line bundle A−EA-E,

H1(X,In⊗Ln)=H1(X′,OX′(n(A−E)))=0(2.22)H^1(X,I^n\otimes L^n)=H^1(X',\mathcal{O}_{X'}(n(A-E)))=0 \tag*{(2.22)}

for all sufficiently large nn; see [22], Tag 0B5U. The exact sequence for InI^n consequently gives a surjection from H0(X,Ln)H^0(X,L^n) onto all its local coefficient data modulo InI^n. The constant projective coordinate trivializes LL on the affine chart. Finite-colength local quotients are unchanged by completion, so these algebraic classes are also the formal coefficient data used in the theorem. In these trivializations, every element of InI^n has weighted order at least nRnR, because every displayed generator of II has weight RR. Thus

In⊆{local series of weight at least nR}.(2.23)I^n \subseteq\{\text{local series of weight at least }nR\}. \tag*{(2.23)}

Surjectivity modulo InI^n therefore implies surjectivity onto the smaller quotient consisting of the desired packets of weight less than nRnR. Equality in (2.23) is not needed.

Finally, every section of LnL^n for sufficiently large nn is supplied by a homogeneous degree-nn polynomial in the projective embedding coordinates. This follows from Serre vanishing applied to the homogeneous ideal sheaf of XX in its projective space. Such a polynomial restricts on the affine chart to one of WW-degree at most nRnR. Taking H=nRH=nR and undoing the filtered Taylor-polynomial coordinate change proves the surjectivity in (2.22), and completes the proof of Theorem 2.1.

The arithmetic and analytic determinant estimates

Interpolation now supplies the algebraic rank needed for an interpolation determinant, in the sense of [9], Section 6. We estimate one full-row minor from below arithmetically, and then translate its rows to exact logarithmic periods to obtain an analytic upper bound.

Throughout this section all parameters except HH are fixed. Write

wα=∑i=1mwiαi,w∗=min⁡1≤i≤mwi,ω=2πi.w\alpha= \sum_{i=1}^{m} w_i\alpha_i, \qquad w_* = \min_{1\le i\le m} w_i, \qquad\omega= 2\pi i.

Let ν>2\nu> 2, and suppose that integers pip_i and qi≥2q_i \ge2 satisfy

∣π−piqi∣≤qi−ν,wi=⌈log⁡qi⌉,ri=2ipiqi(1≤i≤m).(3.1)\left\lvert\pi- \frac{p_i}{q_i} \right\rvert\le q_i^{-\nu}, \qquad w_i = \lceil\log q_i \rceil, \qquad r_i = \frac{2ip_i}{q_i} \qquad(1 \le i \le m). \tag*{(3.1)}

Assume that pi≠0p_i \ne0 and that m,K,w0,v0,θ,w1,…,wmm,K,w_0,v_0,\theta,w_1,\ldots,w_m satisfy the hypotheses of Theorem 2.1, with centers cji=jric_{ji}=jr_i, 0≤j<K0 \le j < K. In particular wiw_i is a positive integer for i>0i>0, while w0w_0 and v0v_0 are positive rational numbers. Fix F0>2/θF_0 > 2/\theta, and put

Ti=⌈F0wiv0⌉,Gi(t)=∑1≤k<Ti(−1)k+1tkk.(3.2)T_i = \left\lceil\frac{F_0w_i}{v_0} \right\rceil, \qquad G_i(t) = \sum_{1\le k<T_i} \frac{(-1)^{k+1}t^k}{k}. \tag*{(3.2)}

Empty sums are zero. The first omitted term has weight v0Ti≥F0wi>wi/θv_0T_i \ge F_0w_i > w_i/\theta. Consequently the substitution ui↦ui+Gi(t)−log⁡(1+t)u_i \mapsto u_i + G_i(t) - \log(1+t) is an invertible substitution preserving the weighted filtration. It induces an invertible map on every finite space of coefficients of weight less than HH. Thus replacing the logarithms in Theorem 2.1 by these GiG_i preserves surjectivity.

A full-row-rank minor and its arithmetic size

Use the monomials

P(Y,X)=YhXα,h∈Z≥0,α∈Z≥0m,w0h+wα≤HP(Y,X) = Y^hX^\alpha, \qquad h \in\mathbb{Z}_{\ge0}, \quad\alpha\in\mathbb{Z}_{\ge0}^{m}, \qquad w_0h+w\alpha\le H

as columns, and the triples

ρ=(j,s,β),0≤j<K,s∈Z≥0,β∈Z≥0m,v0s+wβθ<H\rho= (j,s,\beta), \qquad0 \le j < K, \quad s \in\mathbb{Z}_{\ge0}, \quad\beta\in\mathbb{Z}_{\ge0}^{m}, \qquad v_0s+\frac{w\beta}{\theta} < H

as rows. The matrix entry is the coefficient of tsuβt^su^\beta in

P(1+t,jr1+G1(t)+u1,…,jrm+Gm(t)+um).(3.3)P(1+t,jr_1+G_1(t)+u_1,\ldots,jr_m+G_m(t)+u_m). \tag*{(3.3)}

For all sufficiently large, sufficiently divisible HH, choose a square minor ΔH≠0\Delta_H \ne0 using every row, as permitted by Theorem 2.1. Denote its size by M=MHM=M_H, and set

bˉ=bˉH=1MH∑ρ=(j,s,β)wβ.(3.4)\bar b = \bar b_H = \frac{1}{MH}\sum_{\rho=(j,s,\beta)} w\beta. \tag*{(3.4)}

The elementary lattice count for a simplex gives

M∼KθmHm+1(m+1)!v0∏i=1mwi,0≤bˉ≤θ.(3.5)M \sim\frac{K\theta^m H^{m+1}}{(m+1)!v_0\prod_{i=1}^{m}w_i}, \qquad0 \le\bar b \le\theta. \tag*{(3.5)}

Indeed, after scaling by HH, the lattice boxes of side lengths H−1H^{-1} are Riemann sums for the fixed simplex. Its volume is θm(m+1)!v0∏iwi\frac{\theta^m}{(m+1)!v_0\prod_i w_i}; its boundary has volume zero, so the strict inequality in the row definition does not affect the leading term. We always let HH tend to infinity only after all the weights and centers have been fixed.

Lemma 3.1 (Arithmetic lower bound). Let Λ=4log⁡2\Lambda= 4\log2, and define

Ear=ΛF0mv0+Λ∑i=1m1wi+θw∗.(3.6)E_{\mathrm{ar}}=\frac{\Lambda F_0m}{v_0}+\Lambda\sum_{i=1}^{m}\frac{1}{w_i}+\frac{\theta}{w_*}. \tag*{(3.6)}

Then every minor just chosen satisfies

log⁡∣ΔH∣MH≥−(1−bˉ)−Ear.(3.7)\frac{\log\lvert\Delta_H\rvert}{MH}\geq-(1-\bar b)-E_{\mathrm{ar}}. \tag*{(3.7)}

Proof. Let Li=lcm⁡(1,…,Ti−1)L_i=\operatorname{lcm}(1,\ldots,T_i-1), interpreted as 11 if Ti=1T_i=1, and put

DH=∏i=1mLi⌊H/wi⌋.D_H=\prod_{i=1}^{m}L_i^{\lfloor H/w_i\rfloor}.

Scale a column YhXαY^hX^\alpha by ∏iqiαi\prod_i q_i^{\alpha_i} and a row (j,s,β)(j,s,\beta) by ∏iqi−βi\prod_i q_i^{-\beta_i}. The scaled entry is zero unless α≥β\alpha\geq\beta componentwise; otherwise it is

∏i(αiβi)[ts](1+t)h∏i(qi(jri+Gi(t)))αi−βi.\prod_i\binom{\alpha_i}{\beta_i}[t^s](1+t)^h\prod_i(q_i(jr_i+G_i(t)))^{\alpha_i-\beta_i}.

Here qijri=2ijpi∈Z[i]q_ijr_i=2ijp_i\in\mathbb{Z}[i]. Since GiG_i has coefficients in Li−1ZL_i^{-1}\mathbb{Z}, the denominator of this entry divides ∏iLiαi−βi\prod_iL_i^{\alpha_i-\beta_i}, which divides DHD_H. Thus multiplying every entry of the scaled matrix by DHD_H gives a matrix over Z[i]\mathbb{Z}[i] with nonzero determinant. A nonzero Gaussian integer has modulus at least one, so

log⁡∣ΔH∣≥−Mlog⁡DH−∑columns α∑iαilog⁡qi+∑rows β∑iβilog⁡qi.(3.8)\log\lvert\Delta_H\rvert\geq-M\log D_H-\sum_{\text{columns }\alpha}\sum_i\alpha_i\log q_i+\sum_{\text{rows }\beta}\sum_i\beta_i\log q_i. \tag*{(3.8)}

For each selected column, ∑iαilog⁡qi≤wα≤H\sum_i\alpha_i\log q_i\leq w\alpha\leq H. Also 0≤wi−log⁡qi<10\leq w_i-\log q_i<1, and hence

∑rows β∑iβilog⁡qi≥MHbˉ−∑rows β∑iβi≥MHbˉ−MHθw∗.\sum_{\text{rows }\beta}\sum_i\beta_i\log q_i\geq MH\bar b-\sum_{\text{rows }\beta}\sum_i\beta_i\geq MH\bar b-\frac{MH\theta}{w_*}.

For completeness, log⁡lcm⁡(1,…,n)≤Λn\log\operatorname{lcm}(1,\ldots,n)\leq\Lambda n. To see this, the factorial valuation formula shows that each prime power in (ℓ,2ℓ](\ell,2\ell] contributes its logarithmic prime weight to log⁡(2ℓℓ)\log\binom{2\ell}{\ell}; all the other contributions to the latter are nonnegative. Thus the increase of the log least common multiple across this interval is at most 2ℓlog⁡22\ell\log2. Summing over dyadic intervals up to the smallest power of two above nn gives at most 4nlog⁡24n\log2. Therefore

log⁡DHH≤Λ∑iTiwi≤ΛF0mv0+Λ∑i1wi.\frac{\log D_H}{H}\leq\Lambda\sum_i\frac{T_i}{w_i}\leq\frac{\Lambda F_0m}{v_0}+\Lambda\sum_i\frac{1}{w_i}.

Substitution in (3.8) proves (3.7).

Translation to entire functions

For every multi-index a∈Z≥0ma \in\mathbb{Z}_{\geq0}^{m} and every selected column PP, define the entire function

fa,P(z)=[ua]P(ez,z+u1,…,z+um).(3.9)f_{a,P}(z)=[u^{a}]P(e^{z},z+u_{1},\ldots,z+u_{m}). \tag*{(3.9)}

We regard (fa,P)P(f_{a,P})_{P} as a row vector of entire functions, indexed by the selected columns. For P=YhXαP=Y^{h}X^{\alpha} it has the explicit entry

fa,P(z)={(αa)ehzz∣α∣−∣a∣,a≤α,0,otherwise.(3.10)f_{a,P}(z)= \begin{cases} \binom{\alpha}{a}e^{hz}z^{|\alpha|-|a|}, & a\leq\alpha,\\ 0, & \text{otherwise}. \end{cases} \tag*{(3.10)}

In particular only indices aa with wa≤Hwa\leq H can contribute.

Lemma 3.2 (Exact row translation). Every row ρ=(j,s,β)\rho=(j,s,\beta) of (3.3) is a sum of at most

QH=(⌊H⌋+1)2m(⌊H/v0⌋+1)(3.11)Q_{H}=(\lfloor H\rfloor+1)^{2m}(\lfloor H/v_{0}\rfloor+1) \tag*{(3.11)}

scalar multiples of row vectors of the form

([tℓ]fa,P(jω+log⁡(1+t)))P,a≥β,wa≤H,0≤ℓ≤s.\left([t^{\ell}]f_{a,P}(j\omega+\log(1+t))\right)_{P}, \qquad a\geq\beta,\quad wa\leq H,\quad0\leq\ell\leq s.

Each scalar ξ\xi occurring with index aa satisfies

∣ξ∣≤exp⁡{−νw(a−β)+HEtr},|\xi|\leq\exp\{-\nu w(a-\beta)+HE_{\mathrm{tr}}\},
Etr=νF0+log⁡2v0+log⁡4+log⁡(2K)+νw∗.(3.12)E_{\mathrm{tr}}=\frac{\nu}{F_{0}}+\frac{\log2}{v_{0}}+\frac{\log4+\log(2K)+\nu}{w_{*}}. \tag*{(3.12)}

Proof. Put

ϵi=j(ri−ω),τi(t)=Gi(t)−log⁡(1+t).\epsilon_i=j(r_i-\omega),\qquad\tau_i(t)=G_i(t)-\log(1+t).

Since ejω=1e^{j\omega}=1, the substitutions in (3.3) can be written as Y=ezY=e^{z}, Xi=z+ui+ϵi+τi(t)X_i=z+u_i+\epsilon_i+\tau_i(t), where z=jω+log⁡(1+t)z=j\omega+\log(1+t). Expanding first in the variables uiu_i, then in the constants ϵi\epsilon_i and tails τi\tau_i, gives the exact row vector identity

row⁡j,s,β=∑a≥βwa≤H(aβ)∑0≤d≤a−β(a−βd)ϵa−β−d∑k=0s([tk]∏iτi(t)di)⋅([ts−k]fa,P(jω+log⁡(1+t)))P.(3.13)\operatorname{row}_{j,s,\beta} = \sum_{\substack{a\geq\beta\\wa\leq H}} \binom{a}{\beta} \sum_{0\leq d\leq a-\beta} \binom{a-\beta}{d}\epsilon^{a-\beta-d} \sum_{k=0}^{s} \left([t^{k}]\prod_i\tau_i(t)^{d_i}\right) \cdot \left([t^{s-k}]f_{a,P}(j\omega+\log(1+t))\right)_{P}. \tag*{(3.13)}

All scalar factors in this identity are independent of the column PP. This is therefore an identity to which determinant multilinearity applies directly.

The product of tails vanishes to order at least ∑idiTi\sum_i d_iT_i. Consequently a nonzero coefficient in (3.13) satisfies

∑idiwi≤v0F0∑idiTi≤v0sF0<HF0.(3.14)\sum_i d_iw_i\leq\frac{v_0}{F_0}\sum_i d_iT_i\leq\frac{v_0s}{F_0}<\frac{H}{F_0}. \tag*{(3.14)}

On ∣t∣=1/2|t|=1/2,

∣τi(t)∣≤∑k≥Ti2−kk≤1.|\tau_i(t)|\leq\sum_{k\geq T_i}\frac{2^{-k}}{k}\leq1.

Cauchy’s coefficient estimate thus bounds the tail coefficient in (3.13) by 2k≤2s2^k \le2^s. From (3.1),

∣ϵi∣≤2Kqi−ν≤2Keνe−νwi.|\epsilon_i| \le2Kq_i^{-\nu} \le2Ke^{\nu}e^{-\nu w_i}.

Moreover (aβ)(a−βd)≤4∣a∣\binom{a}{\beta}\binom{a-\beta}{d} \le4^{|a|} and ∣a∣≤H/w∗|a| \le H/w_*. Combining these inequalities and using (3.14) gives

log⁡∣ξ∣≤−νw(a−β)+νHF0+Hlog⁡2v0+H(log⁡4+log⁡(2K)+ν)w∗.\log|\xi| \le-\nu w(a-\beta)+\frac{\nu H}{F_0}+\frac{H\log2}{v_0}+\frac{H(\log4+\log(2K)+\nu)}{w_*}.

for each nonzero scalar. A zero scalar obeys the required bound as well. Finally, each coordinate of aa and dd is at most HH because wi≥1w_i \ge1, while 0≤k≤H/v00 \le k \le H/v_0. This proves the term count and the Lemma.

Repeated Taylor degrees force a quadratic saving

The Taylor expansion of interpolation determinants eliminates repeated degrees [10 Theorem 1]. Our rows fall into different transverse-index groups, so this cancellation is used only inside a fixed group. The next bound is uniform over all row choices.

Lemma 3.3 (Collision estimate). Choose one translated test row from each row expansion in Lemma 3.2, and remove its scalar factor. Let TT be the resulting square matrix, and let nan_a be the number of its rows with index aa. With

c=log⁡24,Ehol=100Kw0+log⁡2v0+log⁡(200K)w∗,(3.15)c=\frac{\log2}{4},\qquad E_{\mathrm{hol}}=\frac{100K}{w_0}+\frac{\log2}{v_0}+\frac{\log(200K)}{w_*}, \tag*{(3.15)}

there is a quantity ρH→0\rho_H \to0, independent of all these row choices and of the selected columns, such that

∣det⁡T∣≤exp⁡{−c∑ana2+MH(Ehol+ρH)}.(3.16)|\det T| \le\exp\left\{-c\sum_a n_a^2+MH(E_{\mathrm{hol}}+\rho_H)\right\}. \tag*{(3.16)}

Proof. Put R=100KR=100K. Equation (3.10) gives, on ∣z∣≤R|z|\le R,

∣fa,P(z)∣≤exp⁡{H(Rw0+log⁡(2R)w∗)}=:DH.|f_{a,P}(z)|\le\exp\left\{H\left(\frac{R}{w_0}+\frac{\log(2R)}{w_*}\right)\right\}=:D_H.

Expand

fa,P(z)=∑d≥0ca,d,P(z/R)d.f_{a,P}(z)=\sum_{d\ge0}c_{a,d,P}(z/R)^d.

Cauchy’s estimate gives ∣ca,d,P∣≤DH|c_{a,d,P}|\le D_H. A row of TT is a test of order ℓ≤s\ell\le s at some center jj. Since

∣jω+log⁡(1+t)∣≤2π(K−1)+log⁡2<50K=R/2(∣t∣=1/2),|j\omega+\log(1+t)|\le2\pi(K-1)+\log2<50K=R/2\qquad(|t|=1/2),

its value on (z/R)d(z/R)^d has modulus at most 2ℓ2−d2^\ell2^{-d}.

Expand the determinant in these power-series rows. The expansion is absolutely convergent: a coefficient determinant has modulus at most M!DHMM!D_H^M, and the sum of the product bounds 2−d2^{-d} over all degrees is finite. If two rows have the same pair (a,d)(a,d), their coefficient vectors (ca,d,P)P(c_{a,d,P})_P agree, and that summand vanishes. Thus every nonzero summand has distinct degrees within each group aa, and so

∑rowsd≥∑a(na2).\sum_{\mathrm{rows}}d\ge\sum_a\binom{n_a}{2}.

Use half of the geometric decay for this lower bound and sum the other half freely over all nonnegative degrees. Since ∑ℓ≤MH/v0\sum\ell\le MH/v_0, this gives

∣det⁡T∣≤M!DHM2MH/v02−12∑a(na2)(1−2−1/2)−M.|\det T| \le M!D_H^M 2^{MH/v_0}2^{-\frac12\sum_a\binom{n_a}{2}}(1-2^{-1/2})^{-M}.

Because ∑ana=M\sum_a n_a=M, the asserted inequality follows with, for example,

ρH=log⁡M+14log⁡2−log⁡(1−2−1/2)H.\rho_H=\frac{\log M+\frac{1}{4}\log2-\log(1-2^{-1/2})}{H}.

Equation (3.5) shows that ρH→0\rho_H\to0 with the fixed parameters stipulated above.

A comparison with two alternatives

Put

Ean=Etr+Ehol.(3.17)E_{\mathrm{an}}=E_{\mathrm{tr}}+E_{\mathrm{hol}}. \tag*{(3.17)}

Let 0<A<10<A<1 set a cutoff AHAH for transverse weights, and let 0<η<10<\eta<1 be a fraction of rows. The main arithmetic cost is 1−bˉ1-\bar b. In each term of the determinant expansion, if at least ηM\eta M rows have wa≤AHwa\le AH, they give a collision saving; otherwise the rows with wa>AHwa>AH supply approximation-error factors. We seek a saving larger than 1−bˉ+Ear+Ean1-\bar b+E_{\mathrm{ar}}+E_{\mathrm{an}}, and choose AA and η\eta in Section 4.

Proposition 3.4 (Determinant comparison). Let 0<A<10<A<1 and 0<η<10<\eta<1, and define

g=ν(A(1−η)−θ)−(1−θ),L=η2Kθm(m+1)v0Am.(3.18)g=\nu\bigl(A(1-\eta)-\theta\bigr)-(1-\theta),\qquad L=\frac{\eta^2K\theta^m}{(m+1)v_0A^m}. \tag*{(3.18)}

The approximations (3.1) and the interpolation hypotheses cannot hold simultaneously if

g>0,Ear+Ean<g,cL>1+Ear+Ean.(3.19)g>0,\qquad E_{\mathrm{ar}}+E_{\mathrm{an}}<g,\qquad cL>1+E_{\mathrm{ar}}+E_{\mathrm{an}}. \tag*{(3.19)}

Proof. Let

DA(H)=#{a∈Z≥0m:wa≤AH},LH=η2MHDA(H).D_A(H)=\#\{a\in\mathbb{Z}_{\ge0}^m:wa\le AH\},\qquad L_H=\frac{\eta^2M}{HD_A(H)}.

The simplex count, now in dimension mm, and (3.5) show that

DA(H)∼(AH)mm!∏iwi,LH⟶L.D_A(H)\sim\frac{(AH)^m}{m!\prod_iw_i},\qquad L_H\longrightarrow L.

Expand ΔH\Delta_H by the row identities in Lemma 3.2. For a choice of terms with indices aρa_\rho, the product of their scalar factors has modulus at most

exp⁡{−ν∑ρwaρ+νMHbˉ+MHEtr}.\exp\left\{-\nu\sum_\rho w_{a_\rho}+\nu MH\bar b+MHE_{\mathrm{tr}}\right\}.

There are at most QHMQ_H^M term choices. Apply Lemma 3.3 to each one. Suppose first that at least ηM\eta M of its indices obey wa≤AHwa\le AH. There are at most DA(H)D_A(H) such indices, so Cauchy–Schwarz gives

∑ana2≥(ηM)2DA(H)=MHLH.\sum_a n_a^2\ge\frac{(\eta M)^2}{D_A(H)}=MHL_H.

The scalar main exponent −ν∑ρw(aρ−βρ)-\nu\sum_{\rho}w(a_{\rho}-\beta_{\rho}) is nonpositive, because aρ≥βρa_{\rho}\ge\beta_{\rho}. Discarding it leaves an upper bound −cLH+Ean+ρH-cL_H+E_{\rm an}+\rho_H after division by MHMH.

In the other case, more than (1−η)M(1-\eta)M indices have wa>AHw a>AH. Hence ∑ρwaρ≥MHA(1−η)\sum_{\rho}w a_{\rho}\ge MHA(1-\eta). Discarding the nonpositive collision term leaves the upper bound −ν(A(1−η)−bˉ)+Ean+ρH-\nu(A(1-\eta)-\bar b)+E_{\rm an}+\rho_H.

Taking absolute values before summing the determinant expansion gives

log⁡∣ΔH∣MH≤Ean+εH+max⁡{−cLH,−ν(A(1−η)−bˉ)},(3.20)\frac{\log\lvert\Delta_H\rvert}{MH}\le E_{\rm an}+\varepsilon_H+\max\{-cL_H,-\nu(A(1-\eta)-\bar b)\}, \tag*{(3.20)}
εH=ρH+log⁡QHH⟶0.\varepsilon_H=\rho_H+\frac{\log Q_H}{H}\longrightarrow0.

All bounds here are uniform over the row-term choices.

For the second alternative, the gap between the two main exponents is at least gg, since bˉ≤θ\bar b\le\theta gives

ν(A(1−η)−bˉ)−(1−bˉ)=νA(1−η)−1−(ν−1)bˉ≥g.\nu(A(1-\eta)-\bar b)-(1-\bar b)=\nu A(1-\eta)-1-(\nu-1)\bar b\ge g.

Under (3.19), both quantities inside the maximum in (3.20), after adding Ean+εHE_{\rm an}+\varepsilon_H, are strictly less than −(1−bˉ)−Ear-(1-\bar b)-E_{\rm ar} for all sufficiently large HH. For the first quantity, use LH→LL_H\to L and 1−bˉ≤11-\bar b\le1; for the second, use the displayed uniform gap. This contradicts Lemma 3.1.

Choice of parameters and proof of Theorem 1.1

We now combine the interpolation theorem and the determinant estimates. The order of choices is essential: the dimension is fixed before the approximation scales, and all these data are fixed before the polynomial degree tends to infinity.

Lemma 4.1. For every real ν>2\nu>2, there are positive rational numbers θ\theta, AA, BB, CC such that

0<θ<A<B<1,ν(A−θ)>1−θ,C>1,B<1/C,B<Cθ<1.(4.1)0<\theta<A<B<1,\qquad\nu(A-\theta)>1-\theta,\qquad C>1,\qquad B<1/C,\qquad B<C\theta<1. \tag*{(4.1)}

One can then choose 0<η<10<\eta<1 such that

g:=ν(A(1−η)−θ)−(1−θ)>0.(4.2)g:=\nu(A(1-\eta)-\theta)-(1-\theta)>0. \tag*{(4.2)}

Proof. Choose a rational bb with 1/2<b<1−1/ν1/2<b<1-1/\nu. For a sufficiently small positive rational δ\delta, put θ=1−δ\theta=1-\delta and A=1−bδA=1-b\delta. Then 0<θ<A<10<\theta<A<1, and

ν(A−θ)−(1−θ)=(ν(1−b)−1)δ>0,\nu(A-\theta)-(1-\theta)=(\nu(1-b)-1)\delta>0,

whereas

θ−A2=(2b−1)δ−b2δ2>0.\theta-A^2=(2b-1)\delta-b^2\delta^2>0.

It follows that the interval (A/θ,1/A)(A/\theta,1/A) is nonempty. Choose a rational CC in this interval. Since A>θA>\theta, we have C>1C>1; since θ<A\theta<A, we also have Cθ<θ/A<1C\theta<\theta/A<1. Now choose a rational BB between AA and min⁡(1/C,Cθ)\min(1/C,C\theta). This proves (4.1). Finally, the strict inequality at η=0\eta=0 allows a sufficiently small η>0\eta>0 in (4.2).

The two inequalities used in this construction have different roles. The inequality ν(A−θ)>1−θ\nu(A-\theta)>1-\theta supplies the approximation-error gap. The inequality A2<θA^2<\theta permits A/θ<C<1/AA/\theta<C<1/A, and hence a choice of BB for which CB<1CB<1, Cθ/B>1C\theta/B>1, and B/A>1B/A>1. With the full-simplex counts of Section 3, these three ratios make the dimension-dependent errors tend to zero while the collision saving tends to infinity. We now choose one finite dimension realizing both requirements; it will remain fixed throughout the degree limit.

Proof of Theorem 1.1. Fix ν>2\nu> 2. Suppose for a contradiction that there are arbitrarily large positive integers qq for which some p∈Zp \in\mathbb{Z} satisfies

∣π−pq∣≤q−ν.(4.3)\left|\pi-\frac{p}{q}\right|\le q^{-\nu}. \tag*{(4.3)}

Fix θ\theta, AA, BB, CC, η\eta, gg from Lemma 4.1, and put ε0=min⁡(g/2,1/2)\varepsilon_0=\min(g/2,1/2). First choose F0>2/θF_0>2/\theta so large that ν/F0<ε0/3\nu/F_0<\varepsilon_0/3.

For an integer mm, set

K=⌊Cm⌋,w0=B−m,v0=2Kθmw0.(4.4)K=\left\lfloor C^m\right\rfloor,\qquad w_0=B^{-m},\qquad v_0=2K\theta^m w_0. \tag*{(4.4)}

These are admissible rational interpolation data:

Kθm≤(Cθ)m<1,Kw0v0θm=12.(4.5)K\theta^m\le(C\theta)^m<1,\qquad K\frac{w_0}{v_0}\theta^m=\frac{1}{2}. \tag*{(4.5)}

The relevant limits as m→∞m\to\infty are

Kw0≤(CB)m⟶0,v0∼2(CθB)m⟶∞,mv0⟶0.(4.6)\frac{K}{w_0}\le(CB)^m\longrightarrow0,\qquad v_0\sim2\left(\frac{C\theta}{B}\right)^m\longrightarrow\infty,\qquad\frac{m}{v_0}\longrightarrow0. \tag*{(4.6)}

With the notation of Proposition 3.4, these choices give

L=η2Kθm(m+1)v0Am=η2(B/A)m2(m+1)⟶∞.(4.7)L=\frac{\eta^2K\theta^m}{(m+1)v_0A^m}=\frac{\eta^2(B/A)^m}{2(m+1)}\longrightarrow\infty. \tag*{(4.7)}

Thus, with Λ=4log⁡2\Lambda=4\log2 and c=(log⁡2)/4c=(\log2)/4, choose mm large enough that

ΛF0m+2log⁡2v0+100Kw0<ε03,cL>2.(4.8)\frac{\Lambda F_0m+2\log2}{v_0}+\frac{100K}{w_0}<\frac{\varepsilon_0}{3},\qquad cL>2. \tag*{(4.8)}

Fix this mm, and hence KK, w0w_0, v0v_0.

The remaining constants are now fixed. Choose approximations pi/qip_i/q_i satisfying (4.3), with wi=⌈log⁡qi⌉w_i=\lceil\log q_i\rceil, successively sufficiently large for Theorem 2.1 and, in addition, for

Λ∑i=1m1wi+θ+log⁡4+log⁡(2K)+ν+log⁡(200K)w∗<ε03,w∗=min⁡i>0wi.(4.9)\Lambda\sum_{i=1}^{m}\frac{1}{w_i}+\frac{\theta+\log4+\log(2K)+\nu+\log(200K)}{w_*}<\frac{\varepsilon_0}{3},\qquad w_*=\min_{i>0}w_i. \tag*{(4.9)}

This is possible: first impose a sufficiently large lower bound on every wiw_i, using ∑i1/wi≤m/w∗\sum_i1/w_i\le m/w_*, and then impose the successive geometric thresholds. The assumed denominators are unbounded, so every finite sequence of such requirements can be met. The thresholds for weight separation are independent of the centers. For sufficiently large qiq_i, pi≠0p_i\ne0, and hence cji=jric_{ji}=jr_i, ri=2ipi/qir_i=2ip_i/q_i, are distinct across jj in each coordinate. No independence between different coordinates is required.

Using (3.6), (3.12), (3.15), and (3.17), the sum of errors is exactly

Ear+Ean=νF0+ΛF0m+2log⁡2v0+100Kw0+Λ∑i1wi+θ+log⁡4+log⁡(2K)+ν+log⁡(200K)w∗.\begin{aligned} E_{\rm ar}+E_{\rm an} &=\frac{\nu}{F_0}+\frac{\Lambda F_0m+2\log2}{v_0}+\frac{100K}{w_0}\\ &\quad+\Lambda\sum_i\frac{1}{w_i}+\frac{\theta+\log4+\log(2K)+\nu+\log(200K)}{w_*}. \end{aligned}

Our three choices make this less than ε0\varepsilon_0. In particular it is less than gg, while cL>2>1+Ear+EancL>2>1+E_{\rm ar}+E_{\rm an}. All hypotheses of Proposition 3.4 now hold, a contradiction. The degree HH in that Proposition tends to infinity only after the dimension, weights, and centers just chosen are fixed.

We have excluded (4.3) for arbitrarily large qq, for each fixed ν>2\nu> 2. This gives the required eventual lower bound, in fact with a strict inequality. The contradiction allowed unreduced fractions and zero error. If π\pi were rational, exact representations with arbitrarily large denominators would contradict it; hence π\pi is irrational.

Finally divide the unit interval into NN equal parts and apply pigeonhole to 0,π,…,Nπ0,\pi,\ldots,N\pi modulo one. There exist p∈Zp \in\mathbb{Z} and 1≤q≤N1 \le q \le N such that

0<∣π−pq∣≤1qN≤1q2.0 < \left|\pi-\frac{p}{q}\right| \le\frac{1}{qN} \le\frac{1}{q^2}.

After reduction, the same error is at most the inverse square of the reduced denominator. These errors tend to zero as N→∞N \to\infty; irrationality forces the reduced denominators to be unbounded. Every exponent less than two therefore occurs infinitely often in the defining inequality. Hence μ(π)≥2\mu(\pi) \ge2, and the upper bound already proved gives μ(π)=2\mu(\pi) = 2.

Flint–Hills series and its generalization

We first prove Corollary 1.2. Alekseyev showed that convergence of the classical Flint–Hills series requires μ(π)≤5/2\mu(\pi) \le5/2 [1 Corollary 4]; Meiburg proved that μ(π)<5/2\mu(\pi) < 5/2 is sufficient [15 Theorem 2.5]. We include the short spacing argument needed for the consequence of Theorem 1.1. Write ∥x∥=min⁡p∈Z∣x−p∣\lVert x\rVert= \min_{p\in\mathbb{Z}} |x-p| for distance to the nearest integer.

Lemma 5.1 (Dyadic spacing estimate). Let α>0\alpha> 0 be irrational. Suppose that, for some c>0c > 0 and 1<ν<5/21 < \nu< 5/2,

∥qα∥≥cq1−ν(q∈Z, q≥1).\lVert q\alpha\rVert\ge cq^{1-\nu} \qquad(q \in\mathbb{Z},\ q \ge1).

Then

∑q=1∞1q3∥qα∥2<∞.\sum_{q=1}^{\infty} \frac{1}{q^3\lVert q\alpha\rVert^2} < \infty.

Proof. Fix a positive integer KK, and put d=c(2K)1−νd = c(2K)^{1-\nu}. For K≤q<2KK \le q < 2K, the points qαq\alpha on the circle R/Z\mathbb{R}/\mathbb{Z} have distance at least dd from zero. Two distinct such points also have circle distance at least dd: apply the hypothesis to their nonzero integer difference, whose absolute value is less than 2K2K, and use 1−ν<01-\nu< 0.

On either half-circle starting at zero, arrange the distances in increasing order. Their first distance is at least dd, and each successive distance increases by at least dd. Thus these distances are at least d,2d,3d,…d,2d,3d,\ldots. No positive integer multiple of α\alpha lies at either endpoint of a half-circle. Consequently

∑K≤q<2K1q3∥qα∥2≤2K3d2∑j=1∞1j2=O(K2ν−5).\sum_{K\le q<2K}\frac{1}{q^3\lVert q\alpha\rVert^2} \le\frac{2}{K^3d^2}\sum_{j=1}^{\infty}\frac{1}{j^2} =O(K^{2\nu-5}).

The implied constant depends only on cc and ν\nu. Since 2ν−5<02\nu- 5 < 0, summing over K=1,2,4,…K = 1, 2, 4, \ldots proves the assertion.

Proof of Corollary 1.2. Fix a real number ν\nu with 2<ν<5/22 < \nu< 5/2, and choose a positive integer QQ as in Theorem 1.1. Taking a nearest integer numerator in that theorem gives

∥qπ∥≥q1−ν(q≥Q).\lVert q\pi\rVert\ge q^{1-\nu} \qquad(q \ge Q).

The same theorem has established irrationality of π\pi. Hence

c=min⁡({1}∪{qν−1∥qπ∥:q∈Z, 1≤q<Q})>0.c=\min\left(\{1\}\cup\left\{q^{\nu-1}\lVert q\pi\rVert:q\in\mathbb{Z},\ 1\le q<Q\right\}\right)>0.

It follows that ∥qπ∥≥cq1−ν\lVert q\pi\rVert\ge cq^{1-\nu} for every positive integer qq, including the finitely many exceptions below QQ. Lemma 5.1 therefore gives

∑q=1∞1q3∥qπ∥2<∞.(5.1)\sum_{q=1}^{\infty}\frac{1}{q^3\lVert q\pi\rVert^2}<\infty. \tag*{(5.1)}

For each positive integer nn, choose a nearest nonnegative integer qq to n/πn/\pi, and group the integers nn by qq. Then ∣n−qπ∣≤π/2|n-q\pi|\le\pi/2. The group with q=0q=0 is finite, and its terms in the Flint–Hills series are finite because irrationality of π\pi excludes sin⁡n=0\sin n=0 for a positive integer nn. For each q≥1q\ge1, its group lies in an interval of length π<4\pi<4, so contains at most four integers. Every integer in that group satisfies

n≥π(q−1/2)≥πq2.n\ge\pi(q-1/2)\ge\frac{\pi q}{2}.

Concavity of sine on [0,π/2][0,\pi/2] also gives

∣sin⁡n∣=∣sin⁡(n−qπ)∣≥2π∣n−qπ∣≥2π∥qπ∥.|\sin n|=|\sin(n-q\pi)|\ge\frac{2}{\pi}|n-q\pi|\ge\frac{2}{\pi}\lVert q\pi\rVert.

The contribution of the group indexed by q≥1q\ge1 is consequently at most

8πq3∥qπ∥2.\frac{8}{\pi q^3\lVert q\pi\rVert^2}.

Summing this bound and using (5.1) proves convergence of ∑n≥1n−3sin⁡−2n\sum_{n\ge1}n^{-3}\sin^{-2}n, with angles in radians.

The same spacing argument gives the convergence criterion for the two-parameter family.

Corollary 5.2 (Generalized Flint–Hills series). For fixed real numbers a,b>0a,b>0, the series

∑n=1∞1na∣sin⁡n∣b\sum_{n=1}^{\infty}\frac{1}{n^a|\sin n|^b}

with angles in radians converges if and only if a>max⁡{1,b}a>\max\{1,b\}.

Proof. Suppose first that a>max⁡{1,b}a>\max\{1,b\}, and choose ε>0\varepsilon>0 so that a>max⁡{1,b}+bεa>\max\{1,b\}+b\varepsilon. Theorem 1.1, with the finitely many exceptional denominators absorbed into a positive constant as above, gives ∥qπ∥≥cεq−1−ε\lVert q\pi\rVert\ge c_\varepsilon q^{-1-\varepsilon} for all q≥1q\ge1. For an integer K≥1K\ge1, put d=cε(2K)−1−εd=c_\varepsilon(2K)^{-1-\varepsilon}. As in the proof of Lemma 5.1, the points qπq\pi on R/Z\mathbb{R}/\mathbb{Z} with K≤q<2KK\le q<2K are mutually dd-separated and at least dd from zero. There are at most KK points, so the half-circle ordering gives

∑K≤q<2K1qa∥qπ∥b≤2K−ad−b∑j=1Kj−b≪a,b,ε{K1−a+bε,0<b<1,K1−a+εlog⁡(2K),b=1,Kb−a+bε,b>1.\sum_{K\le q<2K}\frac{1}{q^a\lVert q\pi\rVert^b} \le2K^{-a}d^{-b}\sum_{j=1}^{K}j^{-b} \ll_{a,b,\varepsilon} \begin{cases} K^{1-a+b\varepsilon}, & 0<b<1,\\ K^{1-a+\varepsilon}\log(2K), & b=1,\\ K^{b-a+b\varepsilon}, & b>1. \end{cases}

Each power of KK is negative by the choice of ε\varepsilon; summing over K=1,2,4,…K = 1, 2, 4, \ldots, including the logarithmic factor when b=1b = 1, proves convergence of ∑q≥1q−a∥qπ∥−b\sum_{q \ge1} q^{-a}\lVert q\pi\rVert^{-b}. Use the same nearest-multiple groups as in the preceding proof. The q=0q = 0 group is finite, while the group indexed by q≥1q \ge1 contributes at most

4(2/π)a(π/2)bq−a∥qπ∥−b.4(2/\pi)^a(\pi/2)^b q^{-a}\lVert q\pi\rVert^{-b}.

This proves the required convergence.

If a≤1a \le1, including the boundary a=1a = 1, then ∣sin⁡n∣≤1|\sin n| \le1 compares the series from below with the divergent series ∑n−a\sum n^{-a}. It remains to consider 1<a≤b1 < a \le b. Let pj/qjp_j/q_j be the continued-fraction convergents to π\pi, whose positive integer numerators tend to infinity. They satisfy

∣sin⁡pj∣=∣sin⁡(pj−πqj)∣≤∣pj−πqj∣<qj−1.|\sin p_j| = |\sin(p_j-\pi q_j)| \le|p_j-\pi q_j| < q_j^{-1}.

Since pj/qj→πp_j/q_j \to\pi, eventually pj≤(π+1)qjp_j \le(\pi+1)q_j, and hence

1pja∣sin⁡pj∣b>pj−aqjb≥(π+1)−bpjb−a.\frac{1}{p_j^a|\sin p_j|^b} > p_j^{-a}q_j^b \ge(\pi+1)^{-b}p_j^{b-a}.

These summands are bounded away from zero when a=ba = b, and tend to infinity when a<ba < b. Thus the series also diverges throughout 1<a≤b1 < a \le b, including its boundary a=b>1a = b > 1. ∎

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