On the transcendence of moduli of the jacobian elliptic functions

Let sn₁ z and sn₂ z be the Jacobian elliptic functions of moduli κ ₁ and κ ₂, 0 < k₁² \kappa_1^2 < 1, 0 < k₂² \kappa_2^2 < 1, τ ₁ and τ ₂ be the values of the modular variable, and θ ₃(τ ₁) and θ ₃(τ ₂) be the theta constants. In this paper, the set κ ₁, κ ₂, θ ₃(τ ₁), and θ ₃(τ ₂) is shown to contain a transcendental number, provided that τ ₁ /τ ₂ is irrational.     

Equations fonctionnelles et estimations de normes de matrices

We solve independently the equations 1/θ(x)θ(y)=ψ(x)−ψ(y)+φ(x−y)/θ(x−y) and 1/θ(x)θ(y)=σ(x)−σ(y)/θ(x−y)+τ(x)τ(y), τ(0)=0. In both cases we find θ²=aθ⁴+bθ²+c. We deduce estimates for the spectral radius of a matrix of type(1/θ(x _r −x _s )) (the accent meaning that the coefficients of the main diagonal are zero) and we study the case where thex _r are equidistant.

Dédié to à Monsieur le Professeur Otto Haupt à l'occasion de son cententiare avec les meilleurs voeux     

A criterion for regular sequences

LetR be a commutative noetherian ring and ƒ₁, …, ƒ_r ∃ R. In this article we give (cf. the Theorem in §2) a criterion for ƒ₁, …, ƒ_r to be regular sequence for a finitely generated module overR which strengthens and generalises a result in [2]. As an immediate consequence we deduce that if V(g ₁, …,g _r ) ⊆ V(ƒ₁, …, ƒ_r) in SpecR and if ƒ₁, …, ƒ_r is a regular sequence inR, theng ₁, …,g _r is also a regular sequence inR.     

Projective bases of division algebras and groups of central type

Letk be a field. For each finite groupG and two-cocylef inZ ² (G, k ^x ) (with trivial action), one can form the twisted group algebra wherex _σ x _τ =f(σ,τ)x _στ for all σ, τ∃G. Our main result is a short list ofp-groups containing all thep-groupsG for which there is a fieldk and a cocycle such that the resulting twisted group algebra is ak-central division algebra. We also complete the proof (presented in all but one case in a previous paper by Aljadeff and Haile) that everyk-central division algebra that is a twisted group algebra is isomorphic to a tensor product of cyclic algebras.     

(2,k)-Factor-Critical Graphs and Toughness

 A graph is (r,k)-factor-critical if the removal of any set of k vertices results in a graph with an r-factor (i.e. with an r-regular spanning subgraph). We show that every τ-tough graph of order n with τ≥2 is (2,k)-factor-critical for every non-negative integer k≤min{2τ−2, n−3}, thus proving a conjecture as well as generalizing the main result of Liu and Yu in [4]. Received: December 16, 1996 / Revised: September 17, 1997     

Small fractional parts of additive forms

Letf(x)=θ₁ x ₁ ^k +...+θ _s x _s ^k be an additive form with real coefficients, and ∥α∥ = min {|α-u|:uεℤ} denote the distance fromα to the nearest integer. We show that ifθ ₁,…,θ _s , are algebraic ands = 4k then there are integersx ₁,…,x _s , satisfying l ≤x ₁,≤ N and ∥f(x)∥ ≤ N ^E , withE = − 1 + 2/e. Whens = λk, 1 ≤λ ≤ 2k, the exponentE may be replaced byλE/4, and if we drop the condition thatθ ₁,…,θ _s , be algebraic then the result holds for almost all values of θεℝ ^s . Whenk ≥ 6 is small a better exponent is obtained using Heath-Brown’s version of Weyl’s estimate.     

Reciprocity transformations for radial nonlinear heat equations

Nonlocal transformations of some quasilinear parabolic equations which describe spherically symmetric heat conduction and diffusion processes are considered. One of them transforms the equationr ⁿ⁻¹θ _t =(r ⁿ⁻¹|θ _r | ^l θ _r ) _r to an equation of the same type but with a different value of the exponent n. Another transformation reduces the equationr ⁿ⁻¹θ _t =(r ⁿ⁻¹θ⁻²θ _r ) _r to an equation with coefficients which do not depend on the space variable. The third nonlocal transformation preserves the equationrθ _t =(rθ ⁻¹θ _r ) _r . Some exact solutions of the mentioned equations are analyzed. Bibliography: 15 titles. Dedicated to V. A. Solonnikov on his sixtieth anniversary Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 213, 1994, pp. 151–163. Translated by S. Yu. Pilyugin     

Inverse problems for Sturm—Liouville operators with potentials in Sobolev spaces: Uniform stability

Two inverse problems for the Sturm-Liouville operator Ly = s-y″ + q(x)y on the interval [0, fy] are studied. For θ ⩾ 0, there is a mapping F:W ₂^θ → l _B ^θ, F(σ) = {s _k }₁^∞, related to the first of these problems, where W ₂^∞ = W ₂^∞[0, π] is the Sobolev space, σ = ∫ q is a primitive of the potential q, and l _B ^θ is a specially constructed finite-dimensional extension of the weighted space l ₂^θ, where we place the regularized spectral data s = {s _k }₁^∞ in the problem of reconstruction from two spectra. The main result is uniform lower and upper bounds for ∥σ - σ₁∥_θ via the l _B ^θ-norm ∥s − s₁∥_θ of the difference of regularized spectral data. A similar result is obtained for the second inverse problem, that is, the problem of reconstructing the potential from the spectral function of the operator L generated by the Dirichlet boundary conditions. The result is new even for the classical case q ∈ L ₂, which corresponds to θ = 1.     

Subsequences of normal sequences

In this paper, we characterize a set of indices τ={τ(0)<τ(1)<…} such that forany normal sequence (α(0), α(1),…) of a certain type, the subsequence (α(τ(0)), α(τ(1)),…) is a normal sequence of the same type. Assume that_n→∞. Then, we prove that τ has this property if and only if the 0–1 sequence (θ _τ (0), whereθ _τ (i)=1 or 0 according asi∈{τ(j);j=0, 1,…} or not, iscompletely deterministic in the sense of B. Weiss.     

Efficient Subspace Approximation Algorithms

We consider the problem of fitting a subspace of a specified dimension k to a set P of n points in ℝ ^d . The fit of a subspace F is measured by the L _τ norm, that is, it is defined as the τ-root of the sum of the τth powers of the Euclidean distances of the points in P from F, for some τ≥1. Our main result is a randomized algorithm that takes as input P, k, and a parameter 0<ε<1; runs in nd ·2^{O(\fractk2e log2 \frac ke)}nd \cdot2^{O(\frac{\tau k^{2}}{\varepsilon} \log^{2} \frac {k}{\varepsilon})} time, and returns a k-subspace that with probability at least 1/2 has a fit that is at most (1+ε) times that of the optimal k-subspace.     

Sums of two k-th powers: an Omega estimate for the error term

The arithmetic function r _k (n) counts the number of ways to write a natural number n as a sum of two k-th powers (k ≧ 2 fixed). The investigation of the asymptotic behaviour of the Dirichlet summatory function of r _k(n) leads in a natural way to a certain error term P _k(t). In this article, we establish an Ω-estimate for P _k(t) (k τ; 2 arbitrary) which is essentially as sharp as the best known one in the classic case k=2. This article is part of a research project supported by the Austrian Science Foundation (Nr. P 9892-PHY).     

Uniform Spacing of Zeros of Orthogonal Polynomials

It is shown that for doubling weights, the zeros of the associated orthogonal polynomials are uniformly spaced in the sense that if cos θ _m,k , θ _m,k ∈[0,π] are the zeros of the m-th orthogonal polynomial associated with w, then θ _m,k −θ _m,k+1∼1/m. It is also shown that for doubling weights, neighboring Cotes numbers are of the same order. Finally, it is proved that these two properties are actually equivalent to the doubling property of the weight function.     

Hopf Bifurcations and Oscillatory Instabilities of Spike Solutions for the One-Dimensional Gierer-Meinhardt Model

Summary. In the limit of small activator diffusivity ɛ , the stability of symmetric k -spike equilibrium solutions to the Gierer-Meinhardt reaction-diffusion system in a one-dimensional spatial domain is studied for various ranges of the reaction-time constant τ≥ 0 and the diffusivity D>0 of the inhibitor field dynamics. A nonlocal eigenvalue problem is derived that determines the stability on an O(1) time-scale of these k -spike equilibrium patterns. The spectrum of this eigenvalue problem is studied in detail using a combination of rigorous, asymptotic, and numerical methods. For k=1 , and for various exponent sets of the nonlinear terms, we show that for each D>0 , a one-spike solution is stable only when 0≤ τ<τ ₀ (D) . As τ increases past τ ₀ (D) , a pair of complex conjugate eigenvalues enters the unstable right half-plane, triggering an oscillatory instability in the amplitudes of the spikes. A large-scale oscillatory motion for the amplitudes of the spikes that occurs when τ is well beyond τ ₀ (D) is computed numerically and explained qualitatively. For k≥ 2 , we show that a k -spike solution is unstable for any τ≥ 0 when D>D _k , where D _k >0 is the well-known stability threshold of a multispike solution when τ=0 . For D>D _k and τ≥ 0 , there are eigenvalues of the linearization that lie on the (unstable) positive real axis of the complex eigenvalue plane. The resulting instability is of competition type whereby spikes are annihilated in finite time. For 0<D<D _k , we show that a k -spike solution is stable with respect to the O(1) eigenvalues only when 0≤ τ<τ ₀ (D;k) . When τ increases past τ ₀ (D;k)>0 , a synchronous oscillatory instability in the amplitudes of the spikes is initiated. For certain exponent sets and for k≥ 2 , we show that τ ₀ (D;k) is a decreasing function of D with τ ₀ (D;k) → τ _0k >0 as D→ D _k ^- .     

Diophantinc approximation by linear forms on manifolds

The following Khintchine-type theorem is proved for manifoldsM embedded in ℝ ^k which satisfy some mild curvature conditions. The inequality |q·x| <Ψ(|q|) whereΨ(r) → 0 asr → ∞ has finitely or infinitely many solutionsqεℤ ^k for almost all (in induced measure) points x onM according as the sum Σ _r ^{= 1/∞} Ψ(r)r ^k−2 converges or diverges (the divergent case requires a slightly stronger curvature condition than the convergent case). Also, the Hausdorff dimension is obtained for the set (of induced measure 0) of point inM satisfying the inequality infinitely often whenψ(r) =r ^−t . τ >k − 1.     

Minimax goodness-of-fit testing in multivariate nonparametric regression

We consider an unknown response function f defined on Δ = [0, 1] ^d , 1 ≤ d ≤ ∞, taken at n random uniform design points and observed with Gaussian noise of known variance. Given a positive sequence r _n → 0 as n → ∞ and a known function f ₀ ∈ L ₂(Δ), we propose, under general conditions, a unified framework for goodness-of-fit testing the null hypothesis H ₀: f = f ₀ against the alternative H ₁: f ∈ $ \mathcal{F} $ \mathcal{F} , ∥f − f ₀∥ ≥ r _n , where $ \mathcal{F} $ \mathcal{F} is an ellipsoid in the Hilbert space L ₂(Δ) with respect to the tensor product Fourier basis and ∥ · ∥ is the norm in L ₂(Δ). We obtain both rate and sharp asymptotics for the error probabilities in the minimax setup. The derived tests are inherently non-adaptive. Several illustrative examples are presented. In particular, we consider functions belonging to ellipsoids arising from the well-known multidimensional Sobolev and tensor product Sobolev norms as well as from the less-known Sloan-Woźniakowski norm and a norm constructed from multivariable analytic functions on the complex strip.     

Cramér-type conditions and quadratic mean differentiability

Summary Let (Ω,A) be a measurable space, let Θ be an open set inR ^k , and let {P _θ; θ∈Θ} be a family of probability measures defined onA. Let μ be a σ-finite measure onA, and assume thatP _θ≪μ for each θ∈Θ. Let us denote a specified version ofdP _θ /d _μ byf(ω; θ). In many large sample problems in statistics, where a study of the log-likelihood is important, it has been convenient to impose conditions onf(ω; θ) similar to those used by Cramér [2] to establish the consistency and asymptotic normality of maximum likelihood estimates. These are of a purely analytical nature, involving two or three pointwise derivatives of lnf(ω; θ) with respect to θ. Assumptions of this nature do not have any clear probabilistic or statistical interpretation. In [10], LeCam introduced the concept of differentially asymptotically normal (DAN) families of distributions. One of the basic properties of such a family is the form of the asymptotic expansion, in the probability sense, of the log-likelihoods. Roussas [14] and LeCam [11] give conditions under which certain Markov Processes, and sequences of independent identically distributed random variables, respectively, form DAN families of distributions. In both of these papers one of the basic assumptions is the differentiability in quadratic mean of a certain random function. This seems to be a more appealing type of assumption because of its probabilistic nature. In this paper, we shall prove a theorem involving differentiability in quadratic mean of random functions. This is done in Section 2. Then, by confining attention to the special case when the random function is that considered by LeCam and Roussas, we will be able to show that the standard conditions of Cramér type are actually stronger than the conditions of LeCam and Roussas in that they imply the existence of the necessary quadratic mean derivative. The relevant discussion is found in Section 3. This research was supported by the National Science Foundation, Grant GP-20036.     

A new technique to compute polygonal schema for 2-manifolds with application to null-homotopy detection

We provide a new technique for deriving optimal-sized polygonal schema for triangulated compact 2-manifolds without boundary inO(n) time, wheren is the size of the given triangulationT. We first derive a polygonal schemaP embedded inT using Seifert-Van Kampen's theorem. A reduced polygonal schemaQ of optimal size is computed fromP, where a surjective map from the vertices ofP is retained to the vertices ofQ. This helps detecting null-homotopic (contractible to a point) cycles. Given a cycle of lengthk, we determine if it is null-homotopic inO(n+k logg) time and in θ(n+k) space, whereg is the genus of the given 2-manifold. The actual contraction for a null-homotopic cycle can be computed in θ(nk) time and space. This is a considerable improvement over the previous best-known algorithm for this problem.     

Approximation of Projections of Random Vectors

Let X be a d-dimensional random vector and X _θ its projection onto the span of a set of orthonormal vectors {θ ₁,…,θ _k }. Conditions on the distribution of X are given such that if θ is chosen according to Haar measure on the Stiefel manifold, the bounded-Lipschitz distance from X _θ to a Gaussian distribution is concentrated at its expectation; furthermore, an explicit bound is given for the expected distance, in terms of d, k, and the distribution of X, allowing consideration not just of fixed k but of k growing with d. The results are applied in the setting of projection pursuit, showing that most k-dimensional projections of n data points in ℝ ^d are close to Gaussian, when n and d are large and k=clog (d) for a small constant c.     

Primarite deL p (l r , 1<p,r<∞

In this article we show that if 1<p, r<∞, the spaceL _p (l _r ) is primary. If we let (h _k ) be the Haar system inL _p and (e _i ) the usual base ofl _r , we give sufficient conditions on a subsequence of (h _k ⊗e _i ) _{k ≧1,i≧1} for it to generate a space isomorphic toL _p (l _r ). We deduce the primarity ofL _p (l _r ).      

A definition of estimator efficiency ink-parameter case

Summary The paper introduces a new definition of efficiency in the multiparameter case (θ₁,...,θ_k) when the variance-covariance matrix of the vector estimator (t ₁, ...t _k) exists. The definition is also applicable to the asymptotically unbiased estimators. The basic idea is that, as we want in general to estimate some function g(θ₁,...θ_k) of the parameters, efficiency of the vector estimator shall be defined as the smallest efficiency of the estimatorg(t ₁, ...t _k),g being regular. It is shown that this definition is asymptotically equivalent to the one obtained by any linear combination of the estimators, as it happens, naturally, for quantile estimation in the location-dispersion case. This efficiency is larger than Cramér efficiency which is, thus, not attained, apart from a very exceptional case. Finally, a lower bound for the asymptotic variance is obtained.