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Related papers: The multivariate integer Chebyshev problem

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There is a vast theory of Chebyshev and residual polynomials and their asymptotic behavior. The former ones maximize the leading coefficient and the latter ones maximize the point evaluation with respect to an $L^\infty$ norm. We study…

Classical Analysis and ODEs · Mathematics 2021-01-07 Benjamin Eichinger , Milivoje Lukić , Giorgio Young

We analyze decay of Chebyshev coefficients and local Chebyshev approximations for functions of finite regularity on finite intervals, focusing on the framework where the interval length tends to zero while the number of approximation nodes…

Numerical Analysis · Mathematics 2025-09-19 Krishna Yamanappa Poojara , Sabhrant Sachan , Ambuj Pandey

We study the n-dimensional problem of finding the smallest ball enclosing the intersection of p given balls, the so-called Chebyshev center problem (CCB). It is a minimax optimization problem and the inner maximization is a uniform…

Optimization and Control · Mathematics 2019-01-24 Yong Xia , Meijia Yang , Shu Wang

In this paper, a new framework for continuous-time maximum a posteriori estimation based on the Chebyshev polynomial optimization (ChevOpt) is proposed, which transforms the nonlinear continuous-time state estimation into a problem of…

Robotics · Computer Science 2022-07-13 Maoran Zhu , Yuanxin Wu

We focus on computing certified upper bounds for the positive maximal singular value (PMSV) of a given matrix. The PMSV problem boils down to maximizing a quadratic polynomial on the intersection of the unit sphere and the nonnegative…

Optimization and Control · Mathematics 2022-02-18 Victor Magron , Ngoc Hoang Anh Mai , Yoshio Ebihara , Hayato Waki

A class P_{n,m,p}(x) of polynomials is defined. The combinatorial meaning of its coefficients is given. Chebyshev polynomials are the special cases of P_{n,m,p}(x). It is first shown that P_{n,m,p}(x) may be expressed in terms of…

Complex Variables · Mathematics 2008-04-15 Milan Janjic

In this work we present an extension of Chubanov's algorithm to the case of homogeneous feasibility problems over a symmetric cone K. As in Chubanov's method for linear feasibility problems, the algorithm consists of a basic procedure and a…

Optimization and Control · Mathematics 2017-09-27 Bruno F. Lourenço , Tomonari Kitahara , Masakazu Muramatsu , Takashi Tsuchiya

We give a short and elementary proof of an inverse Bernstein-type inequality found by S. Khrushchev for the derivative of a polynomial having all its zeros on the unit circle. The inequality is used to show that equally-spaced points solve…

Metric Geometry · Mathematics 2015-09-23 Tamás Erdélyi , Douglas P. Hardin , Edward B. Saff

A polyhedral convex set optimization problem is given by a set-valued objective mapping from the $n$-dimensional to the $q$-dimensional Euclidean space whose graph is a convex polyhedron. This problem can be seen as the most elementary…

Optimization and Control · Mathematics 2023-04-25 Niklas Hey , Andreas Löhne

We computationally investigate the complete polytope of Bell inequalities for 2 particles with small numbers of possible measurements and outcomes. Our approach is limited by Pitowsky's connection of this problem to the computationally hard…

Quantum Physics · Physics 2023-03-23 Daniel Collins , Nicolas Gisin

We develop a method for determining the density of squarefree values taken by certain multivariate integer polynomials that are invariants for the action of an algebraic group on a vector space. The method is shown to apply to the…

Number Theory · Mathematics 2014-02-04 Manjul Bhargava

We derive a stronger uniqueness result if a function with compact support and its truncated Hilbert transform are known on the same interval by using the Sokhotski-Plemelj formulas. To find a function from its truncated Hilbert transform,…

Machine Learning · Computer Science 2020-02-13 Jason You

We consider the NP-hard problem of minimizing a separable concave quadratic function over the integral points in a polyhedron, and we denote by D the largest absolute value of the subdeterminants of the constraint matrix. In this paper we…

Optimization and Control · Mathematics 2019-08-30 Alberto Del Pia

In this paper, an efficient method is presented for solving three dimensional Volterra integral equations of the second kind with continuous kernel. Shifted Chebyshev polynomial is applied to approximate a solution for these integral…

Numerical Analysis · Mathematics 2016-09-28 Doaa shokry Mohamed

We consider the problem of estimating the support size of a discrete distribution whose minimum non-zero mass is at least $ \frac{1}{k}$. Under the independent sampling model, we show that the sample complexity, i.e., the minimal sample…

Statistics Theory · Mathematics 2016-12-13 Yihong Wu , Pengkun Yang

A Chebyshev expansion is a series in the basis of Chebyshev polynomials of the first kind. When such a series solves a linear differential equation, its coefficients satisfy a linear recurrence equation. We interpret this equation as the…

Symbolic Computation · Computer Science 2013-06-19 Alexandre Benoit , Bruno Salvy

The uniqueness question of the multivariate moment problem is studied by different methods: Hilbert space operators, complex function theory, polynomial approximation, disintegration, integral geometry. Most of the known results in the…

Functional Analysis · Mathematics 2008-10-07 Mihai Putinar , Konrad Schmüdgen

In this article, we study multivariate polynomial interpolation and quadrature rules on non-tensor product node sets related to Lissajous curves and Chebyshev varieties. After classifying multivariate Lissajous curves and the interpolation…

Numerical Analysis · Mathematics 2017-08-23 Peter Dencker , Wolfgang Erb

The best polynomial approximation and Chebyshev approximation are both important in numerical analysis. In tradition, the best approximation is regarded as more better than the Chebyshev approximation, because it is usually considered in…

Numerical Analysis · Mathematics 2021-11-17 Xiaolong Zhang

Perturbation theory is a powerful tool for studying large-scale structure formation in the universe and calculating observables such as the power spectrum or bispectrum. However, beyond linear order, typically this is done by assuming a…

Cosmology and Nongalactic Astrophysics · Physics 2023-08-09 Nicholas Choustikov , Zvonimir Vlah , Anthony Challinor