{"title":"High-order lifting for polynomial Sylvester matrices","authors":"Clément Pernet , Hippolyte Signargout , Gilles Villard","doi":"10.1016/j.jco.2023.101803","DOIUrl":null,"url":null,"abstract":"<div><p>A new algorithm is presented for computing the resultant of two generic bivariate polynomials over an arbitrary field. For <span><math><mi>p</mi><mo>,</mo><mi>q</mi></math></span> in <span><math><mi>K</mi><mo>[</mo><mi>x</mi><mo>,</mo><mi>y</mi><mo>]</mo></math></span> of degree <em>d</em> in <em>x</em> and <em>n</em> in <em>y</em>, the resultant with respect to <em>y</em> is computed using <span><math><mi>O</mi><mo>(</mo><msup><mrow><mi>n</mi></mrow><mrow><mn>1.458</mn></mrow></msup><mi>d</mi><mo>)</mo></math></span> arithmetic operations if <span><math><mi>d</mi><mo>=</mo><mi>O</mi><mo>(</mo><msup><mrow><mi>n</mi></mrow><mrow><mn>1</mn><mo>/</mo><mn>3</mn></mrow></msup><mo>)</mo></math></span>. For <span><math><mi>d</mi><mo>=</mo><mn>1</mn></math></span>, the complexity estimate is therefore reconciled with the estimates of Neiger et al. 2021 for the related problems of modular composition and characteristic polynomial in a univariate quotient algebra. The 3/2 barrier in the exponent of <em>n</em> is crossed for the first time for the resultant. The problem is related to that of computing determinants of structured polynomial matrices. We identify new advanced aspects of structure for a polynomial Sylvester matrix. This enables to compute the determinant by mixing the baby steps/giant steps approach of Kaltofen and Villard 2005, until then restricted to the case <span><math><mi>d</mi><mo>=</mo><mn>1</mn></math></span> for characteristic polynomials, and the high-order lifting strategy of Storjohann 2003 usually reserved for dense polynomial matrices.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"80 ","pages":"Article 101803"},"PeriodicalIF":1.8000,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X23000729/pdfft?md5=72b813e3258f79c8cf5a380cd73b1e8f&pid=1-s2.0-S0885064X23000729-main.pdf","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Complexity","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0885064X23000729","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 1
Abstract
A new algorithm is presented for computing the resultant of two generic bivariate polynomials over an arbitrary field. For in of degree d in x and n in y, the resultant with respect to y is computed using arithmetic operations if . For , the complexity estimate is therefore reconciled with the estimates of Neiger et al. 2021 for the related problems of modular composition and characteristic polynomial in a univariate quotient algebra. The 3/2 barrier in the exponent of n is crossed for the first time for the resultant. The problem is related to that of computing determinants of structured polynomial matrices. We identify new advanced aspects of structure for a polynomial Sylvester matrix. This enables to compute the determinant by mixing the baby steps/giant steps approach of Kaltofen and Villard 2005, until then restricted to the case for characteristic polynomials, and the high-order lifting strategy of Storjohann 2003 usually reserved for dense polynomial matrices.
期刊介绍:
The multidisciplinary Journal of Complexity publishes original research papers that contain substantial mathematical results on complexity as broadly conceived. Outstanding review papers will also be published. In the area of computational complexity, the focus is on complexity over the reals, with the emphasis on lower bounds and optimal algorithms. The Journal of Complexity also publishes articles that provide major new algorithms or make important progress on upper bounds. Other models of computation, such as the Turing machine model, are also of interest. Computational complexity results in a wide variety of areas are solicited.
Areas Include:
• Approximation theory
• Biomedical computing
• Compressed computing and sensing
• Computational finance
• Computational number theory
• Computational stochastics
• Control theory
• Cryptography
• Design of experiments
• Differential equations
• Discrete problems
• Distributed and parallel computation
• High and infinite-dimensional problems
• Information-based complexity
• Inverse and ill-posed problems
• Machine learning
• Markov chain Monte Carlo
• Monte Carlo and quasi-Monte Carlo
• Multivariate integration and approximation
• Noisy data
• Nonlinear and algebraic equations
• Numerical analysis
• Operator equations
• Optimization
• Quantum computing
• Scientific computation
• Tractability of multivariate problems
• Vision and image understanding.