论文标题
稀疏多项式求解的复杂性2:重新归一化
Complexity of Sparse Polynomial Solving 2: Renormalization
论文作者
论文摘要
引入了复的同型延续,作为解决多项式方程式稀疏系统或指数和指数总和稀疏系统的工具。延续成本取决于重新规定的条件长度,该长度定义为沿所有升起的重新归一化路径的条件编号的线积分。 本文开发的理论导致了一种延续算法跟踪具有相同结构的两个通用系统之间的所有解决方案。从某种意义上说,该算法是随机的,它遵循两个系统之间的随机路径。成功的可能性是其中之一。为了产生预期的成本约束,仅引入了几个不变的次数。例如,混合区域是一个QuermassIntegral,其以相同的方式将表面积概括为混合体积概括了普通体积。面向风扇中每个1锥和每个支撑层的尺寸测量,支撑超平面与最近的顶点有多近。一旦固定支持,预期的成本就取决于仅通过两个不变的输入系数:重新归一化的感谢您的条件数和系数绝对值的不平衡。这导致了以这两个不变性的方式结合多项式求解的非均匀多项式复杂性。
Renormalized homotopy continuation on toric varieties is introduced as a tool for solving sparse systems of polynomial equations, or sparse systems of exponential sums. The cost of continuation depends on a renormalized condition length, defined as a line integral of the condition number along all the lifted renormalized paths. The theory developed in this paper leads to a continuation algorithm tracking all the solutions between two generic systems with the same structure. The algorithm is randomized, in the sense that it follows a random path between the two systems. The probability of success is one. In order to produce an expected cost bound, several invariants depending solely of the supports of the equations are introduced. For instance, the mixed area is a quermassintegral that generalizes surface area in the same way that mixed volume generalizes ordinary volume. The facet gap measures for each 1-cone in the fan and for each support polytope, how close is the supporting hyperplane to the nearest vertex. Once the supports are fixed, the expected cost depends on the input coefficients solely through two invariants: the renormalized toric condition number and the imbalance of the absolute values of the coefficients. This leads to a non-uniform polynomial complexity bound for polynomial solving in terms of those two invariants.