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Validated numerics for algebraic path tracking

Alexandre Guillemot, Pierre Lairez

TL;DR

Using validated numerical methods, interval arithmetic and Taylor models, a certified predictor-corrector loop for tracking zeros of polynomial systems with a parameter is proposed and a Rust implementation shows tremendous improvement over existing software for certified path tracking.

Abstract

Using validated numerical methods, interval arithmetic and Taylor models, we propose a certified predictor-corrector loop for tracking zeros of polynomial systems with a parameter. We provide a Rust implementation which shows tremendous improvement over existing software for certified path tracking.

Validated numerics for algebraic path tracking

TL;DR

Using validated numerical methods, interval arithmetic and Taylor models, a certified predictor-corrector loop for tracking zeros of polynomial systems with a parameter is proposed and a Rust implementation shows tremendous improvement over existing software for certified path tracking.

Abstract

Using validated numerical methods, interval arithmetic and Taylor models, we propose a certified predictor-corrector loop for tracking zeros of polynomial systems with a parameter. We provide a Rust implementation which shows tremendous improvement over existing software for certified path tracking.
Paper Structure (23 sections, 10 theorems, 22 equations, 1 figure, 1 table, 4 algorithms)

This paper contains 23 sections, 10 theorems, 22 equations, 1 figure, 1 table, 4 algorithms.

Key Result

Theorem 2.1

Let $f : V \to V$ be a continuously differentiable map and let $\rho \in (0,1)$. Let $x\in V$, $r > 0$, and let $A: V\to V$ be a linear map. Assume that for any $u, v\in rB$, Then there is a unique $\zeta \in x + rB$ such that $f(\zeta) = 0$. Moreover, and for any $y \in x + rB$,

Figures (1)

  • Figure 1: Number of iterations performed by algpath (this work) and HomotopyContinuation.jl (noncertified path tracking) in four path tracking problems. We observe that algpath performs typically no more than 5 times more iterations than a state-of-the-art noncertified numerical solver. The ratio is close to 2 on well-conditioned examples (green,0.7804;blue,0.9098] plot[mark=*] coordinates (0,0); and ) but there is much more variability on poor conditioning (, and ).

Theorems & Definitions (12)

  • Theorem 2.1
  • Proposition 3.1
  • Lemma 3.2: Correctness of Algorithm \ref{['algo:M']}
  • Remark 4.1
  • Remark 4.2
  • Theorem 4.3
  • Lemma 4.4
  • Lemma 4.5
  • Lemma 4.6
  • Theorem 5.1
  • ...and 2 more