The complexity of class polynomial computation via floating point approximations

Fuente: arXiv
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Auteur principal: Enge, Andreas
Format: Preprint
Publié: 2006
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author Enge, Andreas
author_facet Enge, Andreas
contents We analyse the complexity of computing class polynomials, that are an important ingredient for CM constructions of elliptic curves, via complex floating point approximations of their roots. The heart of the algorithm is the evaluation of modular functions in several arguments. The fastest one of the presented approaches uses a technique devised by Dupont to evaluate modular functions by Newton iterations on an expression involving the arithmetic-geometric mean. It runs in time $O (|D| \log^5 |D| \log \log |D|) = O (|D|^{1 + ε}) = O (h^{2 + ε})$ for any $ε> 0$, where $D$ is the CM discriminant and $h$ is the degree of the class polynomial. Another fast algorithm uses multipoint evaluation techniques known from symbolic computation; its asymptotic complexity is worse by a factor of $\log |D|$. Up to logarithmic factors, this running time matches the size of the constructed polynomials. The estimate also relies on a new result concerning the complexity of enumerating the class group of an imaginary-quadratic order and on a rigorously proven upper bound for the height of class polynomials.
format Preprint
id arxiv_https___arxiv_org_abs_cs_0601104
institution arXiv
publishDate 2006
record_format arxiv
spellingShingle The complexity of class polynomial computation via floating point approximations
Enge, Andreas
Numerical Analysis
Symbolic Computation
Number Theory
We analyse the complexity of computing class polynomials, that are an important ingredient for CM constructions of elliptic curves, via complex floating point approximations of their roots. The heart of the algorithm is the evaluation of modular functions in several arguments. The fastest one of the presented approaches uses a technique devised by Dupont to evaluate modular functions by Newton iterations on an expression involving the arithmetic-geometric mean. It runs in time $O (|D| \log^5 |D| \log \log |D|) = O (|D|^{1 + ε}) = O (h^{2 + ε})$ for any $ε> 0$, where $D$ is the CM discriminant and $h$ is the degree of the class polynomial. Another fast algorithm uses multipoint evaluation techniques known from symbolic computation; its asymptotic complexity is worse by a factor of $\log |D|$. Up to logarithmic factors, this running time matches the size of the constructed polynomials. The estimate also relies on a new result concerning the complexity of enumerating the class group of an imaginary-quadratic order and on a rigorously proven upper bound for the height of class polynomials.
title The complexity of class polynomial computation via floating point approximations
topic Numerical Analysis
Symbolic Computation
Number Theory
url https://arxiv.org/abs/cs/0601104