Fast methods to compute the Riemann zeta function

The Riemann zeta function on the critical line can be computed using a straightforward application of the Riemann-Siegel formula, Sch\"onhage's method, or Heath-Brown's method. The complexities of these methods have exponents 1/2, 3/8 (=0.375), and 1/3 respectively. In this paper, three new fast and potentially practical methods to compute zeta are presented. One method is very simple. Its complexity has exponent 2/5. A second method relies on this author's algorithm to compute quadratic exponential sums. Its complexity has exponent 1/3. The third method employs an algorithm, developed in this paper, to compute cubic exponential sums. Its complexity has exponent 4/13 (approximately, 0.307).Comment: Presentation simplifie

Computing L-series of hyperelliptic curves

We discuss the computation of coefficients of the L-series associated to a hyperelliptic curve over Q of genus at most 3, using point counting, generic group algorithms, and p-adic methods.Comment: 15 pages, corrected minor typo

Accelerating the CM method

Given a prime q and a negative discriminant D, the CM method constructs an elliptic curve E/\Fq by obtaining a root of the Hilbert class polynomial H_D(X) modulo q. We consider an approach based on a decomposition of the ring class field defined by H_D, which we adapt to a CRT setting. This yields two algorithms, each of which obtains a root of H_D mod q without necessarily computing any of its coefficients. Heuristically, our approach uses asymptotically less time and space than the standard CM method for almost all D. Under the GRH, and reasonable assumptions about the size of log q relative to |D|, we achieve a space complexity of O((m+n)log q) bits, where mn=h(D), which may be as small as O(|D|^(1/4)log q). The practical efficiency of the algorithms is demonstrated using |D| > 10^16 and q ~ 2^256, and also |D| > 10^15 and q ~ 2^33220. These examples are both an order of magnitude larger than the best previous results obtained with the CM method.Comment: 36 pages, minor edits, to appear in the LMS Journal of Computation and Mathematic

On the evaluation of some sparse polynomials

We give algorithms for the evaluation of sparse polynomials of the form P=p0 + p1 x + p2 x^4 + ... + p_{n-1} x^{(N-1)^2} for various choices of coefficients . First, we take p_i=p^i, for some fixed p; in this case, we address the question of fast evaluation at a given point in the base ring, and we obtain a cost quasi-linear in sqrt{N}. We present experimental results that show the good behavior of this algorithm in a floating-point context, for the computation of Jacobi theta functions. Next, we consider the case of arbitrary coefficients; for this problem, we study the question of multiple evaluation: we show that one can evaluate such a polynomial at N values in the base ring in subquadratic time