Computing transcendence and linear relations of 1-periods
Emre Can Sertöz, Joël Ouaknine, James Worrell
TL;DR
The paper provides an algorithmic framework to compute all ${ar{f Q}}$-linear relations among a finite set of $1$-periods, thereby deciding transcendence and equality of periods. It achieves this by grounding $1$-periods in the mixed Hodge structures of punctured curves and in push-pull Jacobian motives, ultimately reducing period-relations to explicit endomorphism data and divisor arithmetic on curves. Central contributions include a complete, effective model for relative algebraic de Rham and Betti realizations, a constructive treatment of $1$-motives and their period relations, and a suite of push-pull, correspondences, and supersaturation techniques that render the Kontsevich–Zagier equality problem tractable in this setting. The methods are computationally explicit, rely on divisor theory on curves, and yield practical tools for both period classification and autonomous differential equations, with broad implications for transcendence and arithmetic geometry.
Abstract
A 1-period is a complex number given by the integral of a univariate algebraic function, where all data involved -- the integrand and the domain of integration -- are defined over algebraic numbers. We give an algorithm that, given a finite collection of 1-periods, computes the space of all linear relations among them with algebraic coefficients. In particular, the algorithm decides whether a given 1-period is transcendental, and whether two 1-periods are equal. This resolves, in the case of 1-periods, a problem posed by Kontsevich and Zagier, asking for an algorithm to decide equality of periods. The algorithm builds on the work of Huber and Wüstholz, who showed that all linear relations among 1-periods arise from 1-motives; we make this perspective effective by reducing the problem to divisor arithmetic on curves and providing the theoretical foundations for a practical and fully explicit algorithm. To illustrate the broader applicability of our methods, we also give an algorithmic classification of autonomous first-order (non-linear) differential equations.
