International audienceThe Eocene Hecho Group turbidite system of the Ainsa-Jaca foreland Basin (southcentral Pyrenees) provides an excellent opportunity to constrain compositional variations within the context of spatial and temporal distribution of source rocks during tectonostratigraphic evolution of foreland basins. The complex tectonic setting necessitated the use of petrographic, geochemical and multivariate statistical techniques to achieve this goal. The turbidite deposits comprise four unconformity-bounded tectonostratigraphic units (TSU), consisting of quartz-rich and feldspar-poor sandstones, calclithites rich in extrabasinal carbonates and hybrid arenites dominated by intrabasinal carbonates. The sandstones occur exclusively in TSU-2, whereas calclithites and hybrid arenites occur in the overlying TSU-3, TSU-4 and TSU-5. The calclithites were deposited at the base of each TSU and hybrid arenites in the uppermost parts. Extrabasinal carbonate sources were derived from the fold-and-thrust belt (mainly Cretaceous and Palaeocene limestones). Conversely, intrabasinal carbonate grains were sourced from foramol shelf carbonate factories. This compositional trend is attributed to alternating episodes of uplift and thrust propagation (siliciclastic and extrabasinal carbonates supplies) and subsequent episodes of development of carbonate platforms supplying intrabasinal detrital grains. The quartz-rich and feldspar-poor composition of the sandstones suggests derivation from intensely weathered cratonic basement rocks during the initial fill of the foreland basin. Successive sediments (calclithites and hybrid arenites) were derived from older uplifted basement rocks (feldspar-rich and, to some extent, rock fragments-rich sandstones), thrust-and-fold belt deposits and from coeval carbonate platforms developed at the basin margins. This study demonstrates that the integration of tectono-stratigraphy, petrology and geochemistry of arenites provides a powerful tool to constrain the spatial and temporal variation in provenance during the tectonic evolution of foreland basins

Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum-mechanical phenomena to perform operations on data) has led to a new class of GAs known as "Quantum Genetic Algorithms" (QGAs). In this review, we present a discussion, future potential, pros and cons of this new class of GAs. The review will be oriented towards computer scientists interested in QGAs "avoiding" the possible difficulties of quantum-mechanical phenomena.

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