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Flowering plants adjust their reproductive period to maximize the success of the offspring. Monocarpic plants, those with a single reproductive cycle that precedes plant senescence and death, tightly regulate both flowering initiation and flowering cessation. The end of the flowering period involves the arrest of the inflorescence meristem activity, known as proliferative arrest, in what has been interpreted as an evolutionary adaptation to maximize the allocation of resources to seed production and the viability of the progeny. Factors influencing proliferative arrest were described for several monocarpic plant species many decades ago, but only in the last few years studies performed in Arabidopsis have allowed to approach proliferative arrest regulation in a comprehensive manner by studying the physiology, hormone dynamics, and genetic factors involved in its regulation. However, these studies remain restricted to Arabidopsis and there is a need to expand our knowledge to other monocarpic species to propose general mechanisms controlling the process. In this work, we have characterized proliferative arrest in Pisum sativum, trying to parallel available studies in Arabidopsis to maximize this comparative framework. We have assessed quantitatively the role of fruits/seeds in the process, the influence of the positional effect of these fruits/seeds in the behavior of the inflorescence meristem, and the transcriptomic changes in the inflorescence associated with the arrested state of the meristem. Our results support a high conservation of the factors triggering arrest in pea and Arabidopsis, but also reveal differences reinforcing the need to perform similar studies in other species.

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Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce's response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process' degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.

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The propagation of N photons in one dimensional waveguides coupled to M qubits is discussed, both in the strong and ultrastrong qubit-waveguide coupling. Special emphasis is placed on the characterisation of the nonlinear response and its linear limit for the scattered photons as a function of N, M, qubit inter distance and light-matter coupling. The quantum evolution is numerically solved via the matrix product states technique. The time evolutions for both the field and qubits are computed. The nonlinear character (as a function of N/M) depends on the computed observable. While perfect reflection is obtained for N/M≅1, photon-photon correlations are still resolved for ratios N/M=non-zero. Inter-qubit distance enhances the nonlinear response. Moving to the ultrastrong coupling regime, we observe that inelastic processes are robust against the number of qubits and that the qubit-qubit interaction mediated by the photons is qualitatively modified. The theory developed in this work models experiments in circuit QED, photonic crystals and dielectric waveguides.

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Complex networks are formal frameworks capturing the interdependencies between the elements of large systems and databases. This formalism allows to use network navigation methods to rank the importance that each constituent has on the global organization of the system. A key example is Pagerank navigation which is at the core of the most used search engine of the World Wide Web. Inspired in this classical algorithm, we define a quantum navigation method providing a unique ranking of the elements of a network. We analyze the convergence of quantum navigation to the stationary rank of networks and show that quantumness decreases the number of navigation steps before convergence. In addition, we show that quantum navigation allows to solve degeneracies found in classical ranks. By implementing the quantum algorithm in real networks, we confirm these improvements and show that quantum coherence unveils new hierarchical features about the global organization of complex systems.