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N. Martín

Publications and source records attributed to N. Martín.

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Tailoring topological order and π-conjugation to engineer quasi-metallic polymers

Topological band theory provides a conceptual framework to predict or even engineer robust metallic states at the boundaries of topologically distinct phases. The bulk-boundary correspondence requires that a topological electronic phase transition between two insulators must proceed via closing of the electronic gap. Therefore, it can provide a conceptual solution to the instability of metallic phases in π-conjugated 1D polymers. In this work we predict and demonstrate that a clever design and on-surface synthesis of polymers consisting of 1D linearly bridged polyacene moieties, can position the resulting polymer near the topological transition from a trivial to a non-trivial quantum phase featuring a very narrow bandgap with in-gap zero-energy edge-states at the topologically non-trivial phase. We also reveal the fundamental connection between topological classes and electronic transformation of 1D π-conjugated polymers.

cond-mat.mes-hall

New robust statistical procedures for polytomous logistic regression models

This paper derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the paper are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications.

stat.ME