Renormalization of spin-orbit coupling in quantum dots due to Zeeman interaction

We derive analitycally a partial diagonalization of the Hamiltonian representing a quantum dot including spin-orbit interaction and Zeeman energy on an equal footing. It is shown that the interplay between these two terms results in a renormalization of the spin-orbit intensity. The relation between this feature and experimental observations on conductance fluctuations is discussed, finding a good agreement between the model predictions and the experimental behavior.Comment: 4 pages, no figures. To appear in Phys. Rev. B (Brief Report) (2004

Interplay between Zeeman interaction and spin-orbit coupling in a two-dimensional semiconductor system

We analyse the interplay between Dresselhaus, Bychkov-Rashba, and Zeeman interactions in a two-dimensional semiconductor quantum system under the action of a magnetic field. When a vertical magnetic field is considered, we predict that the interplay results in an effective cyclotron frequency that depends on a spin-dependent contribution. For in-plane magnetic fields, we found that the interplay induces an anisotropic effective gyromagnetic factor that depends on the orientation of the applied field as well as on the orientation of the electron momentum.Comment: 5 page

Automatic speech recognition with deep neural networks for impaired speech

The final publication is available at https://link.springer.com/chapter/10.1007%2F978-3-319-49169-1_10Automatic Speech Recognition has reached almost human performance in some controlled scenarios. However, recognition of impaired speech is a difficult task for two main reasons: data is (i) scarce and (ii) heterogeneous. In this work we train different architectures on a database of dysarthric speech. A comparison between architectures shows that, even with a small database, hybrid DNN-HMM models outperform classical GMM-HMM according to word error rate measures. A DNN is able to improve the recognition word error rate a 13% for subjects with dysarthria with respect to the best classical architecture. This improvement is higher than the one given by other deep neural networks such as CNNs, TDNNs and LSTMs. All the experiments have been done with the Kaldi toolkit for speech recognition for which we have adapted several recipes to deal with dysarthric speech and work on the TORGO database. These recipes are publicly available.Peer ReviewedPostprint (author's final draft

Self-similar transmission properties of aperiodic Cantor potentials in gapped graphene

We investigate the transmission properties of quasiperiodic or aperiodic structures based on graphene arranged according to the Cantor sequence. In particular, we have found self-similar behaviour in the transmission spectra, and most importantly, we have calculated the scalability of the spectra. To do this, we implement and propose scaling rules for each one of the fundamental parameters: generation number, height of the barriers and length of the system. With this in mind we have been able to reproduce the reference transmission spectrum, applying the appropriate scaling rule, by means of the scaled transmission spectrum. These scaling rules are valid for both normal and oblique incidence, and as far as we can see the basic ingredients to obtain self-similar characteristics are: relativistic Dirac electrons, a self-similar structure and the non-conservation of the pseudo-spin. This constitutes a reduction of the number of conditions needed to observe self-similarity in graphene-based structures, see D\'iaz-Guerrero et al. [D. S. D\'iaz-Guerrero, L. M. Gaggero-Sager, I. Rodr\'iguez-Vargas, and G. G. Naumis, arXiv:1503.03412v1, 2015]

Intrinsic spin dynamics in semiconductor quantum dots

We investigate the characteristic spin dynamics corresponding to semiconductor quantum dots within the multiband envelope function approximation (EFA). By numerically solving an $8\times8$ $k\cdot p$ Hamiltonian we treat systems based on different III-V semiconductor materials.It is shown that, even in the absence of an applied magnetic field, these systems show intrinsic spin dynamics governed by intraband and interband transitions leading to characteristic spin frequencies ranging from the THz to optical frequencies.Comment: to be published in Nanotechnology. Separated figure file

A dependency look at the reality of constituency

A comment on "Neurophysiological dynamics of phrase-structure building during sentence processing" by Nelson et al (2017), Proceedings of the National Academy of Sciences USA 114(18), E3669-E3678.Comment: Final versio