Entangled and sequential quantum protocols with dephasing

Sequences of commuting quantum operators can be parallelized using entanglement. This transformation is behind some optimal quantum metrology protocols and recent results on quantum circuit complexity. We show that dephasing quantum maps in arbitrary dimension can also be parallelized. This implies that for general dephasing noise the protocol with entanglement is not more fragile than the corresponding sequential protocol and, conversely, the sequential protocol is not less effective than the entangled one. We derive this result using tensor networks. Furthermore, we only use transformations strictly valid within string diagrams in dagger compact closed categories. Therefore, they apply verbatim to other theories, such as geometric quantization and topological quantum field theory. This clarifies and characterizes to some extent the role of entanglement in general quantum theories.     

On the velocity and dissipation signature of vortex tubes in isotropic turbulence

The properties of vortex tubes are extracted and analyzed from a DNS database at various Re_λ, with the objective to characterize the associated distributions of induced velocity and kinetic energy dissipation. The induced velocity exhibits an inverse power-law scaling in the far field, different from Burgers’ r⁻¹ scaling, supporting the interpretation that tubes are the remnants of vortex sheets after roll-up, and suggesting a possible link with the Kolmogorov k^−5/3 spectral scaling. The energy dissipation signature is characterized by a local maximum near the edge of the vortex core, and an absolute peak at its center, which can be tentatively explained appealing to the occurrence of a bi-axial configuration of the strain-rate tensor.     

On the structure and normal modes of hydrogenated Ti-fullerene compounds

While nephrotoxicity of cadmium is well documented, very limited information exists on renal effects of exposure to cadmium-containing nanomaterials. In this work, ??omics?? methodologies have been used to assess the action of cadmium-containing silica nanoparticles (Cd-SiNPs) in the kidney of Sprague-Dawley rats exposed intratracheally. Groups of animals received a single dose of Cd-SiNPs (1?mg/rat), CdCl₂ (400???g/rat) or 0.1?ml saline (control). Renal gene expression was evaluated 7 and 30?days post exposure by DNA microarray technology using the Agilent Whole Rat Genome Microarray 4x44K. Gene modulating effects were observed in kidney at both time periods after treatment with Cd-SiNPs. The number of differentially expressed genes being 139 and 153 at the post exposure days 7 and 30, respectively. Renal gene expression changes were also observed in the kidney of CdCl₂-treated rats with a total of 253 and 70 probes modulated at 7 and 30?days, respectively. Analysis of renal gene expression profiles at day 7 indicated in both Cd-SiNP and CdCl₂ groups downregulation of several cluster genes linked to immune function, oxidative stress, and inflammation processes. Differing from day 7, the majority of cluster gene categories modified by nanoparticles in kidney 30?days after dosing were genes implicated in cell regulation and apoptosis. Modest renal gene expression changes were observed at day 30 in rats treated with CdCl₂. These results indicate that kidney may be a susceptible target for subtle long-lasting molecular alterations produced by cadmium nanoparticles locally instilled in the lung.     

Remarks on cannibalism and pattern formation in spatially extended prey–predator systems

The relationships between cannibalism and pattern formation in spatially extended prey–predator systems are studied with a model that degenerates, in the absence of cannibalism, into the most standard prey–predator model, known as Rosenzweig–MacArthur model. The analysis is based on the theory developed long ago by Turing in his famous paper on morphogenesis, but in a special form, which allows one to decouple the role of demographic parameters from that of diffusive dispersal. The proofs are given in terms of prey and predator nullclines because ecologists are mainly familiar with this technique. The final result of the analysis is that spatial pattern can exist only in systems with highly cannibalistic and highly dispersing predator provided the attractor of the system in the absence of cannibalism is a limit cycle. This result is more simple and more complete than that published in this journal a few years ago by Sun and coauthors.     

Existence and time-discretization for the finite-strain Souza–Auricchio constitutive model for shape-memory alloys

We prove the global existence of solutions for a shape-memory alloys constitutive model at finite strains. The model has been presented in Evangelista et al. (Int J Numer Methods Eng 81(6):761–785, 2010) and corresponds to a suitable finite-strain version of the celebrated Souza–Auricchio model for SMAs (Auricchio and Petrini in Int J Numer Methods Eng 55:1255–1284, 2002; Souza et al. in J Mech A Solids 17:789–806, 1998). We reformulate the model in purely variational fashion under the form of a rate-independent process. Existence of suitably weak (energetic) solutions to the model is obtained by passing to the limit within a constructive time-discretization procedure.     

Constitutive modeling of fiber composites with a soft hyperelastic matrix

This paper presents an experimental and numerical study of unidirectional carbon fiber composites with a silicone matrix, loaded transversally to the fibers. The experiments show nonlinear behavior with significant strain softening under cyclic loading. The numerical study uses a plane-strain finite element continuum model of the composite material in which the fiber distribution is based on experimental observations and cohesive elements allow debonding to take place at the fiber/matrix interfaces. It is found that accurate estimates of the initial tangent stiffness measured in the experiments can be obtained without allowing for debonding, but this feature has to be included to capture the non-linear and strain-softening behavior.     

Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment

Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level. Two different methods have been studied: one based on the data distribution and the other based on the energy function, with entropy as its main component. The method based on the data distribution shows poor performance with signals containing high amplitude outliers. On the contrary, the method based on the energy function is more robust to outliers. As it does not depend on the data distribution, it is not affected by artifactual events. A double rejection strategy has been chosen, first on a motion signal (accelerometer or EEG low-pass filtered between 1 and 10 Hz) and then on the EEG signal. The results showed a higher performance when working combining both artifact rejection methods. The energy-based method, to isolate motion artifacts, and the data-distribution-based method, to eliminate the remaining lower amplitude artifacts were used. In conclusion, a new method that proves to be robust for all types of signals is designed.     

Intermediate inflation on the brane

Brane inflationary universe model in the context of intermediate inflation is studied. General conditions for this model to be realizable are discussed. In the high-energy limit we describe in great details the characteristic of this model.     

A Tsallis’ statistics based neural network model for novel word learning

We invoke the Tsallis entropy formalism, a nonextensive entropy measure, to include some degree of non-locality in a neural network that is used for simulation of novel word learning in adults. A generalization of the gradient descent dynamics, realized via nonextensive cost functions, is used as a learning rule in a simple perceptron. The model is first investigated for general properties, and then tested against the empirical data, gathered from simple memorization experiments involving two populations of linguistically different subjects. Numerical solutions of the model equations corresponded to the measured performance states of human learners. In particular, we found that the memorization tasks were executed with rather small but population-specific amounts of nonextensivity, quantified by the entropic index q. Our findings raise the possibility of using entropic nonextensivity as a means of characterizing the degree of complexity of learning in both natural and artificial systems.     

Phase transition in the spanning-hyperforest model on complete hypergraphs

By using our novel Grassmann formulation we study the phase transition of the spanning-hyperforest model of the k-uniform complete hypergraph for any k2. The case k=2 reduces to the spanning-forest model on the complete graph. Different k are studied at once by using a microcanonical ensemble in which the number of hypertrees is fixed. The low-temperature phase is characterized by the appearance of a giant hyperforest. The phase transition occurs when the number of hyperforests is a fraction (k−1)/k of the total number of vertices. The behaviour at criticality is also studied by means of the coalescence of two saddle points. As the Grassmann formulation exhibits a global supersymmetry we show that the phase transition is second order and is associated to supersymmetry breaking and we explore the pure thermodynamical phase at low temperature by introducing an explicit breaking field.