Superconducting charge qubits from a microscopic many-body perspective

The quantised Josephson junction equation that underpins the behaviour of charge qubits and other tunnel devices is usually derived through cannonical quantisation of the classical macroscopic Josephson relations. However, this approach may neglect effects due to the fact that the charge qubit consists of a superconducting island of finite size connected to a large superconductor. We show that the well known quantised Josephson equation can be derived directly and simply from a microscopic many-body Hamiltonian. By choosing the appropriate strong coupling limit we produce a highly simplified Hamiltonian that nevertheless allows us to go beyond the mean field limit and predict further finite-size terms in addition to the basic equation.Comment: Accepted for J Phys Condensed Matte

Reproductive performance and reconception of Nellore cows according to their pure- or cross-bred calves.

The objective of the present research was to evaluate the effect of a calf?s genetic group on the productive and reproductive efficiency of its Nellore dam. Fixed-time artificial insemination was applied to 800 cows using semen extracted from Nellore, Simmental and Angus Red bulls. Four hundred eleven cows calved, producing 119 Nellore, 103 ½Simmental?½Nellore and 189 ½Nellore?½Angus Red calves. The second mating period, which paired Nellore cows with Simmental bulls, was initiated 10 days after parturitions began and lasted for 5 months. Based on the two successive parturitions, the cumulative parturition rate for calving periods of 3, 4 and 5 months was calculated. Although no significant difference was observed for birth weight among the genetic groups, cross-bred calves weighed, on average, 10% more than did pure-bred calves at the age of 205 days. Nellore dams experienced a gestation period that was 7 days longer than did the cross-bred dams, and the former showed a higher parturition rate at 90 and 120 days of the calving season, but not at 150 days (calving rates of 80.6, 76.4 and 76.2% for mothers of Nellore, ½Nellore?½Angus Red and ½Nellore?½Simmental, respectively, p > 0.05). At 90 and 120 days, Nellore dams produced more kg of calf per mated dam. In conclusion, in a short breeding season, Nellore dams nursing pure-bred Nellore calves were found to have a higher biological efficiency compared with Nellore dams nursing cross-bred calves

Dotted and Undotted Algebraic Spinor Fields in General Relativity

We investigate using Clifford algebra methods the theory of algebraic dotted and undotted spinor fields over a Lorentzian spacetime and their realizations as matrix spinor fields, which are the usual dotted and undotted two component spinor fields. We found that some ad hoc rules postulated for the covariant derivatives of Pauli sigma matrices and also for the Dirac gamma matrices in General Relativity cover important physical meaning, which is not apparent in the usual matrix presentation of the theory of two components dotted and undotted spinor fields. We also discuss some issues related to the the previous one and which appear in a proposed "unified" theory of gravitation and electromagnetism which use two components dotted and undotted spinor fields and also paravector fields, which are particular sections of the even subundle of the Clifford bundle of spacetime.Comment: some new misprints have been correcte

Spin Gauge Theory of Gravity in Clifford Space: A Realization of Kaluza-Klein Theory in 4-Dimensional Spacetime

A theory in which 4-dimensional spacetime is generalized to a larger space, namely a 16-dimensional Clifford space (C-space) is investigated. Curved Clifford space can provide a realization of Kaluza-Klein theory. A covariant Dirac equation in curved C-space is explored. The generalized Dirac field is assumed to be a polyvector-valued object (a Clifford number) which can be written as a superposition of four independent spinors, each spanning a different left ideal of Clifford algebra. The general transformations of a polyvector can act from the left and/or from the right, and form a large gauge group which may contain the group U(1)xSU(2)xSU(3) of the standard model. The generalized spin connection in C-space has the properties of Yang-Mills gauge fields. It contains the ordinary spin connection related to gravity (with torsion), and extra parts describing additional interactions, including those described by the antisymmetric Kalb-Ramond fields.Comment: 57 pages; References added, section 2 rewritten and expande

Wireless Image Transmission Using Deep Source Channel Coding With Attention Modules

Recent research on joint source channel coding (JSCC) for wireless communications has achieved great success owing to the employment of deep learning (DL). However, the existing work on DL based JSCC usually trains the designed network to operate under a specific signal-to-noise ratio (SNR) regime, without taking into account that the SNR level during the deployment stage may differ from that during the training stage. A number of networks are required to cover the scenario with a broad range of SNRs, which is computational inefficiency (in the training stage) and requires large storage. To overcome these drawbacks our paper proposes a novel method called Attention DL based JSCC (ADJSCC) that can successfully operate with different SNR levels during transmission. This design is inspired by the resource assignment strategy in traditional JSCC, which dynamically adjusts the compression ratio in source coding and the channel coding rate according to the channel SNR. This is achieved by resorting to attention mechanisms because these are able to allocate computing resources to more critical tasks. Instead of applying the resource allocation strategy in traditional JSCC, the ADJSCC uses the channel-wise soft attention to scaling features according to SNR conditions. We compare the ADJSCC method with the state-of-the-art DL based JSCC method through extensive experiments to demonstrate its adaptability, robustness and versatility. Compared with the existing methods, the proposed method takes less storage and is more robust in the presence of channel mismatch

Entanglement of superconducting charge qubits by homodyne measurement

We present a scheme by which projective homodyne measurement of a microwave resonator can be used to generate entanglement between two superconducting charge qubits coupled to this resonator. The non-interacting qubits are initialised in a product of their ground states, the resonator is initialised in a coherent field state, and the state of the system is allowed to evolve under a rotating wave Hamiltonian. Making a homodyne measurement on the resonator at a given time projects the qubits into an state of the form (|gg> + exp(-i phi)|ee>)/sqrt(2). This protocol can produce states with a fidelity as high as required, with a probability approaching 0.5. Although the system described is one that can be used to display revival in the qubit oscillations, we show that the entanglement procedure works at much shorter timescales.Comment: 17 pages, 7 figure

Numerical Evolution of axisymmetric vacuum spacetimes: a code based on the Galerkin method

We present the first numerical code based on the Galerkin and Collocation methods to integrate the field equations of the Bondi problem. The Galerkin method like all spectral methods provide high accuracy with moderate computational effort. Several numerical tests were performed to verify the issues of convergence, stability and accuracy with promising results. This code opens up several possibilities of applications in more general scenarios for studying the evolution of spacetimes with gravitational waves.Comment: 11 pages, 6 figures. To appear in Classical and Quantum Gravit

Flutuação populacional de nematoides em hortaliças sob sistema de plantio direto.

Resumo 579-

Recognition of Facial Expressions by Cortical Multi-scale Line and Edge Coding

Face-to-face communications between humans involve emotions, which often are unconsciously conveyed by facial expressions and body gestures. Intelligent human-machine interfaces, for example in cognitive robotics, need to recognize emotions. This paper addresses facial expressions and their neural correlates on the basis of a model of the visual cortex: the multi-scale line and edge coding. The recognition model links the cortical representation with Paul Ekman's Action Units which are related to the different facial muscles. The model applies a top-down categorization with trends and magnitudes of displacements of the mouth and eyebrows based on expected displacements relative to a neutral expression. The happy vs. not-happy categorization yielded a. correct recognition rate of 91%, whereas final recognition of the six expressions happy, anger, disgust, fear, sadness and surprise resulted in a. rate of 78%