Semimetalic graphene in a modulated electric potential

The $\pi$-electronic structure of graphene in the presence of a modulated electric potential is investigated by the tight-binding model. The low-energy electronic properties are strongly affected by the period and field strength. Such a field could modify the energy dispersions, destroy state degeneracy, and induce band-edge states. It should be noted that a modulated electric potential could make semiconducting graphene semimetallic, and that the onset period of such a transition relies on the field strength. There exist infinite Fermi-momentum states in sharply contrast with two crossing points (Dirac points) for graphene without external fields. The finite density of states (DOS) at the Fermi level means that there are free carriers, and, at the same time, the low DOS spectrum exhibits many prominent peaks, mainly owing to the band-edge states.Comment: 12pages, 5 figure

Dynamical Properties of a Growing Surface on a Random Substrate

The dynamics of the discrete Gaussian model for the surface of a crystal deposited on a disordered substrate is investigated by Monte Carlo simulations. The mobility of the growing surface was studied as a function of a small driving force $F$ and temperature $T$. A continuous transition is found from high-temperature phase characterized by linear response to a low-temperature phase with nonlinear, temperature dependent response. In the simulated regime of driving force the numerical results are in general agreement with recent dynamic renormalization group predictions.Comment: 10 pages, latex, 3 figures, to appear in Phys. Rev. E (RC

Optical probes of the quantum vacuum: The photon polarization tensor in external fields

The photon polarization tensor is the central building block of an effective theory description of photon propagation in the quantum vacuum. It accounts for the vacuum fluctuations of the underlying theory, and in the presence of external electromagnetic fields, gives rise to such striking phenomena as vacuum birefringence and dichroism. Standard approximations of the polarization tensor are often restricted to on-the-light-cone dynamics in homogeneous electromagnetic fields, and are limited to certain momentum regimes only. We devise two different strategies to go beyond these limitations: First, we aim at obtaining novel analytical insights into the photon polarization tensor for homogeneous fields, while retaining its full momentum dependence. Second, we employ wordline numerical methods to surpass the constant-field limit.Comment: 13 pages, 4 figures; typo in Eq. (5) corrected (matches journal version

Numerical analysis of the Iosipescu specimen for composite materials

A finite element analysis of the Iosipescu shear tests for unidirectional and cross-ply composites is presented. It is shown that an iterative analysis procedure must be used to model the fixture-specimen kinematics. The correction factors which are needed to compensate for the nonuniformity of stress distribution in calculating shear modulus are shown to be dependent on the material orthotropic ratio and the finite element loading models. Test section strain distributions representative of typical graphite-epoxy specimens are also presented

Nonorthogonal coding in spectrally-entangled photons

Controlling and engineering continuous spectral modes of entangled photons represents one of the promising approaches toward secure quantum communications. By using the telecom bandwidth generated from a cascade-emitted biphoton in atomic ensembles, a fiber-based long-distance quantum communication can be feasible owing to its low transmission loss. With multiplexed photon pairs, we propose to implement a nonorthogonal coding scheme in their spectral modes and present an architecture of multiple channels enabling a high-capacity transfer of codewords. Using the measures of the second-order correlations and associated visibility and contrast, we further quantify the performance of the proposed nonorthogonal coding scheme. Our results demonstrate the capability to encode and decode quantum information beyond the orthogonal coding scheme. The proposed scheme here can be applicable to a large-scale and multiuser quantum communication and pave the way toward an efficient and functional quantum information processing.Comment: Four figure

The impact of artificial intelligence on sustainable corporate brand:a netnography study of tesla

Abstract. The global market has become ever more turbulent due to digitalisation and digital transformation. Artificial Intelligence (AI) plays a central role in moving forward the advance of technology. AI has become an important research field in marketing while various companies have successfully implemented AI technologies to meet customers’ needs. However, the impacts of AI on brands have not been widely explored in both scientific and managerial aspects. Brands generate values for businesses by providing functional and non-functional benefits that can be contributed by implementing AI technologies. Mainly, developing sustainability is crucial to address stakeholders’ concerns for today’s brands. The sustainable corporate brand can be a solution to this market demand as its promise has sustainability as a core value. Through exploring this phenomenon, the thesis answers the research question: to what extent does AI contribute positive impacts on sustainable corporate brands in the electric autonomous vehicle (EAVs) sector? The EAVs industry, represented by the case company, Tesla, is chosen for conducting this research because it integrates the variants of electric vehicles that provide environmental benefits and the autonomous cars that use AI technologies. The study is performed using the qualitative research method of netnography. The data are collected from the publicly available information on Twitter and Youtube based on their relevance to the research question. One hundred sixty tweets and thirteen Youtube videos are extracted in textual form and analysed following the guidelines of thematic analysis and triangulated with multiple sources of data. The key results of the research suggest the unique characteristics of the three AI features, machine learning, natural language processing (NLP) and Big Data analytics, help create the normative emotions and efficacy in the mind of stakeholders. These norms of emotions and efficacy further motivate stakeholders’ normative actions that, in return, enhance the normative emotions and efficacy in a loop. Five elements represent the values AI technologies contribute to brand promise through creating a unique experience for the stakeholders that differentiate the brand from its competitors. The refreshed excitements and trust are brought by machine learning technologies. The fun and human characteristics and safety are brought by NLP technologies. Technology superiority is made possible through Big Data analytics. Four elements act for the values conveyed by AI technologies that enrich and expand the brand identity. NLP features can effectively enhance the connections between the focal brand and the other brand associations: the CEO, the affiliate brands and meaningful cultural references. The shared ownership of the brand is intensified through the co-creation of Big Data analytics. By contributing to brand promise and brand identity, AI implementation helps foster positive impacts in building an authentic, emotionally charged, and behaviourally based sustainable corporate brand

Anomalous physical properties of underdoped weak-ferromagnetic superconductor RuSr2_2EuCu2_{2}O8_{8}

Similar to the optimal-doped, weak-ferromagnetic (WFM induced by canted antiferromagnetism, T$_{Curie}$ = 131 K) and superconducting (T$_{c}$ = 56 K) RuSr$_{2}$GdCu$_{2}$O$_{8}$, the underdoped RuSr$_{2}$EuCu$_{2}$O$_{8}$ (T$_{Curie}$ = 133 K, T$_{c}$ = 36 K) also exhibited a spontaneous vortex state (SVS) between 16 K and 36 K. The low field ($\pm$20 G) superconducting hysteresis loop indicates a weak and narrow Meissner state region of average lower critical field B$_{c1}^{ave}$(T) = B$_{c1}^{ave}$(0)[1 - (T/T$_{SVS}$)$^{2}$], with B$_{c1}^{ave}$(0) = 7 G and T$_{SVS}$ = 16 K. The vortex melting transition (T$_{melting}$ = 21 K) below T$_{c}$ obtained from the broad resistivity drop and the onset of diamagnetic signal indicates a vortex liquid region due to the coexistence and interplay between superconductivity and WFM order. No visible jump in specific heat was observed near T$_{c}$ for Eu- and Gd-compound. This is not surprising, since the electronic specific heat is easily overshadowed by the large phonon and weak-ferromagnetic contributions. Furthermore, a broad resistivity transition due to low vortex melting temperature would also lead to a correspondingly reduced height of any specific heat jump. Finally, with the baseline from the nonmagnetic Eu-compound, specific heat data analysis confirms the magnetic entropy associated with antiferromagnetic ordering of Gd$^{3+}$ (J = S = 7/2) at 2.5 K to be close to $\it{N_{A}k}$ ln8 as expected.Comment: 7 figure