6,328 research outputs found

    Shot noise in resonant tunneling structures

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    We propose a quantum mechanical approach to noise in resonant tunneling structures, that can be applied in the whole range of transport regimes, from completely coherent to completely incoherent. In both limiting cases, well known results which have appeared in the literature are recovered. Shot noise reduction due to both Pauli exclusion and Coulomb repulsion, and their combined effect, are studied as a function of the rate of incoherent processes in the well (which are taken into account by means of a phenomenological relaxation time), and of temperature. Our approach allows the study of noise in a variety of operating conditions (i.e., equilibrium, sub-peak voltages, second resonance voltages), and as a function of temperature, explaining experimental results and predicting interesting new results.Comment: RevTeX file, 26 pages, 3 Postscript figures, uses epsf.sty. submitted to Phys. Rev.

    Functional Methods and Effective Potentials for Nonlinear Composites

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    A formulation of variational principles in terms of functional integrals is proposed for any type of local plastic potentials. The minimization problem is reduced to the computation of a path integral. This integral can be used as a starting point for different approximations. As a first application, it is shown how to compute to second-order the weak-disorder perturbative expansion of the effective potentials in random composite. The three-dimensional results of Suquet and Ponte-Casta\~neda (1993) for the plastic dissipation potential with uniform applied tractions are retrieved and extended to any space dimension, taking correlations into account. In addition, the viscoplastic potential is also computed for uniform strain rates.Comment: 20 pages, accepted for publication in JMP

    Artificial intelligence as an enabler for entrepreneurs: a systematic literature review and an agenda for future research

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    Purpose While the disruptive potential of artificial intelligence (AI) has been receiving growing consensus with regards to its positive influence on entrepreneurship, there is a clear lack of systematization in academic literature pertaining to this correlation. The current research seeks to explore the impact of AI on entrepreneurship as an enabler for entrepreneurs, taking into account the crucial application of AI within all Industry 4.0 technological paradigms, such as smart factory, the Internet of things (IoT), augmented reality (AR) and blockchain. Design/methodology/approach A systematic literature review was used to analyze all relevant studies forging connections between AI and entrepreneurship. The cluster interpretation follows a structure that we called the "AI-enabled entrepreneurial process." Findings This study proves that AI has profound implications when it comes to entrepreneurship and, in particular, positively impacts entrepreneurs in four ways: through opportunity, decision-making, performance, and education and research. Practical implications The framework's practical value is linked to its applications for researchers, entrepreneurs and aspiring entrepreneurs (as well as those acting entrepreneurially within established organizations) who want to unleash the power of AI in an entrepreneurial setting. Originality/value This research offers a model through which to interpret the impact of AI on entrepreneurship, systematizing disconnected studies on the topic and arranging contributions into paradigms of entrepreneurial and managerial literature

    Hybridization of multi-objective deterministic particle swarm with derivative-free local searches

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    The paper presents a multi-objective derivative-free and deterministic global/local hybrid algorithm for the efficient and effective solution of simulation-based design optimization (SBDO) problems. The objective is to show how the hybridization of two multi-objective derivative-free global and local algorithms achieves better performance than the separate use of the two algorithms in solving specific SBDO problems for hull-form design. The proposed method belongs to the class of memetic algorithms, where the global exploration capability of multi-objective deterministic particle swarm optimization is enriched by exploiting the local search accuracy of a derivative-free multi-objective line-search method. To the authors best knowledge, studies are still limited on memetic, multi-objective, deterministic, derivative-free, and evolutionary algorithms for an effective and efficient solution of SBDO for hull-form design. The proposed formulation manages global and local searches based on the hypervolume metric. The hybridization scheme uses two parameters to control the local search activation and the number of function calls used by the local algorithm. The most promising values of these parameters were identified using forty analytical tests representative of the SBDO problem of interest. The resulting hybrid algorithm was finally applied to two SBDO problems for hull-form design. For both analytical tests and SBDO problems, the hybrid method achieves better performance than its global and local counterparts

    Fractal Fidelity as a signature of Quantum Chaos

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    We analyze the fidelity of a quantum simulation and we show that it displays fractal fluctuations iff the simulated dynamics is chaotic. This analysis allows us to investigate a given simulated dynamics without any prior knowledge. In the case of integrable dynamics, the appearance of fidelity fractal fluctuations is a signal of a highly corrupted simulation. We conjecture that fidelity fractal fluctuations are a signature of the appearance of quantum chaos. Our analysis can be realized already by a few qubit quantum processor.Comment: 5 pages, 5 figure

    Hidden AGNs in Early-Type Galaxies

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    We present a stacking analysis of the complete sample of Early Type Galaxies (ETGs) in the \textit{Chandra} COSMOS (C-COSMOS) survey, to explore the nature of the X-ray luminosity in the redshift and stellar luminosity ranges 0<z<1.50<z<1.5 and {10}^{9}. Using established scaling relations, we subtract the contribution of X-ray binary populations, to estimate the combined emission of hot ISM and AGN. To discriminate between the relative importance of these two components, we (1) compare our results with the relation observed in the local universe LX,gasLK4.5L_{X,gas}\propto L_K^{4.5} for hot gaseous halos emission in ETGs, and (2) evaluate the spectral signature of each stacked bin. We find two regimes where the non-stellar X-ray emission is hard, consisten t with AGN emission. First, there is evidence of hard, absorbed X-ray emission in stacked bins including relatively high z (1.2\sim 1.2) ETGs with average high X-ray luminosity (L_{X-LMXB}\gtrsim 6\times{10}^{42}\mbox{ erg}/\mbox{s}). These luminosities are consistent with the presence ofhighly absorbed "hidden" AGNs in these ETGs, which are not visible in their optical-IR spectra and spectral energy distributions. Second, confirming the early indication from our C-COSMOS study of X-ray detected ETGs, we find significantly enhanced X-ray luminoaity in lower stellar mass ETGs (L_K\lesssim{10}^{11}L_{\astrosun}), relative to the local LX,gasLK4.5L_{X,gas}\propto L_K^{4.5} relation. The stacked spectra of these ETGs also suggest X-ray emission harder than expected from gaseous hot halos. This emission is consistent with inefficient accretion 105104M˙Edd{10}^{-5}-{10}^{-4}\dot{M}_{Edd} onto M_{BH}\sim {10}^{6}-{10}^{8}\,M_{\astrosun}.Comment: 22 pages, 7 figures, 2 tables. Accepted for publications on Ap
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