496 research outputs found

    Multispin Coding Technique for Nonequilibrium Reweighting

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    We present the multispin coding for the nonequlibrium reweighting method of the Monte Carlo simulation, that was developed by the present authors. As an illustration, we treat the driven diffusive lattice gas model. We use the multispin coding technique both for the spin update and for the calculation of the histogram of incremental weights, which is needed in the calculation of nonequlibrium reweighting. All the operations are executed by the bitwise logical commands.Comment: accepted for publication in Int. J. Mod. Phys.

    Financial Liberalization and Monetary Policy Cooperation in East Asia

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    As the countries in East Asia embark on financial liberalization, a key issue that confronts policymakers is the greater complexity of risks that is injected into the financial system. In particular, capital account liberalization may potentially increase the vulnerability of individual countries to external financial shocks. This paper advocates the optimally cascading of financial liberalization that is consistent across three dimensions: extent of domestic financial liberalization; the degree of exchange rate flexibility; and the scope of capital account liberalization. Unless the process of liberalization is properly managed, it could provoke destabilizing capital flows and lead to volatile exchange rates. Smooth responses to fluctuating capital flows require accelerated institutional reforms in individual countries and an upgraded regional financial infrastructure. We argue that informal monetary arrangements, sequenced from simple to more intensive commitments, can go a long way in improving sovereign and regional institutions both to handle ongoing financial liberalization and to promote intra-regional currency stability.

    Pseudo spin-orbit coupling of Dirac particles in graphene spintronics

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    We study the pseudo spin-orbital (SO) effects experienced by massive Dirac particles in graphene, which can potentially be of a larger magnitude compared to the conventional Rashba SO effects experienced by particles in a 2DEG semiconductor heterostructure. In order to generate a uniform vertical pseudo SO field, we propose an artificial atomic structure, consisting of a graphene ring and a charged nanodot at the center which produces a large radial electric field. In this structure, a large pseudo SO coupling strength can be achieved by accelerating the Dirac particles around the ring, due to the small energy gap in graphene and the large radial electric field emanating from the charged nanodot. We discuss the theoretical possibility of harnessing the pseudo SO effects in mesoscopic applications, e.g. pseudo spin relaxation and switching.Comment: 12 pages, 1 figur

    Nonequilibrium Reweighting on the Driven Diffusive Lattice Gas

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    The nonequilibrium reweighting technique, which was recently developed by the present authors, is used for the study of the nonequilibrium steady states. The renewed formulation of the nonequlibrium reweighting enables us to use the very efficient multi-spin coding. We apply the nonequilibrium reweighting to the driven diffusive lattice gas model. Combining with the dynamical finite-size scaling theory, we estimate the critical temperature Tc and the dynamical exponent z. We also argue that this technique has an interesting feature that enables explicit calculation of derivatives of thermodynamic quantities without resorting to numerical differences.Comment: Accepted for publication in J. Phys. A (Lett.

    Aquatic Photovoltaic Facility

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    A feasibility design and cost estimate was completed for a 1 megawatt photovoltaic (PV) facility which would float on an island reservoir at Catalina Island off the coast the coast of Southern California. If built, this project would be one of the largest PV operating facilities to date and also the first floating PV system. The modular facility consists of 250 floating platforms each supporting 430 square feet of flat panel PV cells. This facility would provide 25% of Catalina\u27s yearly peak energy demand and reduce the amount of diesel fuel used

    SEW-ing a Simple Endorsement Web to incentivize trustworthy participatory sensing

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    Two crucial issues to the success of participatory sensing are (a) how to incentivize the large crowd of mobile users to participate and (b) how to ensure the sensing data to be trustworthy. While they are traditionally being studied separately in the literature, this paper proposes a Simple Endorsement Web (SEW) to address both issues in a synergistic manner. The key idea is (a) introducing a social concept called nepotism into participatory sensing, by linking mobile users into a social \u27web of participants\u27 with endorsement relations, and (b) overlaying this network with investment-like economic implications. The social and economic layers are interleaved to provision and enhance incentives and trustworthiness. We elaborate the social implications of SEW, and analyze the economic implications under a Stackelberg game framework. We derive the optimal design parameter that maximizes the utility of the sensing campaign organizer, while ensuring participants to strictly have incentive to participate. We also design algorithms for participants to optimally \u27sew\u27 SEW, namely to manipulate the endorsement links of SEW such that their economic benefits are maximized and social constrains are satisfied. Finally, we provide two numerical examples for an intuitive understanding

    Optimal Prizes for All-Pay Contests in Heterogeneous Crowdsourcing

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    Incentive is key to the success of crowd sourcing which heavily depends on the level of user participation. This paper designs an incentive mechanism to motivate a heterogeneous crowd of users to actively participate in crowd sourcing campaigns. We cast the problem in a new, asymmetric all-pay contest model with incomplete information, where an arbitrary n of users exert irrevocable effort to compete for a prize tuple. The prize tuple is an array of prize functions as opposed to a single constant prize typically used by conventional contests. We design an optimal contest that (a) induces the maximum profit -- total user effort minus the prize payout -- for the crowdsourcer, and (b) ensures users to strictly have incentive to participate. In stark contrast to intuition and prior related work, our mechanism induces an equilibrium in which heterogeneous users behave independently of one another as if they were in a homogeneous setting. This newly discovered property, which we coin as strategy autonomy (SA), is of practical significance: it (a) reduces computational and storage complexity by n-fold for each user, (b) increases the crowdsourcer's revenue by counteracting an effort reservation effect existing in asymmetric contests, and (c) neutralizes the (almost universal) law of diminishing marginal returns (DMR). Through an extensive numerical case study, we demonstrate and scrutinize the superior profitability of our mechanism, as well as draw insights into the SA property
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