1,785 research outputs found

    Bipolaronic blockade effect in quantum dots with negative charging energy

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    We investigate single-electron transport through quantum dots with negative charging energy induced by a polaronic energy shift. For weak dot-lead tunnel couplings, we demonstrate a bipolaronic blockade effect at low biases which suppresses the oscillating linear conductance, while the conductance resonances under large biases are enhanced. Novel conductance plateau develops when the coupling asymmetry is introduced, with its height and width tuned by the coupling strength and external magnetic field. It is further shown that the amplitude ratio of magnetic-split conductance peaks changes from 3 to 1for increasing coupling asymmetry. Though we demonstrate all these transport phenomena in the low-order single-electron tunneling regime, they are already strikingly different from the usual Coulomb blockade physics and are easy to observe experimentally.Comment: 6 pages, 5 figure

    On Investigating the Conservative Property of Score-Based Generative Models

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    Existing Score-based Generative Models (SGMs) can be categorized into constrained SGMs (CSGMs) or unconstrained SGMs (USGMs) according to their parameterization approaches. CSGMs model probability density functions as Boltzmann distributions, and assign their predictions as the negative gradients of some scalar-valued energy functions. On the other hand, USGMs employ flexible architectures capable of directly estimating scores without the need to explicitly model energy functions. In this paper, we demonstrate that the architectural constraints of CSGMs may limit their modeling ability. In addition, we show that USGMs' inability to preserve the property of conservativeness may lead to degraded sampling performance in practice. To address the above issues, we propose Quasi-Conservative Score-based Generative Models (QCSGMs) for keeping the advantages of both CSGMs and USGMs. Our theoretical derivations demonstrate that the training objective of QCSGMs can be efficiently integrated into the training processes by leveraging the Hutchinson trace estimator. In addition, our experimental results on the CIFAR-10, CIFAR-100, ImageNet, and SVHN datasets validate the effectiveness of QCSGMs. Finally, we justify the advantage of QCSGMs using an example of a one-layered autoencoder

    Training Energy-Based Normalizing Flow with Score-Matching Objectives

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    In this paper, we establish a connection between the parameterization of flow-based and energy-based generative models, and present a new flow-based modeling approach called energy-based normalizing flow (EBFlow). We demonstrate that by optimizing EBFlow with score-matching objectives, the computation of Jacobian determinants for linear transformations can be entirely bypassed. This feature enables the use of arbitrary linear layers in the construction of flow-based models without increasing the computational time complexity of each training iteration from O(D2L)\mathcal{O}(D^2L) to O(D3L)\mathcal{O}(D^3L) for an LL-layered model that accepts DD-dimensional inputs. This makes the training of EBFlow more efficient than the commonly-adopted maximum likelihood training method. In addition to the reduction in runtime, we enhance the training stability and empirical performance of EBFlow through a number of techniques developed based on our analysis on the score-matching methods. The experimental results demonstrate that our approach achieves a significant speedup compared to maximum likelihood estimation, while outperforming prior efficient training techniques with a noticeable margin in terms of negative log-likelihood (NLL)

    Movable Fiber-Integrated Hybrid Plasmonic Waveguide on Metal Film

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    A waveguide structure consisting of a tapered nanofiber on a metal film is proposed and analyzed to support highly localized hybrid plasmonic modes. The hybrid plasmonic mode can be efficiently excited through the in-line tapered fiber based on adiabatic conversion and collected by the same fiber, which is very convenient in the experiment. Due to the ultrasmall mode area of plasmonic mode, the local electromagnetic field is greatly enhanced in this movable waveguide, which is potential for enhanced coherence light emitter interactions, such as waveguide quantum electrodynamics, single emitter spectrum and nonlinear optics
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