137 research outputs found
Refractive-index sensing with ultra-thin plasmonic nanotubes
We study the refractive-index sensing properties of plasmonic nanotubes with
a dielectric core and ultra-thin metal shell. The few-nm thin metal shell is
described by both the usual Drude model and the nonlocal hydrodynamic model to
investigate the effects of nonlocality. We derive an analytical expression for
the extinction cross section and show how sensing of the refractive index of
the surrounding medium and the figure-of-merit are affected by the shape and
size of the nanotubes. Comparison with other localized surface plasmon
resonance sensors reveals that the nanotube exhibits superior sensitivity and
comparable figure-of-merit
Plasmonic atoms and plasmonic molecules
The proposed paradigm of plasmonic atoms and plasmonic molecules allows one
to describe and predict the strongly localized plasmonic oscillations in the
clusters of nanoparticles and some other nanostructures in uniform way.
Strongly localized plasmonic molecules near the contacting surfaces might
become the fundamental elements (by analogy with Lego bricks) for a
construction of fully integrated opto-electronic nanodevices of any complexity
and scale of integration.Comment: 30 pages, 16 figure
Coupled surface polaritons and the Casimir force
The Casimir force between metallic plates made of realistic materials is
evaluated for distances in the nanometer range. A spectrum over real
frequencies is introduced and shows narrow peaks due to surface resonances
(plasmon polaritons or phonon polaritons) that are coupled across the vacuum
gap. We demonstrate that the Casimir force originates from the attraction
(repulsion) due to the corresponding symmetric (antisymmetric) eigenmodes,
respectively. This picture is used to derive a simple analytical estimate of
the Casimir force at short distances. We recover the result known for Drude
metals without absorption and compute the correction for weakly absorbing
materials.Comment: revised version submitted to Phys. Rev. A, 06 November 200
Resonant hyper-Raman scattering in spherical quantum dots
A theoretical model of resonant hyper-Raman scattering by an ensemble of
spherical semiconductor quantum dots has been developed. The electronic
intermediate states are described as Wannier-Mott excitons in the framework of
the envelope function approximation. The optical polar vibrational modes of the
nanocrystallites (vibrons) and their interaction with the electronic system are
analized with the help of a continuum model satisfying both the mechanical and
electrostatic matching conditions at the interface. An explicit expression for
the hyper-Raman scattering efficiency is derived, which is valid for incident
two-photon energy close to the exciton resonances. The dipole selection rules
for optical transitions and Fr\"ohlich-like exciton-lattice interaction are
derived: It is shown that only exciton states with total angular momentum
and vibrational modes with angular momentum contribute to the
hyper-Raman scattering process. The associated exciton energies, wavefunctions,
and vibron frequencies have been obtained for spherical CdSe zincblende-type
nanocrystals, and the corresponding hyper-Raman scattering spectrum and
resonance profile are calculated. Their dependence on the dot radius and the
influence of the size distribution on them are also discussed.Comment: 12 pages REVTeX (two columns), 2 tables, 8 figure
Polariton propagation in weak confinement quantum wells
Exciton-polariton propagation in a quantum well, under centre-of-mass
quantization, is computed by a variational self-consistent microscopic theory.
The Wannier exciton envelope functions basis set is given by the simple
analytical model of ref. [1], based on pure states of the centre-of-mass wave
vector, free from fitting parameters and "ad hoc" (the so called additional
boundary conditions-ABCs) assumptions. In the present paper, the former
analytical model is implemented in order to reproduce the centre-of-mass
quantization in a large range of quantum well thicknesses (5a_B < L < inf.).
The role of the dynamical transition layer at the well/barrier interfaces is
discussed at variance of the classical Pekar's dead-layer and ABCs. The Wannier
exciton eigenstates are computed, and compared with various theoretical models
with different degrees of accuracy. Exciton-polariton transmission spectra in
large quantum wells (L>> a_B) are computed and compared with experimental
results of Schneider et al.\cite{Schneider} in high quality GaAs samples. The
sound agreement between theory and experiment allows to unambiguously assign
the exciton-polariton dips of the transmission spectrum to the pure states of
the Wannier exciton center-of-mass quantization.Comment: 15 pages, 15 figures; will appear in Phys.Rev.
Fano resonances in plasmonic core-shell particles and the Purcell effect
Despite a long history, light scattering by particles with size comparable
with the light wavelength still unveils surprising optical phenomena, and many
of them are related to the Fano effect. Originally described in the context of
atomic physics, the Fano resonance in light scattering arises from the
interference between a narrow subradiant mode and a spectrally broad radiation
line. Here, we present an overview of Fano resonances in coated spherical
scatterers within the framework of the Lorenz-Mie theory. We briefly introduce
the concept of conventional and unconventional Fano resonances in light
scattering. These resonances are associated with the interference between
electromagnetic modes excited in the particle with different or the same
multipole moment, respectively. In addition, we investigate the modification of
the spontaneous-emission rate of an optical emitter at the presence of a
plasmonic nanoshell. This modification of decay rate due to electromagnetic
environment is referred to as the Purcell effect. We analytically show that the
Purcell factor related to a dipole emitter oriented orthogonal or tangential to
the spherical surface can exhibit Fano or Lorentzian line shapes in the near
field, respectively.Comment: 28 pages, 10 figures; invited book chapter to appear in "Fano
Resonances in Optics and Microwaves: Physics and Application", Springer
Series in Optical Sciences (2018), edited by E. O. Kamenetskii, A. Sadreev,
and A. Miroshnichenk
Broadening of Plasmonic Resonance Due to Electron Collisions with Nanoparticle Boundary: а Quantum Mechanical Consideration
We present a quantum mechanical approach to calculate broadening of plasmonic
resonances in metallic nanostructures due to collisions of electrons with the
surface of the structure. The approach is applicable if the characteristic size
of the structure is much larger than the de Broglie electron wavelength in the
metal. The approach can be used in studies of plasmonic properties of both
single nanoparticles and arrays of nanoparticles.Comment: 9 page
Inevitable Evolutionary Temporal Elements in Neural Processing: A Study Based on Evolutionary Simulations
Recent studies have suggested that some neural computational mechanisms are based on the fine temporal structure of spiking activity. However, less effort has been devoted to investigating the evolutionary aspects of such mechanisms. In this paper we explore the issue of temporal neural computation from an evolutionary point of view, using a genetic simulation of the evolutionary development of neural systems. We evolve neural systems in an environment with selective pressure based on mate finding, and examine the temporal aspects of the evolved systems. In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment. In ten different simulated evolutionary sessions, there was an increased effect of time -related neural ablations on the agents' fitness. These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable. Future research using similar evolutionary simulations may shed new light on various biological mechanisms
Evolving Synaptic Plasticity with an Evolutionary Cellular Development Model
Since synaptic plasticity is regarded as a potential mechanism for memory formation and learning, there is growing interest in the study of its underlying mechanisms. Recently several evolutionary models of cellular development have been presented, but none have been shown to be able to evolve a range of biological synaptic plasticity regimes. In this paper we present a biologically plausible evolutionary cellular development model and test its ability to evolve different biological synaptic plasticity regimes. The core of the model is a genomic and proteomic regulation network which controls cells and their neurites in a 2D environment. The model has previously been shown to successfully evolve behaving organisms, enable gene related phenomena, and produce biological neural mechanisms such as temporal representations. Several experiments are described in which the model evolves different synaptic plasticity regimes using a direct fitness function. Other experiments examine the ability of the model to evolve simple plasticity regimes in a task -based fitness function environment. These results suggest that such evolutionary cellular development models have the potential to be used as a research tool for investigating the evolutionary aspects of synaptic plasticity and at the same time can serve as the basis for novel artificial computational systems
Associating Genes and Protein Complexes with Disease via Network Propagation
A fundamental challenge in human health is the identification of disease-causing genes. Recently, several studies have tackled this challenge via a network-based approach, motivated by the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. However, most of these approaches use only local network information in the inference process and are restricted to inferring single gene associations. Here, we provide a global, network-based method for prioritizing disease genes and inferring protein complex associations, which we call PRINCE. The method is based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. We exploit this function to predict not only genes but also protein complex associations with a disease of interest. We test our method on gene-disease association data, evaluating both the prioritization achieved and the protein complexes inferred. We show that our method outperforms extant approaches in both tasks. Using data on 1,369 diseases from the OMIM knowledgebase, our method is able (in a cross validation setting) to rank the true causal gene first for 34% of the diseases, and infer 139 disease-related complexes that are highly coherent in terms of the function, expression and conservation of their member proteins. Importantly, we apply our method to study three multi-factorial diseases for which some causal genes have been found already: prostate cancer, alzheimer and type 2 diabetes mellitus. PRINCE's predictions for these diseases highly match the known literature, suggesting several novel causal genes and protein complexes for further investigation
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