20 Gb/s mode-group-division multiplexing employing Hermite-Gaussian launches over worst-case multimode fiber links

For the first time, mode group division multiplexing is achieved in a multimode fiber link using a 2-D Hermite-Gaussian mode launch. 20 Gb/s error-free transmission is achieved over a 250 m worst-case OM1 multimode fiber link. © OSA 2014.

Bayesian inference and learning in Gaussian process state-space models with Particle MCMC

State-space models are successfully used in many areas of science, engineering and economics to model time series and dynamical systems. We present a fully Bayesian approach to inference and learning (i.e. state estimation and system identification) in nonlinear nonparametric state-space models. We place a Gaussian process prior over the state transition dynamics, resulting in a flexible model able to capture complex dynamical phenomena. To enable efficient inference, we marginalize over the transition dynamics function and, instead, infer directly the joint smoothing distribution using specially tailored Particle Markov Chain Monte Carlo samplers. Once a sample from the smoothing distribution is computed, the state transition predictive distribution can be formulated analytically. Our approach preserves the full nonparametric expressivity of the model and can make use of sparse Gaussian processes to greatly reduce computational complexity.

Classification using log Gaussian Cox processes

McCullagh and Yang (2006) suggest a family of classification algorithms based on Cox processes. We further investigate the log Gaussian variant which has a number of appealing properties. Conditioned on the covariates, the distribution over labels is given by a type of conditional Markov random field. In the supervised case, computation of the predictive probability of a single test point scales linearly with the number of training points and the multiclass generalization is straightforward. We show new links between the supervised method and classical nonparametric methods. We give a detailed analysis of the pairwise graph representable Markov random field, which we use to extend the model to semi-supervised learning problems, and propose an inference method based on graph min-cuts. We give the first experimental analysis on supervised and semi-supervised datasets and show good empirical performance.

A criterion for local interconvertibility between all-tripartite Gaussian states

We arrive at a necessary and sufficient criterion that can be readily used for interconvertibility between general, all-tripartite Gaussian states under local quantum operation. The derivation involves a systematic reduction that converts the original complex conditions in high-dimensional, 6n x 6n matrix space eventually into 2 x 2 matrix problems.

Conditions for the local manipulation of all bipartite Gaussian states

We provide a general, necessary, and sufficient condition for the possibility of transforming a mixed bipartite Gaussian state with arbitrarily many modes to another one under arbitrary local Gaussian channels, which do not include classical communication. Moreover, by means of this condition we present a necessary criterion that can be used to check the possibility of a state transformation between two mixed Gaussian states. At the same time, we prove that our criterion can be reduced to the Eisert-Plenio criterion when the mode number is chosen as 1 per side.

Conditions for the local manipulation of tripartite Gaussian states

We present the normal form of the covariance matrix for three-mode tripartite Gaussian states. By means of this result, the general form of a necessary and sufficient criterion for the possibility of a state transformation from one tripartite entangled Gaussian state to another with three modes is found. Moreover, we show that the conditions presented include not only inequalities but equalities as well.

On the representation of an inclined Gaussian beam

In most contemporary optics courses, Gaussian beams are demonstrated in the form of propagation along one coordinate axis. This is referred to as the conventional representation and is in fact a special form. In this paper, we derive the general representation of a Gaussian beam propagating obliquely to the coordinate axis, by performing a coordinate rotation transformation on the conventional representation. When doing so on the beam parameters, a restrictive condition has to be taken into account. Without this condition, the expressions for the beam parameters after the rotation are not consistent with the conventional ones.

Transverse trapping forces of focused Gaussian beam on ellipsoidal particles

A modified T-matrix method is presented to compute the scattered fields of various realistically shaped particles; then the radiation forces on the particles can be calculated via the Maxwell stress tenser integral. Numerical results of transverse trapping efficiencies of a focused Gaussian beam on ellipsoidal and spherical particles with the same volume are compared, which show that the shape and orientation of particles affect the maximal transverse trapping force and the displacement corresponding to the maximum. The effect of the polarization direction of the incident beam on the transverse trapping forces is also revealed. (c) 2007 Optical Society of America.

Accurate description of a radially polarized Gaussian beam

An accurate description of a radially polarized fundamental Gaussian beam is presented on the basis of complex-source-point spherical waves (CSPSWs). In contrast to other descriptions based on the perturbative Lax series, the expressions for the electromagnetic field components of this description have explicit and simple mathematical forms. Numerical calculations show that both paraxial and fifth-order corrected beam descriptions have large relative error when the diffraction angle is large, while the accurate description based on the CSPSW approach proposed here can give field expressions which satisfy Maxwell's equations with great accuracy.

Gaussian diffraction model for Sb thin films in super-resolution near-field structure

SPIE

Characteristics of beam profile of Gaussian beam passing through an axicon

Bessel beam can overcome the limitation of the Rayleigh range of Gaussian beam with the same spot size propagation without any spreading due to diffraction, which is considered as an useful function in guiding particles in the next generation of optical tweezers. The mathematical description of the Bessel beam generated by an axicon is usually based on the Fresnel diffraction integral theory. In this paper, we deduce another type of analytic expression suitable for describing the beam profile generated from the axicon illuminated by the Gaussian beam based on the interferential theory. Compared with the Fresnel diffraction integral theory, this theory does not use much approximation in the process of mathematical analysis. According to the derived expression, the beam intensity profiles at any positions behind the axicon can be calculated not just restricted inside the cross region as the Fresnel diffraction integral theory gives. The experiments prove that the theoretical results fit the experimental results very well. (C) 2004 Elsevier B.V. All rights reserved.