Three-Dimensional Light Bullets in Arrays of Waveguides

We report the first experimental observation of 3D-LBs, excited by femtosecond pulses in a system featuring quasi-instantaneous cubic nonlinearity and a periodic, transversally-modulated refractive index. Stringent evidence of the excitation of LBs is based on time-gated images and spectra which perfectly match our numerical simulations. Furthermore, we reveal a novel evolution mechanism forcing the LBs to follow varying dispersion/diffraction conditions, until they leave their existence range and decay.Comment: 4 pages, 5 figures - Published by the American Physical Societ

Modulational instability in nonlocal Kerr-type media with random parameters

Modulational instability of continuous waves in nonlocal focusing and defocusing Kerr media with stochastically varying diffraction (dispersion) and nonlinearity coefficients is studied both analytically and numerically. It is shown that nonlocality with the sign-definite Fourier images of the medium response functions suppresses considerably the growth rate peak and bandwidth of instability caused by stochasticity. Contrary, nonlocality can enhance modulational instability growth for a response function with negative-sign bands.Comment: 6 pages, 12 figures, revTeX, to appear in Phys. Rev.

Separating a Real-Life Nonlinear Image Mixture

When acquiring an image of a paper document, the image printed on the back page sometimes shows through. The mixture of the front- and back-page images thus obtained is markedly nonlinear, and thus constitutes a good real-life test case for nonlinear blind source separation. This paper addresses a difficult version of this problem, corresponding to the use of "onion skin" paper, which results in a relatively strong nonlinearity of the mixture, which becomes close to singular in the lighter regions of the images. The separation is achieved through the MISEP technique, which is an extension of the well known INFOMAX method. The separation results are assessed with objective quality measures. They show an improvement over the results obtained with linear separation, but have room for further improvement

Nonlinear Hebbian learning as a unifying principle in receptive field formation

The development of sensory receptive fields has been modeled in the past by a variety of models including normative models such as sparse coding or independent component analysis and bottom-up models such as spike-timing dependent plasticity or the Bienenstock-Cooper-Munro model of synaptic plasticity. Here we show that the above variety of approaches can all be unified into a single common principle, namely Nonlinear Hebbian Learning. When Nonlinear Hebbian Learning is applied to natural images, receptive field shapes were strongly constrained by the input statistics and preprocessing, but exhibited only modest variation across different choices of nonlinearities in neuron models or synaptic plasticity rules. Neither overcompleteness nor sparse network activity are necessary for the development of localized receptive fields. The analysis of alternative sensory modalities such as auditory models or V2 development lead to the same conclusions. In all examples, receptive fields can be predicted a priori by reformulating an abstract model as nonlinear Hebbian learning. Thus nonlinear Hebbian learning and natural statistics can account for many aspects of receptive field formation across models and sensory modalities

The Mid-Infrared Instrument for the James Webb Space Telescope, VII: The MIRI Detectors

The MIRI Si:As IBC detector arrays extend the heritage technology from the Spitzer IRAC arrays to a 1024 x 1024 pixel format. We provide a short discussion of the principles of operation, design, and performance of the individual MIRI detectors, in support of a description of their operation in arrays provided in an accompanying paper (Ressler et al. (2015)). We then describe modeling of their response. We find that electron diffusion is an important component of their performance, although it was omitted in previous models. Our new model will let us optimize the bias voltage while avoiding avalanche gain. It also predicts the fraction of the IR-active layer that is depleted (and thus contributes to the quantum efficiency) as signal is accumulated on the array amplifier. Another set of models accurately predicts the nonlinearity of the detector-amplifier unit and has guided determination of the corrections for nonlinearity. Finally, we discuss how diffraction at the interpixel gaps and total internal reflection can produce the extended cross-like artifacts around images with these arrays at short wavelengths, ~ 5 microns. The modeling of the behavior of these devices is helping optimize how we operate them and also providing inputs to the development of the data pipeline