A survey of uncertainty principles and some signal processing applications

The goal of this paper is to review the main trends in the domain of uncertainty principles and localization, emphasize their mutual connections and investigate practical consequences. The discussion is strongly oriented towards, and motivated by signal processing problems, from which significant advances have been made recently. Relations with sparse approximation and coding problems are emphasized

Primordial density perturbations with running spectral index: impact on non-linear cosmic structures

(abridged) We explore the statistical properties of non-linear cosmic structures in a flat $\Lambda$CDM cosmology in which the index of the primordial power spectrum for scalar perturbations is allowed to depend on the scale. Within the inflationary paradigm, the running of the scalar spectral index can be related to the properties of the inflaton potential, and it is hence of critical importance to test it with all kinds of observations, which cover the linear and non-linear regime of gravitational instability. We focus on the amount of running $\alpha_{\mathrm{S},0}$ allowed by an updated combination of CMB anisotropy data and the 2dF Galaxy Redshift Survey. Our analysis constrains $\alpha_{\mathrm{S},0} = -0.051^{+0.047}_{-0.053}$ $(-0.034^{+0.039}_{-0.040})$ at 95% Confidence Level when (not) taking into account primordial gravitational waves in a ratio as predicted by canonical single field inflation, in agreement with other works. For the cosmological models best fitting the data both with and without running we studied the abundance of galaxy clusters and of rare objects, the halo bias, the concentration of dark matter halos, the Baryon Acoustic Oscillation, the power spectrum of cosmic shear, and the Integrated Sachs-Wolfe effect. We find that counting galaxy clusters in future X-ray and Sunyaev-Zel'dovich surveys could discriminate between the two models, more so if broad redshift information about the cluster samples will be available. Likewise, measurements of the power spectrum of cosmological weak lensing as performed by planned all-sky optical surveys such as EUCLID could detect a running of the primordial spectral index, provided the uncertainties about the source redshift distribution and the underlying matter power spectrum are well under control.Comment: 17 pages, 14 figures, 4 tables. Accepted for publication on MNRA

Institutional paraconsciousness and its pathologies

This analysis extends a recent mathematical treatment of the Baars consciousness model to analogous, but far more complicated, phenomena of institutional cognition. Individual consciousness is limited to a single, tunable, giant component of interacting cognitive modules, instantiating a Global Workspace. Human institutions, by contrast, support several, sometimes many, such giant components simultaneously, although their behavior remains constrained to a topology generated by cultural context and by the path-dependence inherent to organizational history. Such highly parallel multitasking - institutional paraconsciousness - while clearly limiting inattentional blindness and the consequences of failures within individual workspaces, does not eliminate them, and introduces new characteristic dysfunctions involving the distortion of information sent between global workspaces. Consequently, organizations (or machines designed along these principles), while highly efficient at certain kinds of tasks, remain subject to canonical and idiosyncratic failure patterns similar to, but more complicated than, those afflicting individuals. Remediation is complicated by the manner in which pathogenic externalities can write images of themselves on both institutional function and therapeutic intervention, in the context of relentless market selection pressures. The approach is broadly consonant with recent work on collective efficacy, collective consciousness, and distributed cognition

Information transmission in genetic regulatory networks: a review

Genetic regulatory networks enable cells to respond to the changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between network's inputs and its outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary to understand recent work. We then discuss the functional complexity of gene regulation which arrises from the molecular nature of the regulatory interactions. We end by reviewing some experiments supporting the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional' information.Comment: Submitted to J Phys: Condens Matter, 31 page

Spatiospectral concentration of vector fields on a sphere

We construct spherical vector bases that are bandlimited and spatially concentrated, or, alternatively, spacelimited and spectrally concentrated, suitable for the analysis and representation of real-valued vector fields on the surface of the unit sphere, as arises in the natural and biomedical sciences, and engineering. Building on the original approach of Slepian, Landau, and Pollak we concentrate the energy of our function bases into arbitrarily shaped regions of interest on the sphere, and within certain bandlimits in the vector spherical-harmonic domain. As with the concentration problem for scalar functions on the sphere, which has been treated in detail elsewhere, a Slepian vector basis can be constructed by solving a finite-dimensional algebraic eigenvalue problem. The eigenvalue problem decouples into separate problems for the radial and tangential components. For regions with advanced symmetry such as polar caps, the spectral concentration kernel matrix is very easily calculated and block-diagonal, lending itself to efficient diagonalization. The number of spatiospectrally well-concentrated vector fields is well estimated by a Shannon number that only depends on the area of the target region and the maximal spherical-harmonic degree or bandwidth. The spherical Slepian vector basis is doubly orthogonal, both over the entire sphere and over the geographic target region. Like its scalar counterparts it should be a powerful tool in the inversion, approximation and extension of bandlimited fields on the sphere: vector fields such as gravity and magnetism in the earth and planetary sciences, or electromagnetic fields in optics, antenna theory and medical imaging.Comment: Submitted to Applied and Computational Harmonic Analysi