243 research outputs found
Distortion-Memory Tradeoffs in Cache-Aided Wireless Video Delivery
Mobile network operators are considering caching as one of the strategies to
keep up with the increasing demand for high-definition wireless video
streaming. By prefetching popular content into memory at wireless access points
or end user devices, requests can be served locally, relieving strain on
expensive backhaul. In addition, using network coding allows the simultaneous
serving of distinct cache misses via common coded multicast transmissions,
resulting in significantly larger load reductions compared to those achieved
with conventional delivery schemes. However, prior work does not exploit the
properties of video and simply treats content as fixed-size files that users
would like to fully download. Our work is motivated by the fact that video can
be coded in a scalable fashion and that the decoded video quality depends on
the number of layers a user is able to receive. Using a Gaussian source model,
caching and coded delivery methods are designed to minimize the squared error
distortion at end user devices. Our work is general enough to consider
heterogeneous cache sizes and video popularity distributions.Comment: To appear in Allerton 2015 Proceedings of the 53rd annual Allerton
conference on Communication, control, and computin
Large Deviations of the Smallest Eigenvalue of the Wishart-Laguerre Ensemble
We consider the large deviations of the smallest eigenvalue of the
Wishart-Laguerre Ensemble. Using the Coulomb gas picture we obtain rate
functions for the large fluctuations to the left and the right of the hard
edge. Our findings are compared with known exact results for finding
good agreement. We also consider the case of almost square matrices finding new
universal rate functions describing large fluctuations.Comment: 4 pages, 2 figure
SIRT1 Activity Is Linked to Its Brain Region-Specific Phosphorylation and Is Impaired in Huntingtonâs Disease Mice
Huntingtons disease (HD) is a neurodegenerative disorder for which there are no disease-modifying treatments. SIRT1 is a NAD+-dependent protein deacetylase that is implicated in maintaining neuronal health during development, differentiation and ageing. Previous studies suggested that the modulation of SIRT1 activity is neuroprotective in HD mouse models, however, the mechanisms controlling SIRT1 activity are unknown. We have identified a striatum-specific phosphorylation-dependent regulatory mechanism of SIRT1 induction under normal physiological conditions, which is impaired in HD. We demonstrate that SIRT1 activity is down-regulated in the brains of two complementary HD mouse models, which correlated with altered SIRT1 phosphorylation levels. This SIRT1 impairment could not be rescued by the ablation of DBC1, a negative regulator of SIRT1, but was linked to changes in the sub-cellular distribution of AMPK-α1, a positive regulator of SIRT1 function. This work provides insights into the regulation of SIRT1 activity with the potential for the development of novel therapeutic strategies
A Study of Problem Posing as a Means to Help Mathematics Teachers Foster Creativity
Research suggests that mathematical creativity often results from extended periods of mathematical activity and reflection based on the use of deep and flexible content knowledge [14, 15]. This implies that instruction can influence creativity. However, for teaching to foster creativity in mathematics, there should be purposefully designed instructional tasks. It is doubtful that routine, mechanical exercises would foster creativity. Moreover, mathematical creativity may neither be explicitly promoted, nor fully appreciated, by students when a learning space involves only problem solving, even if the problems are challenging and engaging. For students to get an authentic sense of mathematics and to develop habits that are more likely to lead to an appreciation of mathematical creativity, they need to experience both problem solving and problem posing, as both are âessential aspects of mathematical activityâ [22, page 31]
Eigenvalues and Singular Values of Products of Rectangular Gaussian Random Matrices
We derive exact analytic expressions for the distributions of eigenvalues and
singular values for the product of an arbitrary number of independent
rectangular Gaussian random matrices in the limit of large matrix dimensions.
We show that they both have power-law behavior at zero and determine the
corresponding powers. We also propose a heuristic form of finite size
corrections to these expressions which very well approximates the distributions
for matrices of finite dimensions.Comment: 13 pages, 3 figure
Eigenvalue distributions for some correlated complex sample covariance matrices
The distributions of the smallest and largest eigenvalues for the matrix
product , where is an complex Gaussian matrix
with correlations both along rows and down columns, are expressed as determinants. In the case of correlation along rows, these expressions are
computationally more efficient than those involving sums over partitions and
Schur polynomials reported recently for the same distributions.Comment: 11 page
Spectral Density of Sparse Sample Covariance Matrices
Applying the replica method of statistical mechanics, we evaluate the
eigenvalue density of the large random matrix (sample covariance matrix) of the
form , where is an real sparse random matrix.
The difference from a dense random matrix is the most significant in the tail
region of the spectrum. We compare the results of several approximation
schemes, focusing on the behavior in the tail region.Comment: 22 pages, 4 figures, minor corrections mad
Spectra of sparse non-Hermitian random matrices: an analytical solution
We present the exact analytical expression for the spectrum of a sparse
non-Hermitian random matrix ensemble, generalizing two classical results in
random-matrix theory: this analytical expression forms a non-Hermitian version
of the Kesten-Mckay law as well as a sparse realization of Girko's elliptic
law. Our exact result opens new perspectives in the study of several physical
problems modelled on sparse random graphs. In this context, we show
analytically that the convergence rate of a transport process on a very sparse
graph depends upon the degree of symmetry of the edges in a non-monotonous way.Comment: 5 pages, 5 figures, 12 pages supplemental materia
Spectra of Empirical Auto-Covariance Matrices
We compute spectra of sample auto-covariance matrices of second order
stationary stochastic processes. We look at a limit in which both the matrix
dimension and the sample size used to define empirical averages
diverge, with their ratio kept fixed. We find a remarkable scaling
relation which expresses the spectral density of sample
auto-covariance matrices for processes with dynamical correlations as a
continuous superposition of appropriately rescaled copies of the spectral
density for a sequence of uncorrelated random
variables. The rescaling factors are given by the Fourier transform
of the auto-covariance function of the stochastic process. We also obtain a
closed-form approximation for the scaling function
. This depends on the shape parameter , but
is otherwise universal: it is independent of the details of the underlying
random variables, provided only they have finite variance. Our results are
corroborated by numerical simulations using auto-regressive processes.Comment: 4 pages, 2 figure
Random matrix techniques in quantum information theory
The purpose of this review article is to present some of the latest
developments using random techniques, and in particular, random matrix
techniques in quantum information theory. Our review is a blend of a rather
exhaustive review, combined with more detailed examples -- coming from research
projects in which the authors were involved. We focus on two main topics,
random quantum states and random quantum channels. We present results related
to entropic quantities, entanglement of typical states, entanglement
thresholds, the output set of quantum channels, and violations of the minimum
output entropy of random channels
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