Superstatistical generalisations of Wishart-Laguerre ensembles of random matrices

Using Beck and Cohen's superstatistics, we introduce in a systematic way a family of generalized Wishart–Laguerre ensembles of random matrices with Dyson index β = 1, 2 and 4. The entries of the data matrix are Gaussian random variables whose variances η fluctuate from one sample to another according to a certain probability density f(η) and a single deformation parameter γ. Three superstatistical classes for f(η) are usually considered: χ2-, inverse χ2- and log-normal distributions. While the first class, already considered by two of the authors, leads to a power-law decay of the spectral density, we here introduce and solve exactly a superposition of Wishart–Laguerre ensembles with inverse χ2-distribution. The corresponding macroscopic spectral density is given by a γ-deformation of the semi-circle and Marčenko–Pastur laws, on a non-compact support with exponential tails. After discussing in detail the validity of Wigner's surmise in the Wishart–Laguerre class, we introduce a generalized γ-dependent surmise with stretched-exponential tails, which well approximates the individual level spacing distribution in the bulk. The analytical results are in excellent agreement with numerical simulations. To illustrate our findings we compare the χ2- and inverse χ2-classes to empirical data from financial covariance matrices

Random pure states: quantifying bipartite entanglement beyond the linear statistics

We analyze the properties of entangled random pure states of a quantum system partitioned into two smaller subsystems of dimensions $N$ and $M$. Framing the problem in terms of random matrices with a fixed-trace constraint, we establish, for arbitrary $N \leq M$, a general relation between the $n$-point densities and the cross-moments of the eigenvalues of the reduced density matrix, i.e. the so-called Schmidt eigenvalues, and the analogous functionals of the eigenvalues of the Wishart-Laguerre ensemble of the random matrix theory. This allows us to derive explicit expressions for two-level densities, and also an exact expression for the variance of von Neumann entropy at finite $N,M$. Then we focus on the moments $\mathbb{E}\{K^a\}$ of the Schmidt number $K$, the reciprocal of the purity. This is a random variable supported on $[1,N]$, which quantifies the number of degrees of freedom effectively contributing to the entanglement. We derive a wealth of analytical results for $\mathbb{E}\{K^a\}$ for $N = 2$ and $N=3$ and arbitrary $M$, and also for square $N = M$ systems by spotting for the latter a connection with the probability $P(x_{min}^{GUE} \geq \sqrt{2N}\xi)$ that the smallest eigenvalue $x_{min}^{GUE}$ of a $N\times N$ matrix belonging to the Gaussian Unitary Ensemble is larger than $\sqrt{2N}\xi$. As a byproduct, we present an exact asymptotic expansion for $P(x_{min}^{GUE} \geq \sqrt{2N}\xi)$ for finite $N$ as $\xi \to \infty$. Our results are corroborated by numerical simulations whenever possible, with excellent agreement.Comment: 22 pages, 8 figures. Minor changes, typos fixed. Accepted for publication in PR

DEVELOPMENT POLICIES IN SOUTHERN ITALY BETWEEN GOVERNMENT AND GOVERNANCE

The paper has analysed outputs generated by the development policies implemented in last decades in the South of Italy, starting from the Extraordinary Intervention (since 1950, until 1992) to the European cohesion policy (since 1996). The first one was a high-centralized development policy. Differently, the European cohesion policy is based on multilevel governance, and follows a bottom-up approach oriented to stimulate local stakeholders’ participation. The analysis, exposed in previous paragraphs, has described these two different policy experiences, the related effects on local development and on convergence between North and South of Italy and among European regions. The paper has tried to answer to a fundamental question: what factors have negatively affected the implementation of these policies, generating unexpected effects

Occlusion points identification algorithm

In this paper a very simple and efficient algorithm is proposed, to calculate the invisible regions of a scene, or shadowed side of a body, when it is observed from a pre-set point. This is done by applying a deterministic numerical procedure to the portion of scene in the field of view, after having been projected in the observer reference frame. The great advantage of this approach is its generality and suitability for a wide number of applications. They span from real time renderings, to the simulation of different types of light sources, such as diffused or collimated, or simply to calculate the effective visible surface for a camera mounted on board of an aircraft, in order to optimize its trajectory if remote sensing or aerial mapping task should be carried out. Optimizing the trajectory, by minimizing at any time the occluded surface, is also a powerful solution for a search and rescue mission, because a wider area in a shorter time can be observed, particularly in situations where the time is a critical parameter, such as, during a forest fire or in case of avalanches. For its simplicity of implementation, the algorithm is suitable for real time applications, providing an extremely accurate solution in a fraction of a millisecond. In this paper, the algorithm has been tested by calculating the occluded regions of a very complex mountainous scenario, seen from a gimbal-camera mounted on board of a flying platform

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 $N$ and the sample size $M$ used to define empirical averages diverge, with their ratio $\alpha=N/M$ kept fixed. We find a remarkable scaling relation which expresses the spectral density $\rho(\lambda)$ of sample auto-covariance matrices for processes with dynamical correlations as a continuous superposition of appropriately rescaled copies of the spectral density $\rho^{(0)}_\alpha(\lambda)$ for a sequence of uncorrelated random variables. The rescaling factors are given by the Fourier transform $\hat C(q)$ of the auto-covariance function of the stochastic process. We also obtain a closed-form approximation for the scaling function $\rho^{(0)}_\alpha(\lambda)$. This depends on the shape parameter $\alpha$, 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

"Spectrally gapped" random walks on networks: a Mean First Passage Time formula

We derive an approximate but explicit formula for the Mean First Passage Time of a random walker between a source and a target node of a directed and weighted network. The formula does not require any matrix inversion, and it takes as only input the transition probabilities into the target node. It is derived from the calculation of the average resolvent of a deformed ensemble of random sub-stochastic matrices H = ⟨ H ⟩ + δ H, with ⟨ H ⟩ rank- 1 and non-negative. The accuracy of the formula depends on the spectral gap of the reduced transition matrix, and it is tested numerically on several instances of (weighted) networks away from the high sparsity regime, with an excellent agreement

Jacobi Crossover Ensembles of Random Matrices and Statistics of Transmission Eigenvalues

We study the transition in conductance properties of chaotic mesoscopic cavities as time-reversal symmetry is broken. We consider the Brownian motion model for transmission eigenvalues for both types of transitions, viz., orthogonal-unitary and symplectic-unitary crossovers depending on the presence or absence of spin-rotation symmetry of the electron. In both cases the crossover is governed by a Brownian motion parameter {\tau}, which measures the extent of time-reversal symmetry breaking. It is shown that the results obtained correspond to the Jacobi crossover ensembles of random matrices. We derive the level density and the correlation functions of higher orders for the transmission eigenvalues. We also obtain the exact expressions for the average conductance, average shot-noise power and variance of conductance, as functions of {\tau}, for arbitrary number of modes (channels) in the two leads connected to the cavity. Moreover, we give the asymptotic result for the variance of shot-noise power for both the crossovers, the exact results being too long. In the {\tau} \rightarrow 0 and {\tau} \rightarrow \infty limits the known results for the orthogonal (or symplectic) and unitary ensembles are reproduced. In the weak time-reversal symmetry breaking regime our results are shown to be in agreement with the semiclassical predictions.Comment: 24 pages, 5 figure

Optimization of graphene-based materials outperforming host epoxy matrices

The degree of graphite exfoliation and edge-carboxylated layers can be controlled and balanced to design lightweight materials characterized by both low electrical percolation thresholds (EPT) and improved mechanical properties. So far, this challenging task has been undoubtedly very hard to achieve. The results presented in this paper highlight the effect of exfoliation degree and the role of edge-carboxylated graphite layers to give self-assembled structures embedded in the polymeric matrix. Graphene layers inside the matrix may serve as building blocks of complex systems that could outperform the host matrix. Improvements in electrical percolation and mechanical performance have been obtained by a synergic effect due to finely balancing the degree of exfoliation and the chemistry of graphene edges which favors the interfacial interaction between polymer and carbon layers. In particular, for epoxy-based resins including two partially exfoliated graphite samples, differing essentially in the content of carboxylated groups, the percolation threshold reduces from 3 wt% down to 0.3 wt%, as the carboxylated group content increases up to 10 wt%. Edge-carboxylated nanosheets also increase the nanofiller/epoxy matrix interaction, determining a relevant reinforcement in the elastic modulus

Number statistics for β\beta-ensembles of random matrices: applications to trapped fermions at zero temperature

Let $\mathcal{P}_{\beta}^{(V)} (N_{\cal I})$ be the probability that a $N\times N$ $\beta$-ensemble of random matrices with confining potential $V(x)$ has $N_{\cal I}$ eigenvalues inside an interval ${\cal I}=[a,b]$ of the real line. We introduce a general formalism, based on the Coulomb gas technique and the resolvent method, to compute analytically $\mathcal{P}_{\beta}^{(V)} (N_{\cal I})$ for large $N$. We show that this probability scales for large $N$ as $\mathcal{P}_{\beta}^{(V)} (N_{\cal I})\approx \exp\left(-\beta N^2 \psi^{(V)}(N_{\cal I} /N)\right)$, where $\beta$ is the Dyson index of the ensemble. The rate function $\psi^{(V)}(k_{\cal I})$, independent of $\beta$, is computed in terms of single integrals that can be easily evaluated numerically. The general formalism is then applied to the classical $\beta$-Gaussian (${\cal I}=[-L,L]$), $\beta$-Wishart (${\cal I}=[1,L]$) and $\beta$-Cauchy (${\cal I}=[-L,L]$) ensembles. Expanding the rate function around its minimum, we find that generically the number variance ${\rm Var}(N_{\cal I})$ exhibits a non-monotonic behavior as a function of the size of the interval, with a maximum that can be precisely characterized. These analytical results, corroborated by numerical simulations, provide the full counting statistics of many systems where random matrix models apply. In particular, we present results for the full counting statistics of zero temperature one-dimensional spinless fermions in a harmonic trap.Comment: 34 pages, 19 figure

Surface figure correction using differential deposition of WSi2_2

The surface figure of an x-ray mirror was improved by differential deposition of WSi$_2$ layers. DC magnetron sputtering through beam-defining apertures was applied on moving substrates to generate thin films with arbitrary longitudinal thickness variations. The required velocity profiles were calculated using a deconvolution algorithm. Height errors were evaluated after each correction iteration using offline visible light surface metrology. WSi$_2$ was selected as a promising material since it conserves the initial substrate surface roughness and limits the film stress to acceptable levels. On a 300 mm long flat Si mirror the shape error was reduced to less than 0.2 nm RMS