arXiv subjects

Maria Longobardi

Publications and source records attributed to Maria Longobardi.

17 recordsLinked to original sources

arXiv2025

Accelerating the drive towards energy-efficient generative AI with quantum computing algorithms

Research and usage of artificial intelligence, particularly generative and large language models, have rapidly progressed over the last years. This has, however, given rise to issues due to high energy consumption. While quantum computing is not (yet) mainstream, its intersection with machine learning is especially promising, and the technology could alleviate some of these energy challenges. In this perspective article, we break down the lifecycle stages of large language models and discuss relevant enhancements based on quantum algorithms that may aid energy efficiency and sustainability, including industry application examples and open research problems.

quant-ph↗

arXiv2021

Informal Science Education and Career Advancement

This document supports a proposed APS statement that encourages academic, research, and other institutions to add the participation in informal science education activities to the criteria they use for hiring and career advancement decisions. There is a prevalent attitude that the time spent by a researcher on these activities takes time away from research efforts that are more valued by their peers and their institution. To change this mindset, we enumerate the many benefits of informal science education activities to the public, to researchers, to their institutions, and to the field of physics. We also suggest aspects of these activities that may be considered by institutions in evaluating informal educational efforts for recruitment and career advancement decisions.

physics.soc-ph↗

arXiv2021

Dispersion indices based on Kerridge inaccuracy and Kullback-Leibler divergence

The concept of varentropy has been recently introduced as a dispersion index of the reliability of measure of information. In this paper, we introduce new measures of variability for two measures of uncertainty, the Kerridge inaccuracy measure and the Kullback-Leibler divergence. These new definitions and related properties, bounds and examples are presented. Finally we show an application of Kullback-Leibler divergence and its dispersion index using the mean-variance rule.

math.PR↗

arXiv2021

Interval extropy and weighted interval extropy

Recently, Extropy was introduced by Lad, Sanfilippo and Agrò as a complement dual of Shannon Entropy. In this paper, we propose dynamic versions of Extropy for doubly truncated random variables as measures of uncertainty called Interval Extropy and Weighted Interval Extropy. Some characterizations of random variables related to these new measures are given. Several examples are shown. These measures are evaluated under the effect of linear transformations and, finally, some bounds for them are presented.

math.PR↗

arXiv2021

On Tsallis extropy with an application to pattern recognition

Recently, a new measure of information called extropy has been introduced by Lad, Sanfilippo and Agrò as the dual version of Shannon entropy. In the literature, Tsallis introduced a measure for a discrete random variable, named Tsallis entropy, as a generalization of Boltzmann-Gibbs statistics. In this work, a new measure of discrimination, called Tsallis extropy, is introduced and some of its properties are then discussed. The relation between Tsallis extropy and entropy is given and some bounds are also presented. Finally, an application of this extropy to pattern recognition is demonstrated.

math.PR↗

arXiv2021

Asymptotic results for linear combinations of spacings generated by i.i.d. exponential random variables

We prove large (and moderate) deviations for a class of linear combinations of spacings generated by i.i.d. exponentially distributed random variables. We allow a wide class of coefficients which can be expressed in terms of continuous functions defined on [0, 1] which satisfy some suitable conditions. In this way we generalize some recent results by Giuliano et al. (2015) which concern the empirical cumulative entropies defined in Di Crescenzo and Longobardi (2009a).

math.PR↗

arXiv2021

On cumulative residual (past) inaccuracy for truncated random variables

To overcome the drawbacks of Shannon's entropy, the concept of cumulative residual and past entropy has been proposed in the information theoretic literature. Furthermore, the Shannon entropy has been generalized in a number of different ways by many researchers. One important extension is Kerridge inaccuracy measure. In the present communication we study the cumulative residual and past inaccuracy measures, which are extensions of the corresponding cumulative entropies. Several properties, including monotonicity and bounds, are obtained for left, right and doubly truncated random variables.

cs.IT↗

arXiv2020

Distortion Representations of Multivariate Distributions

The univariate distorted distribution were introduced in risk theory to represent changes (distortions) in the expected distributions of some risks. Later they were also applied to represent distributions of order statistics, coherent systems, proportional hazard rate (PHR) and proportional reversed hazard rate (PRHR) models, etc. In this paper we extend this concept to the multivariate setup. We show that, in some cases, they are a valid alternative to the copula representations especially when the marginal distributions may not be easily handled. Several relevant examples illustrate the applications of such representations in statistical modeling. They include the study of paired (dependent) ordered data, joint residual lifetimes, order statistics and coherent systems.

math.ST↗

arXiv2020

On Generalized Reversed Aging Intensity Functions

The reversed aging intensity function is defined as the ratio of the instantaneous reversed hazard rate to the baseline value of the reversed hazard rate. It analyzes the aging property quantitatively, the higher the reversed aging intensity, the weaker the tendency of aging. In this paper, a family of generalized reversed aging intensity functions is introduced and studied. Those functions depend on a real parameter. If the parameter is positive they characterize uniquely the distribution functions of univariate positive absolutely continuous random variables, in the opposite case they characterize families of distributions. Furthermore, the generalized reversed aging intensity orders are defined and studied. Finally, several numerical examples are given.

math.ST↗

arXiv2020

On cumulative entropies in terms of moments of order statistics

In this paper relations among some kinds of cumulative entropies and moments of order statistics are presented. By using some characterizations and the symmetry of a non negative and absolutely continuous random variable X, lower and upper bounds for entropies are obtained and examples are given.

math.ST↗

arXiv2020

Cumulative Residual Extropy of Minimum Ranked Set Sampling with Unequal Samples

Recently, an alternative measure of uncertainty called cumulative residual extropy (CREX) was proposed by Jahanshahi et al. (2019). In this paper, we consider uncertainty measures of minimum ranked set sampling procedure with unequal samples (MinRSSU) in terms of CREX and its dynamic version and we compare the uncertainty and information content of CREX based on MinRSSU and simple random sampling (SRS) designs. Also, using simulation, we study on new estimators of CREX for MinRSSU and SRS designs in terms of bias and mean square error. Finally, we provide a new discrimination measure of disparity between the distribution of MinRSSU and parental data SRS.

math.ST↗

arXiv2020

On Weighted Extropies

The extropy is a measure of information introduced by Lad et al. (2015) as dual to entropy. As the entropy, it is a shift-independent information measure. We introduce here the notion of weighted extropy, a shift-dependent information measure which gives higher weights to large values of observed random variables. We also study the weighted residual and past extropies as weighted versions of extropy for residual and past lifetimes. Bivariate versions extropy and weighted extropy are also provided. Several examples are presented through out to illustrate the various concepts introduced here.

math.ST↗

arXiv2020

Varentropy of past lifetimes

In Reliability Theory, uncertainty is measured by the Shannon entropy. Recently, in order to analyze the variability of such measure, varentropy has been introduced and studied. In this paper we define a new concept of varentropy for past lifetime distributions as the variability of uncertainty in past lifetime. We analyze the relation of this varentropy with the corresponding past entropy and other concepts of interest in reliability and we study the effect of linear and monotonic transformations on it. Finally, we evaluate past varentropy for random variables following a proportional reversed hazard rate model.

math.PR↗

arXiv2016

On dynamic mutual information for bivariate lifetimes

We consider dynamic versions of the mutual information of lifetime distributions, with focus on past lifetimes, residual lifetimes and mixed lifetimes evaluated at different instants. This allows to study multicomponent systems, by measuring the dependence in conditional lifetimes of two components having possibly different ages. We provide some bounds, and investigate the mutual information of residual lifetimes within the time-transformed exponential model (under both the assumptions of unbounded and truncated lifetimes). Moreover, with reference to the order statistics of a random sample, we evaluate explicitly the mutual information between the minimum and the maximum, conditional on inspection at different times, and show that it is distribution-free. Finally, we develop a copula-based approach aiming to express the dynamic mutual information for past and residual bivariate lifetimes in an alternative way.

math.PR↗

arXiv2014

Surface transport and band gap structure of exfoliated 2H-MoTe$_2$ crystals

Semiconducting transition metal dichalcogenides (TMDs) have emerged as materials that can be used to realize two-dimensional (2D) crystals possessing rather unique transport and optical properties. Most research has so far focused on sulfur and selenium compounds, while tellurium-based materials attracted little attention so far. As a first step in the investigation of Te-based semiconducting TMDs in this context, we have studied MoTe$_2$ crystals with thicknesses above 4 nm, focusing on surface transport and a quantitative determination of the gap structure. Using ionic-liquid gated transistors, we show that ambipolar transport at the surface of the material is reproducibly achieved, with hole and electron mobility values between 10 and 30 cm$^2$/Vs at room temperature. The gap structure is determined through three different techniques: ionic-liquid gated transistors and scanning tunneling spectroscopy, that allow the measurement of the indirect gap ($E_{ind}$), and optical transmission spectroscopy on crystals of different thickness, that enables the determination of both the direct ($E_{dir}$) and the indirect gap. We find that at room temperature $E_{ind}$ = 0.88 eV and $E_{dir}$ = 1.02 eV. Our results suggest that thin MoTe$_2$ layers may exhibit a transition to a direct gap before mono-layer thickness. They should also drastically extend the range of direct gaps accessible in 2D semiconducting TMDs.

cond-mat.mes-hall↗

arXiv2011

On Weighted Residual and Past Entropies

We consider a "length-biased" shift-dependent information measure, related to the differential entropy in which higher weight is assigned to large values of observed random variables. This allows us to introduce the notions of "weighted residual entropy" and "weighted past entropy", that are suitable to describe dynamic information of random lifetimes, in analogy with the entropies of residual and past lifetimes introduced in [9] and [6], respectively. The obtained results include their behaviors under monotonic transformations.

math.ST↗

arXiv2008

Competing risks within shock models

We consider a competing risks model, in which system failures are due to one out of two mutually exclusive causes, formulated within the framework of shock models driven by bivariate Poisson process. We obtain the failure densities and the survival functions as well as other related quantities under three different schemes. Namely, system failures are assumed to occur at the first instant in which a random constant threshold is reached by (a) the sum of received shocks, (b) the minimum of shocks, (c) the maximum of shocks.

math.PR↗