Candidates for non-baryonic dark matter

This report is a brief review of the efforts to explain the nature of non-baryonic dark matter and of the studies devoted to the search for relic particles. Among the different dark matter candidates, special attention is devoted to relic neutralinos, by giving an overview of the recent calculations of its relic abundance and detection rates in a wide variety of supersymmetric schemes.Comment: 13 pages, 10 figures, typeset with ReVTeX, uses espcrc2.sty. Invited review talk presented at "Topics in Astroparticle and Underground Physics (TAUP 2001)" Laboratori Nazionali del Gran Sasso, Italy, September 8-12, 2001. References added. The paper may also be downloaded from http://www.to.infn.it/~fornengo/proceedings/taup01.ps.g

Particle dark matter searches in the anisotropic sky

Anisotropies in the electromagnetic emission produced by dark matter annihilation or decay in the extragalactic sky are a recent tool in the quest for a particle dark matter evidence. We review the formalism to compute the two-point angular power spectrum in the halo-model approach and discuss the features and the relative size of the various auto- and cross-correlation signals that can be envisaged for anisotropy studies. From the side of particle dark matter signals, we consider the full multi-wavelength spectrum, from the radio emission to X-ray and gamma-ray productions. We discuss the angular power spectra of the auto-correlation of each of these signals and of the cross-correlation between any pair of them. We then extend the search to comprise specific gravitational tracers of dark matter distribution in the Universe: weak-lensing cosmic shear, large-scale-structure matter distribution and CMB-lensing. We have shown that cross-correlating a multi-wavelength dark matter signal (which is a direct manifestation of its particle physics nature) with a gravitational tracer (which is a manifestation of the presence of large amounts of unseen matter in the Universe) may offer a promising tool to demonstrate that what we call dark matter is indeed formed by elementary particles.Comment: 16 pages, 11 figures. Prepared as inaugural article for Frontiers in High-Energy and Astroparticle Physics. v2: few comments added, to appear in Frontiers (Hypothesis and Theory Article

Prospects to verify a possible dark matter hint in cosmic antiprotons with antideuterons and antihelium

Cosmic rays are an important tool to study dark matter annihilation in our Galaxy. Recently, a possible hint for dark matter annihilation was found in the antiproton spectrum measured by AMS-02, even though the result might be affected by theoretical uncertainties. A complementary way to test its dark matter interpretation would be the observation of low-energy antinuclei in cosmic rays. We determine the chances to observe antideuterons with GAPS and AMS-02, and the implications for the ongoing AMS-02 antihelium searches. We find that the corresponding antideuteron signal is within the GAPS and AMS-02 detection potential. If, more conservatively, the putative signal was considered as an upper limit on DM annihilation, our results would indicate the highest possible fluxes for antideuterons and antihelium compatible with current antiproton data.Comment: 11 pages, 5 figures, matches published versio

Client-server multi-task learning from distributed datasets

A client-server architecture to simultaneously solve multiple learning tasks from distributed datasets is described. In such architecture, each client is associated with an individual learning task and the associated dataset of examples. The goal of the architecture is to perform information fusion from multiple datasets while preserving privacy of individual data. The role of the server is to collect data in real-time from the clients and codify the information in a common database. The information coded in this database can be used by all the clients to solve their individual learning task, so that each client can exploit the informative content of all the datasets without actually having access to private data of others. The proposed algorithmic framework, based on regularization theory and kernel methods, uses a suitable class of mixed effect kernels. The new method is illustrated through a simulated music recommendation system

Opinion influence and evolution in social networks: a Markovian agents model

In this paper, the effect on collective opinions of filtering algorithms managed by social network platforms is modeled and investigated. A stochastic multi-agent model for opinion dynamics is proposed, that accounts for a centralized tuning of the strength of interaction between individuals. The evolution of each individual opinion is described by a Markov chain, whose transition rates are affected by the opinions of the neighbors through influence parameters. The properties of this model are studied in a general setting as well as in interesting special cases. A general result is that the overall model of the social network behaves like a high-dimensional Markov chain, which is viable to Monte Carlo simulation. Under the assumption of identical agents and unbiased influence, it is shown that the influence intensity affects the variance, but not the expectation, of the number of individuals sharing a certain opinion. Moreover, a detailed analysis is carried out for the so-called Peer Assembly, which describes the evolution of binary opinions in a completely connected graph of identical agents. It is shown that the Peer Assembly can be lumped into a birth-death chain that can be given a complete analytical characterization. Both analytical results and simulation experiments are used to highlight the emergence of particular collective behaviours, e.g. consensus and herding, depending on the centralized tuning of the influence parameters.Comment: Revised version (May 2018