Quantum annealing and the Schr\"odinger-Langevin-Kostin equation

We show, in the context of quantum combinatorial optimization, or quantum annealing, how the nonlinear Schr\"odinger-Langevin-Kostin equation can dynamically drive the system toward its ground state. We illustrate, moreover, how a frictional force of Kostin type can prevent the appearance of genuinely quantum problems such as Bloch oscillations and Anderson localization which would hinder an exhaustive search.Comment: 5 pages, 4 figures. To appear on Physical Review

A solvable model of quantum random optimization problems

We study the quantum version of a simplified model of optimization problems, where quantum fluctuations are introduced by a transverse field acting on the qubits. We find a complex low-energy spectrum of the quantum Hamiltonian, characterized by an abrupt condensation transition and a continuum of level crossings as a function of the transverse field. We expect this complex structure to have deep consequences on the behavior of quantum algorithms attempting to find solutions to these problems.Comment: 4 pages, 3 figures, accepted versio

First-order transitions and the performance of quantum algorithms in random optimization problems

We present a study of the phase diagram of a random optimization problem in presence of quantum fluctuations. Our main result is the characterization of the nature of the phase transition, which we find to be a first-order quantum phase transition. We provide evidence that the gap vanishes exponentially with the system size at the transition. This indicates that the Quantum Adiabatic Algorithm requires a time growing exponentially with system size to find the ground state of this problem.Comment: 4 pages, 4 figures; final version accepted on Phys.Rev.Let

Grover's algorithm on a Feynman computer

We present an implementation of Grover's algorithm in the framework of Feynman's cursor model of a quantum computer. The cursor degrees of freedom act as a quantum clocking mechanism, and allow Grover's algorithm to be performed using a single, time-independent Hamiltonian. We examine issues of locality and resource usage in implementing such a Hamiltonian. In the familiar language of Heisenberg spin-spin coupling, the clocking mechanism appears as an excitation of a basically linear chain of spins, with occasional controlled jumps that allow for motion on a planar graph: in this sense our model implements the idea of "timing" a quantum algorithm using a continuous-time random walk. In this context we examine some consequences of the entanglement between the states of the input/output register and the states of the quantum clock

Metaservizi per la produzione collaborativa di moduli didattici in ambienti sociali = Social metaservices for the collaborative production of learning modules

In queste pagine si introduce una piattaforma a servizio degli usuali Learning Management Systems (LMS) per consentirne un utilizzo facile e proficuo da parte dei docenti di un determinato settore. Nello specifico la piattaforma costituisce il supporto informativo a un ampio progetto di promozione dell\u2019educazione all\u2019imprenditorialit\ue0 lanciato dalla Comunit\ue0 Europea. La chiave di volta \ue8 costituta dai metadati con cui sono descritti i suoi contenuti. Questi metadati sono alla base delle procedure d\u2019interrogazione e raccomandazione, nonch\ue9 di altre azioni \u201csocial\u201d sulle quali i docenti possono contare per reperire il materiale su cui fondare i corsi che intendono erogare. In tal prospettiva la piattaforma s\u2019identifica con una social network per utenti esigenti, appunto i docenti, che si aspettano di reperire nel sistema materiali autorevoli e appropriati, essendo capaci di valutarne tali aspetti e al contempo desiderosi di venire guidati nella loro ricerca all\u2019interno dell\u2019ampio repertorio messo a disposizione dalla piattaforma.In this paper we introduce a platform designed to help educators make profitable use of current LMSs for teaching in a particular domain. The platform has been developed within a major European Commission funded project for the promotion of Entrepreneurship Education (EE). The conceptual core of the platform is the metadata for describing content. These metadata form the basis for query and recommender systems, as well as for other socially oriented services designed to help teachers retrieve suitable material for their courses. Seen in this light, the platform is a social network for a very demanding user group, namely teachers. They use the environment as a means to locate material considered authoritative and appropriate, and at the same time seek platform support for searching the system\u2019s considerable repository

The SandS Ecosystem, a True Instance of WEB4.0

We introduce a peculiar ecosystem aimed at ruling in remote the household appliances of the members of a special social network. The keen feature of the social network is a networked intelligence, equipped with cognitive tools that enable it to provide services fully compliant with the members\u2019 needs. The scheme is the following: The appliances are internet-connected through the home Wi-Fi router. The user asks the social network for a task to be executed by his appliance (for instance, washing three kilos of woollen coloured laundry), the network, in the role of an electronic super-mom, sends directly to the washing machine an optimal sequence of commands the recipes (such as: warm the water at 34\ub0, soak for 57 minutes, etc.) to execute the task in a way that matches the user preferences, possibly green goals included. Feedbacks are sent by user and appliances themselves to the network intelligence to close the permanent recipe optimization loop, with offline advice on the part of appliance manufacturers. A properly devised user interface allows a friendly and accurate management of all interactions between the user and the social network, constituting the user-centric support of the cognitive driven services representing a genuine instance of WEB 4.0

Tight Bounds for SVM Classification Error

We find very tight bounds on the accuracy of a Support Vector Machine classification error within the Algorithmic Inference framework. The framework is specially suitable for this kind of classifier since (i) we know the number of support vectors really employed, as an ancillary output of the learning procedure, and (ii) we can appreciate confidence intervals of misclassifying probability exactly in function of the cardinality of these vectors. As a result we obtain confidence intervals that are up to an order narrower than those supplied in the literature, having a slight different meaning due to the different approach they come from, but the same operational function. We numerically check the covering of these intervals

Some Thoughts About Appealing Directions for the Future of Fuzzy Theory and Technologies Along the Path Traced by Lotfi Zadeh

The quoted text is an interesting instance of a fuzzy object: it is currently known in slightly diversified forms, each rather different from the quoted one, which corresponds to the first known appearance in English of this adage