1,721,293 research outputs found
Time-polynomial Lieb-Robinson bounds for finite-range spin-network models
Full text linkThe Lieb-Robinson bound sets a theoretical upper limit on the speed at which information can propagate in nonrelativistic quantum spin networks. In its original version, it results in an exponentially exploding function of the evolution time, which is partially mitigated by an exponentially decreasing term that instead depends upon the distance covered by the signal (the ratio between the two exponents effectively defining an upper bound on the propagation speed). In the present paper, by properly accounting for the free parameters of the model, we show how to turn this construction into a stronger inequality where the upper limit only scales polynomially with respect to the evolution time. Our analysis applies to any chosen topology of the network, as long as the range of the associated interaction is explicitly finite. For the special case of linear spin networks we present also an alternative derivation based on a perturbative expansion approach which improves the previous inequality. In the same context we also establish a lower bound to the speed of the information spread which yields a nontrivial result at least in the limit of small propagation times
Iterative Probabilistic Performance Prediction for Multiple IoT Applications in Contention
No full textInternet of Things (IoT) has become omnipresent in many applications, such as healthcare, vehicles, and precision farming. They sense data from dozens of sensors scheduled periodically in a synchronous fashion on mobile CPUs that are forwarded to the cloud or other IoT devices via an essentially stochastic wireless channel. Hence, the task response time becomes stochastic, preventing optimization at compile time. On the other hand, knowing response time at compile time along with jitter, availability, and scalability is crucial to ensure a certain level of Quality of Service. This contribution presents a stochastic framework for performance analyses of multiapplications on a possible multiprocessor platform. When annotated with (stochastic) execution time, a traditional synchronous dataflow (SDF) graph can be transformed into a directed acyclic workflow graph, revealing the timing of individual actors. A generalized version of the rejection sampling Monte Carlo algorithm explores the properties of the workflow graph, to determine the distribution of the response time in a single application as well as a multiapplication multiple access scenario. Mean and jitter are the moments of the distribution. An IoT toy example with a number of distributed smart sensors was deployed in real environments to assess the performance of the proposed framework. Our analysis framework works at compile time of the code, scales with the number of things, and has low computational complexity
Quantum capacity analysis of multi-level amplitude damping channels
Full text linkEvaluating capacities of quantum channels is the first purpose of quantum Shannon theory, but in most cases the task proves to be very hard. Here, we introduce the set of Multi-level Amplitude Damping quantum channels as a generalization of the standard qubit Amplitude Damping Channel to quantum systems of finite dimension d. In the special case of d = 3, by exploiting degradability, data-processing inequalities, and channel isomorphism, we compute the associated quantum and private classical capacities for a rather wide class of maps, extending the set of models whose capacity can be computed known so far. We proceed then to the evaluation of the entanglement assisted quantum and classical capacities
Interazioni montaliane
No full textSOMMARIO DEL NUMERO: M. Tortora, L’incipit di Ossi di seppia. Pan, il meriggio e fonti nietzschiane ne "I limoni" di Eugenio Montale; R. Luperini, Il desiderio e la sua negazione. Su "Felicità raggiunta, si cammina"; P.V. Mengaldo, Un’evoluzione: dagli "Ossi di seppia" ai " Mottetti"; F. Bausi, Verità biografica e verità poetica nei mottetti; R. Leporatti, Montale al crocevia del classicismo moderno: lettura di "Barche sulla Marna"; S. Carrai, Loria, Clizia e il retroscena di "Un sogno, uno dei tanti" di Montale; A. Aveto, Sette lettere di Eugenio Montale a «La Fiera letteraria» (1927); C.A. Girotto, Cinque lettere di Eugenio Montale a Mario Fubini; S. Chessa, "Indispensabili antidoti". Eugenio Montale e Giuseppe De Robertis; M.A. Grignani, Montale, una laurea, la Svizzera; F. Castellano, "Une heure avec Montale". Interviste disperse
Understanding Human Mobility for CrowdSensing Strategies with the ParticipAct Data Set
Full text linkThe Mobile CrowdSensing (MCS) paradigm has been increasingly adopted in the last years. Its adoption has been proved as beneficial for different scenarios, such as environmental monitoring and mobility analysis. However, one of the major barriers of the MCS initiatives, is the difficulty in recruiting users for the purpose of collecting data. We focus in this work to such limitation, and we analyze the mobility traces collected with a real-world MCS experiment, namely ParticipAct. Our goal is to discuss how to exploit the mobility features of the recruited users, as grounding information to plan and optimize a MCS data collection campaign. In detail, we analyze the quality of the data set, its accuracy and several features of human mobility such as radius of gyration and the real entropy of the locations visited. We discuss the impact of such metrics on the task scheduling, allocation and how to obtain a certain Tcoverage of data from visited locations
Evaluation of a Location Coverage Model for Mobile Edge Computing
No full textThe Mobile Edge Computing paradigm shifts the computation back to places where it is required. A traditional MEC architecture comprises a number of Edge Data Centers (EDC) in charge of seamlessly providing services to users with wireless network technologies. In this scenario, it becomes crucial to deploy the EDCs in strategic locations, such as highly visited places. In this paper we focus on the deployment phase of an EDC. In particular, we propose a probabilistic model designed to measure the location converge, namely the probability that a candidate location for an EDC is visited by users. Our model is based on the analysis of user's trajectories and on the probability of detouring towards the target locations for the EDS. The information returned by our model offers the possibility of implementing mobility-aware deployment strategies in urban environments. We test the model with two real-world mobility data sets, evaluating its applicability of realistic settings
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