Interferometric modulation of quantum cascade interactions

We consider many-body quantum systems dissipatively coupled by a cascade network, i.e. a setup in which interactions are mediated by unidirectional environmental modes propagating through a linear optical interferometer. In particular we are interested in the possibility of inducing different effective interactions by properly engineering an external dissipative network of beam-splitters and phase-shifters. In this work we first derive the general structure of the master equation for a symmetric class of translation-invariant cascade networks. Then we show how, by tuning the parameters of the interferometer, one can exploit interference effects to tailor a large variety of many-body interactions.Comment: 12 pages, 10 figure

Interferometric Quantum Cascade Systems

In this work we consider quantum cascade networks in which quantum systems are connected through unidirectional channels that can mutually interact giving rise to interference effects. In particular we show how to compute master equations for cascade systems in an arbitrary interferometric configuration by means of a collisional model. We apply our general theory to two specific examples: the first consists in two systems arranged in a Mach-Zender-like configuration; the second is a three system network where it is possible to tune the effective chiral interactions between the nodes exploiting interference effects.Comment: 15 pages, 5 figure

A data driven equivariant approach to constrained Gaussian mixture modeling

Maximum likelihood estimation of Gaussian mixture models with different class-specific covariance matrices is known to be problematic. This is due to the unboundedness of the likelihood, together with the presence of spurious maximizers. Existing methods to bypass this obstacle are based on the fact that unboundedness is avoided if the eigenvalues of the covariance matrices are bounded away from zero. This can be done imposing some constraints on the covariance matrices, i.e. by incorporating a priori information on the covariance structure of the mixture components. The present work introduces a constrained equivariant approach, where the class conditional covariance matrices are shrunk towards a pre-specified matrix Psi. Data-driven choices of the matrix Psi, when a priori information is not available, and the optimal amount of shrinkage are investigated. The effectiveness of the proposal is evaluated on the basis of a simulation study and an empirical example

e-{\mu} Discrimination at High Energy in the JUNO Detector

Cosmic Ray and neutrino oscillation physics can be studied by using atmospheric neutrinos. JUNO (Jiangmen Underground Neutrino Observatory) is a large liquid scintillator detector with low energy detection threshold and excellent energy resolution. The detector performances allow the atmospheric neutrino oscillation measurements. In this work, a discrimination algorithm for different reaction channels of neutrino-nucleon interactions in the JUNO liquid scintillator, in the GeV/sub-GeV energy region, is presented. The atmospheric neutrino flux is taken as reference, considering $\overset{(-)}{\nu_\mu}$ and $\overset{(-)}{\nu_e}$. The different temporal behaviour of the classes of events have been exploited to build a time profile-based discrimination algorithm. The results show a good selection power for $\overset{(-)}{\nu_e}$ CC events, while the $\overset{(-)}{\nu_\mu}$ CC component suffers of an important contamination from NC events at low energy, which is under study. Preliminary results are presented.Comment: Proceeding for poster presented at the 7th Roma International Conference on AstroParticle Physic

An example of integration between en economic and an hydrologic model in the framework of water resource management problems

Growing scarcity, increasing demand and bad management of water resources are causing weighty competition for water and consequently managers are facing more and more pressure in an attempt to satisfy users? requirement. In many regions agriculture is one of the most important users at river basin scale since it concentrates high volumes of water consumption during relatively short periods (irrigation season), with a significant economic, social and environmental impact. The interdisciplinary characteristics of related water resources problems require, as established in the Water Framework Directive 2000/60/EC, an integrated and participative approach to water management and assigns an essential role to economic analysis as a decision support tool. For this reason, a methodology is developed to analyse the economic and environmental implications of water resource management under different scenarios, with a focus on the agricultural sector. This research integrates both economic and hydrologic components in modelling, defining scenarios of water resource management with the goal of preventing critical situations, such as droughts. The model follows the Positive Mathematical Programming (PMP) approach, an innovative methodology successfully used for agricultural policy analysis in the last decade and also applied in several analyses regarding water use in agriculture. This approach has, among others, the very important capability of perfectly calibrating the baseline scenario using a very limited database. However one important disadvantage is its limited capacity to simulate activities non-observed during the reference period but which could be adopted if the scenario changed. To overcome this problem the classical methodology is extended in order to simulate a more realistic farmers? response to new agricultural policies or modified water availability. In this way an economic model has been developed to reproduce the farmers? behaviour within two irrigation districts in the Tiber High Valley. This economic model is then integrated with SIMBAT, an hydrologic model developed for the Tiber basin which allows to simulate the balance between the water volumes available at the Montedoglio dam and the water volumes required by the various irrigation users

Clinical, Histological and Trichoscopic Correlations in Scalp Disorders

Trichoscopy is the term coined for the dermoscopic imaging of scalp and hair. This diagnostic technique, simple and noninvasive, can be used as a handy bedside tool for the diagnosis and follow-up of hair and scalp disorders. It allows the recognition of morphologic structures not visible by the naked eye and provides the clinician with a range of dermoscopic findings necessary for differential diagnosis. Trichoscopy observation can be broadly grouped as interfollicular patterns and follicular patterns. Recently, a third mixed class, called the follicular plus interfollicular pattern, has been introduced. Some of these features are specific to a certain scalp disease, while others can be found in many hair disorders. Although studies suggest that the use of trichoscopy can improve clinical accuracy, further investigation is needed. This review provides update information on the trichoscopic features of the most common scalp disorders, striving to show a histopathological and clinical correlation

Study of the performance of standard RPC chambers as a function of bakelite temperature

A systematic study of the performance of the Resistive Plate Chambers as a function of the bakelite temperature is presented. The current, the rate and the efficiency were measured in the temperature range 22-40degreesC. The values of the relative humidity during the data taking were in the range 40-60%. Measurements show a strong dependence of the efficiency on bakelite temperature. (C) 2003 Elsevier Science B.V. All rights reserved